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보건학석사 학위논문

Characterization of Organic Compounds

in Ambient PM2.5 Measured at Seoul,

Korea

서울시 관악구 대기 중 PM2.5의 유기성분 특성

2020년 2월

서울대학교 보건대학원

환경보건학과 대기환경전공

정 소 영

I

Abstract

Characterization of Organic Compounds

in Ambient PM2.5 Measured at Seoul,

Korea

Soyoung Jung

Department of Environmental Health Sciences

The Graduate School of Public Health

Seoul National University

Fine particulate matter(PM2.5) which is one of the major air pollutants, is emitted

by diverse natural and anthropogenic sources and affects not only human health but

also the living environment. PM2.5 is composed of varied constituents such as water-

soluble ions, heavy metals, elemental carbon, and organic carbon. Organic matter

contains various organic compounds which have different emission characteristics

depend on each emission source. Thus, identifying the emission characteristic is

possible by characterizing the concentration of various organic compounds. The aim

of this study is to figure out organic speciation of PM2.5 and to identify major

emission sources by using diverse parameters and chemical species in PM2.5

collected from June 2018 to May 2019 in Seoul, Korea. The average PM2.5 mass

concentration during the study period was 26.4 ± 21.5 ㎍/m3. During the sampling

period, winter (36.9 ± 15.6 ㎍/m3) and spring (35.5 ± 34.3 ㎍/m3) showed higher

II

value than fall (17.5 ± 11.9 ㎍/m3) and summer (17.5 ± 10.1 ㎍/m3) relatively.

Among the organic compounds such as PAHs, the total average concentration of

sugars and glyceride (71.2±69.4 ng/m3) showed the highest concentration

throughout the year. Despite the low concentration of PAHs, the possible emission

sources were identified by using PAHs diagnostic ratio; Flt/(Flt+Pyr) against

ANT/(ANT+PHE). As a result, it is assumed that Seoul is Seoul is mostly influenced

by pyrogenic sources. n-Alkanes showed the seasonal patterns well in this study

which are high concentration in winter and low concentration in summer. According

to the n-alkanes parameters, Cmax, CPI and WNA, the sampling area was influenced

by various sources, especially vegetative detritus. The Principal component analysis

(PCA) was performed to identify the possible emission sources in the sampling area.

Total 4 factors were identified to possible emission sources; biomass burning

(44.381 %), secondary organic aerosols (SOAs) (19.745 %), vehicle emission

(6.873 %), biogenic secondary organic aerosols (5.935 %). According to the result

of PCA, the sampling region, Gwanak district, were possibly influenced by PM2.5

originated from both biomass burning and SOAs.

Keywords : Fine particulate matter (PM2.5), Organic compounds,

Organic molecular markers, Organic speciation, Source

identification, Principal Component Analysis (PCA)

Student Number : 2018-21005

III

Contents

Abstract ................................................................................................... I

List of Tables ........................................................................................ IV

List of Figures ..................................................................................... VII

1. Introduction ........................................................................................ 1

2. Materials and methods ....................................................................... 4

2.1. Sample collection and analysis .............................................................. 4

2.2. Data analysis ...................................................................................... 13

3. Result and Discussion ....................................................................... 16

3.1. Chmical constituents. .......................................................................... 16

3.2. Principal Component Analysis ............................................................ 31

4. Conclusion ......................................................................................... 34

5. Referrence ......................................................................................... 36

6. Supplemental Materials .................................................................... 40

IV

List of Tables

Table 1. Summary of other studies associated with the organic speciation of

PM2.5 .................................................................................................................. ３

Table 2. OC/EC operation program for carbonaceous analysis performed in

this study. .......................................................................................................... ６

Table 3. Targeted organic groups with individual organic compounds in this

study. ............................................................................................................. １０

Table 4. GC/MSD analysis condition in this study. ...................................... １１

Table 5. PAHs diagnostic ratio ...................................................................... １４

Table 6. Summary of PM2.5 species concentrations collected in Seoul during

the whole sampling period (June 1, 2018 ~ May 27, 2019) ........................... １８

Table 7. PAHs compounds depending on its number of benzene rings ....... ２５

Table 8. Summary of carbon preference index (CPI) and the wax n-alkanes

percentage (WNA%) in this study and comparison with other studies. ...... ３０

Table 9. PCA analysis of PM2.5 with factor loading results during sampling

period ............................................................................................................ ３３

Table 14. Information of target non-polar compounds (PAHs) ................... ４０

Table 15. Information of target non-polar compounds (n-Alkanes) ............ ４１

Table 16. Information of target non-polar compounds (Hopane, Steranes,

Alkylcyclohexanes and Isoprenoids)............................................................. ４２

V

Table 17. Information of target polar compounds (Aliphatic diacids and

Benzencarboxylic acids) ................................................................................ ４３

Table 18. Information of target polar compounds (Alkanoic acids) ............ ４４

Table 19. Information of target polar compounds (Fatty acids, sugars and

glycerides) ..................................................................................................... ４５

Table 20. Information of target polar compounds (Sterols and

Methoxyphenols) ........................................................................................... ４６

Table 21. Information of target polar compounds (Resin acids).................. ４７

Table 22. Spike volume (ul) and final spike concentration (ng/ul) of

surrogate/internal standard used in this study............................................. ４８

Table 23. Summary of quality assurance and quality controls (QAQC) data

(PAHs) ........................................................................................................... ４９

Table 24. Summary of quality assurance and quality controls (QAQC) data (n-

Alkanes) ......................................................................................................... ５０


(Hopanes & Steranes) ................................................................................... ５１


(Alkylcyclohexanes) ...................................................................................... ５２


(Aliphatic Diacids) ........................................................................................ ５３


(Benzencarboxylic acids) .............................................................................. ５４

VI


(Alkanoic acids) ............................................................................................. ５５


(Fatty acids)................................................................................................... ５６


(Sugar & glyceride) ....................................................................................... ５７


(Sterols) ......................................................................................................... ５８


(Methoxyphenols).......................................................................................... ５９


(Resin Acids).................................................................................................. ６０

VII

List of Figures

Figure 1. Location of sampling site in Seoul, Korea ......................................... ４

Figure 2. Time series plots of Temperature and RH (A), OC/EC ratio and

PM2.5 (B), OC and EC (C), and Ionic species (D) concentrations from June 1,

2018 to May 27, 2019..................................................................................... ２１

Figure 3. Time series plots of organic molecular marker compounds from June

1, 2018 to May 27, 2019 summed by its class ................................................ ２３

Figure 4. Seasonal differences of organic species by its categories in this study

....................................................................................................................... ２４

Figure 5. Monthly average concentration (ng/m3) (A) and percentage (%) (B)

of PAHs depending on the number of benzene rings in this study............... ２６

Figure 6. A scatter plot of Flt/(Flt+Pyr) against ANT/(ANT+PHE) in this study

....................................................................................................................... ２７

Figure 7. Seasonal concentration trends of n-Alkanes in this study ............ ２９

１

1. Introduction

Fine particulate matter (PM2.5) which is well-known as one of the major air

pollutants is defined as a mixture of solid or liquid matter found in the atmosphere,

with diameters that are less than 2.5 ㎛. PM2.5 is emitted by diverse natural and

anthropogenic sources such as volcanic eruption, fossil fuels, biomass burning and

mobile sources and it affects not only human health but also the living environment.

PM2.5 is classified as carcinogenic pollutants to humans (WHO, 2013) and it is able

to triggered adverse health effects related to cardiovascular and respiratory diseases

(Dominici et al., 2006). It also impacts on the reduced visibility (Tao et al., 2009) as

well as climate change (Tai, Mickley, & Jacob, 2010).

PM2.5 is composed of varied constituents such as water-soluble ions, heavy

metals, elemental carbon (EC) and organic carbon (OC). Organic matter is a major

component of PM2.5 and accounts for 10~80 % of its total mass (Baltensperger &

Prévôt, 2008). It contains over thousands individual organic compounds which have

unique emission characteristics depend on its emission sources (Gonçalves et al.,

2011; Zheng, Fang, Wang, & To, 2000) . Therefore, it is necessary to understand the

characteristics of organic species in order to identify its emission sources.

Since NRC report (1998) showed the human health risk increases due to the

exposure of particulate matter, many studies have been reported that the organic

compounds such as polycyclic aromatic hydrocarbons (PAHs) in PM2.5 are highly

associated with the increase of human health risk (Kim, Jahan, Kabir, & Brown, 2013;

Oh, Kim, Park, Lee, & Chung, 2011). In order to identify the relationship between

organic species and human health risks, varied studies analyzing individual organic

２

compounds have been conducted (Callén, Iturmendi, & López, 2014).

However, those organic compounds exist in trace levels in the atmosphere and

only 10~30 % of the total particulate organic compound mass can be quantified as

individual organic species. Despite those difficulties, qualitative and quantitative

studies over 100 individual compounds have been conducted overseas (Dutton,

Williams, Garcia, Vedal, & Hannigan, 2009; Fraser, Yue, Tropp, Kohl, & Chow, 2002;

Schauer & Cass, 2000; Wang et al., 2016; Zheng et al., 2005), but only some studies

have been performed in Korea (Choi, Heo, Ban, Yi, & Zoh, 2012; Park et al., 2006).

Thus, the objectives of this study are (1) to characterize the concentration of organic

compounds with seasonal variations, (2) to identify major emission sources around

the sampling site by using various diagnostic parameters and statistical model which

referred as Principal component analysis (PCA), and (3) to establish a qualitative

and quantitative database suitable for Korea.

３

Table 1. Summary of other studies associated with the organic speciation of PM2.5

Reference Schauer, J. J. and

Cass, G.R., 2000 Fraser et al., 2002 Zheng et al., 2005 Park et al., 2006 Dutton et al., 2009 Choi et al., 2012 Wang et al., 2016

Study Site California, USA Houston, USA Beijing, China Gwangju, Korea Colorado, USA Incheon, Korea Guangzhou, China

Study periods 1995-1996 1997-1998 2000 2001 2002-2003 2009-2010 2012-2013

PAHs 23.8-100

(19 species)

0.65-14.8

(25 species)

23.2-438

(26 species)

13.2-26.7

(22 species)

2.71

(18 species)

2.60-21.4

(16 species)

10.4-45.5

(17 species)

n-Alkanes 98.0-216

(C24-C33)

4.19-39.4

(C16-C33)

98.3-706

(C17-C38)

19.0-257

(C24-C36)

17.0

(C22-C40)

109-266

(C17-C34)

26.2-103

(C14-C40)

Hopanes & steranes - 0.29-4.16

(8 species)

9.16-26.38

(15 species) -

1.29

(10 species)

0.99-1.40

(10 species)

1.20-1.65

(3 species)

Alkylcyclohexanes - 0.41-4.77

(5 species) -

0.31

(2 species) - -

Aliphatic Diacids - 13.6-54.2

(C3-C10) -

0.80-84.0

(C4-C9) -

0.87-10.97

(4 species) -

Benzencarboxylic

acids 22.0-32.1 -

33.4-86.0

(5 species)

4.4-30.7

(6 species) - - -

Alkanoic/Fatty

acids

333-979

(C10-C30)

45.6-135

(C10-C26)

147-436

(C14-C30)

31.0-223

(C14-C30)

38.9

(7 species)

91.6-148

(C6-C24) -

Sugar&Glyceride 1271-8660 7.97-51.96

(Levoglucosan)

473-2407

(Levoglucosan)

18.1-1753

(Levoglucosan) -

1.42-66.1

(Levoglucosan) -

Sterols - - - 0.5-2.6

(Cholesterol)

0.59

(2 species)

1.03-2.44

(Cholesterol) -

Methoxyphenols 60.9-876

(18 species) - - -

5.72

(5 species) - -

Resin Acids 22.2-296

(9 species) -

81.3-312

(8 species)

15.6-27.2

(9 species) - - -

Other organic

compounds 9.23-627 - - 92.0-1866 -

41.8-149

(15 species) -

４

2. Materials and Methods

2.1. Sample collection and analysis

2.1.1. Sampling site

Ambient PM2.5 samples were collected on the rooftop of Graduate School of

Public Health Building at Seoul National University (37.581°N, 127.001°E, 21m

above ground level) in Seoul, Korea. The Seoul National University is situated on

the mountainside referred to as Gwanak Mountain and surrounded by multiple roads.

Not only residential and commercial districts are located near the region, but also

industrial complex located in the southwest side influences sampling region,

Gwanak district. The sampling site is affected by various local sources as well as

long range transported pollutants by westerlies.

Figure 1. Location of sampling site in Seoul, Korea

５

2.1.2. Sampling method

PM2.5 samples (n=63) for PM2.5 mass concentration, carbonaceous species

(organic carbon and elemental carbon) and ionic species were collected every 6 days

over a 23-hour period from June 1, 2018 to May 27, 2019. For the analysis of mass

concentration, carbonaceous species and ionic species, Teflon filter (47 mm, 1.0 ㎛

pore size, Pall corporation, USA) and quartz filter (47 mm, 1.0 ㎛ pore size, Pall

corporation, USA), PTFE filter (47 mm, 1.0 ㎛ pore size, Pall corporation, USA)

were used with low volume air samplers. The low volume air samplers consisting of

filter pack system (URG-2000-30FG, URG, USA) and cyclone (URG-2000-30EH,

URG, USA) were used within the 10% range of 16.7 L/min flow rate. In order to

analyze the organic compounds existing in trace level, high-volume PM2.5 samples

were collected on quartz filter (QMA 1851-865, 203mm x 254mm, Whatman, UK)

by using high volume air sampler (TE-HVPLUS, TISCH, USA) with impactor filter

(TE-230-QZ, TISCH, USA) at a flow rate of 40 cubic feet per minute (CFM).

Teflon filter used for mass concentration measurement was stored in desiccator

(SA0010, Sanplatec, Japan) for 24 hours and was weighed with microbalance

(CPA225D, Sartorius, Germany) before and after the sampling. Quartz filters for

both low and high volume were baked at 450 ℃ for 12 hours to remove pre-existing

organic matters before sampling. PTFE filter were soaked with ethanol and distilled

deionized water (18.2 MΩ cm of conductivity) in turn, twice. All collected filters

were kept in the freezer under -20 ℃ until further analysis.

６

2.1.3. Chemical speciation analysis

2.1.3.1. Organic carbon (OC) and Elemental carbon (EC)

Organic carbon (OC) and elemental carbon (EC) concentration were analyzed

by using Carbon Aerosol Analyzer (Model 3, Sunset Laboratory Inc., USA). The

quartz filter was punched to 1.5 cm × 1.0 cm and analyzed by the analyzer by using

the thermal/optical transmittance (TOT) method with the National Institute of

Occupational Safety and Health (NIOSH) 5040 protocol (Table 2). The instrument

was calibrated with a 5 % methane in helium mixture gas and 0.02 M of sucrose

solution (#57-50-1, USB Corporation, USA), respectively. Percent relative standard

deviation (%RSD) was calculated, and was within 5 % nominal value. LOD was

calculated as 3 times standard deviation of 4 blanks.

Table 2. OC/EC operation program for carbonaceous analysis performed in this study.

Step Carrier Gas Ramp Time

(seconds)

Program Temperature

(℃)

OC

Step 1

Helium (He)

80 310

Step 2 60 475

Step 3 60 650

Step 4 90 870

Helium (He) Cool down

EC

Step 5

2% O2 in He

45 550

Step 6 45 625

Step 7 45 700

Step 8 45 775

Step 9 45 850

Step 10 120 870

CH4 gas + He/O2 External Std. Calibration and cool down

７

2.1.3.2. Ionic species (NO3-, SO4

2- and NH4+)

Anions (NO3- and SO4

2-) and Cation (NH4+) were speciated using Ion

chromatography (IC, Dionex Co., DX-1100, USA). PTFE filter collected PM2.5

were extracted in 30 ml of distilled deionized water and ultrasonicated for 60 ℃ for

4 hours. Extracted samples were stored overnight and filtered using syringe and disc

filter (PALL science, 0.2 um pore size). The extracted solution was moved to IC auto

sampler vials. The IC analysis was performed by using the anion column (Ionpac

AS14A 4, 250 mm) and the cation column (Ionpac CS12A 4, 250 mm). For anion

eluent, Na2CO3 with NaHCO3 dissolved in DI water, and for cation eluent, Methane

Sulfonic Acid (MSA) solution with DI water is used.

８

2.1.3.3. Organic speciation

For analyzing the organic compounds, the PM2.5 samples were extracted with

ultrasonication method. The collected quartz filters were punched (4 cm x 4 cm x 3

ea) and were spiked with a deuterated internal standards containing 18 isotopically

labeled compounds (Acenaphthene-d10, Pyrene-d10, Benz[a]anthracene-d12,

Coronene-d12, Pentadeane-d32, Eicosane-d42, Tetracosane-d50, Triacontane-d58,

Dotriacontane-d66, Hexatriacontane-d74, Cholestane-d4, Succinic acid-d4,

Tetradeanoic Acid-d27, Phthalic Acid-d4, Heptadecanoic Acid-d33, Eicosanoic Acid-

d39, Levoclucosan-13C6, and Cholesterol-d6). These were extracted twice using

ultrasonication with 30 mL of mixture of dichlomethane (DCM; HPLC grade, J. T.

Baker, USA) and methanol (HPLC grade, J. T. Baker, USA) (3:1, v/v) for 30minutes.

The combined extracts were concentrated with nitrogen gas to a volume of

approximately 5 ~ 10 mL using Turbovap II (Zymark, USA), and then were filtered

with an Acrodisc syringe filters (0.45 ㎛-pore size, 25 mm, PALL, USA). The

filtered extracts were finally concentrated to 0.5 mL in 2 ml vials (5182-0716,

Agilent, USA). To analyze polar compounds, 50 ㎕ from the final concentrates was

taken using wiretrols (Drummond®, USA) and completely fried with nitrogen gas.

50 ㎕ of N, O-bis- (trimethylsilyl)trifluoroacetamide (BSTFA) with 1 %

trimethylchlorosilane (TMCS) (99 %, Sigma Aldrich, USA) and 50 ㎕ of pyridine

(HPLC grade, Sigma Aldrich, USA) were added for the silylation process, which is

derivatization transformed the chemicals by removing the polarity groups (Jaoui,

９

Kleindienst, Lewandowski, & Edney, 2004). The reaction lasted for 90 minutes at

75 ℃. The silylated samples were analyzed within 3 days. The remainder of final

concentration was used for the analysis of non-polar compounds. All compounds

described in Table 3 were analyzed by gas chromatography/mass spectrometry

(GC/MS; 7890A/5975C TAD for non-polar compounds, 7890B/5977B for polar-

compounds, Agilent Technologies, USA) with GC/MS analysis conditions as shown

in the Table 4, respectively.

１０

Table 3. Targeted organic groups with individual organic compounds in this study.

Non-polar compounds Polar compounds

PAHs n-Alkanes Hopanes & steranes Aliphatic Diacids Alkanoic acids Sterols Naphthalene n-C10 (Decane) AAA-20S-C27-Cholestane Malonic (C3) C6:0 (Hexanoic acid) Coprostanol

1-Methylnaphthalene n-C11 (Undecane) ABB-20R-C27-Cholestane Maleic (C3=) C8:0 (Octanoic acid) Cholesterol

2-Methylnaphthalene n-C12 (Dodecane) ABB-20R-C28-Methylcholestane Succinic (C4) C10:0 (Decanoic acid) Cholestanol

2,6-Dimethylnaphthalene n-C13 (Tridecane) 17A(H)-22,29,30-Trisnorhopane Fumaric (C4=) C12:0 (Dodecanoic acid) Stigmasterol

Acenaphthylene n-C14 (Tetradecane) ABB-20R-C29-Ethylcholestane Glutaric (C5) C14:0 (Tetradecenoic acid) B-Sitosterol

Acenaphthene n-C15 (Pentadecane) 17A(H)-21B(H)-30-Norhopane Adipic (C6) C16:0 (Hexadecanoic acid) Stigmastanol

Fluorene n-C16 (Hexadecane) 17A(H)-21B(H)-Hopane Pimelic (C7) C18:0 (Octadecanoic acid) Methoxyphenols

Phenanthrene n-C17 (Heptadecane) Alkylcyclohexanes Suberic (C8) C20:0 (Eicosanoic acid) Vanillin

Anthracene n-C18 (Octadecane) Dibenzofuran Azelaic (C9) C22:0 (Docosanoic acid) Iso-Eugenol

9-Methylanthracene n-C19 (Nonadecane) 9-Methylfluorene Sebacic (C10) C24:0 (Tetracosanoic acid) Acetovanillone

Fluoranthene n-C20 (Eicosane) 2-Methylnonadecane Benzencarboxylic acids Fatty acids Syringaldehyde

Pyrene n-C21 (Heneicosane) 2,6,10-Trimethylpentadecane Terephthalic Acid (1,4) Pinonic Acid 3,5-Dimethoxy-4-

Retene n-C22 (Docosane) 3-Methylnonadecane Isophthalic Acid (1,3) Palmitoleic Acid (C16:1) hydroxyacetophenone

Benzo[ghi]fluoranthene n-C23 (Tricosane) Pentadecylcyclohexane Phthalic Acid (1,2) Linoleic Acid (18:2) 4-Hydroxy-3-

Cyclopenta[cd]pyrene n-C24 (Tetracosane) Methylfluoranthene Methylphthalic Acid Oleic Acid (C18:1) methoxycinnamaldehyde

Benzo[a]anthracene n-C25 (Pentacosane) Hexadecylcyclohexane 1,2,4- Linolenic Acid 3,5-Dimethoxy-4-

Chrysene n-C26 (Hexacosane) Heptadecylcyclohexane Benzenetricaboxylic Acid Octacosanoic Acid hydroxycinnamaldehyde

Benzo[b]fluoranthene n-C27 (Heptacosane) Octadecylcyclohexane 1,2,4,5- Triacontanoic acid Resin Acids

Benzo[k]fluoranthene n-C28 (Octacosane) Nonadecylcyclohexane Benzenetetracarboxylic acid Sugar&Glyceride Pimaric Acid

Benzo[a]pyrene n-C29 (Nonacosane) 1-Methylchrysene Mannosan Iso-Pimaric Acid

Benzo[e]pyrene n-C30 (Triacontane) Levoglucosan Abietic Acid

Perylene n-C31 (Hentriacontane) Monopalmitin (16:0) Dehydroabietic Acid

Indeno[1,2,3-cd]pyrene n-C32 (Dotriacontane) Monoolein (18:1) Campesterol

Dibenzo[a,h]anthracene n-C33 (Tritriacontane) Monostearin (18:0)

Picene n-C34 (Tetratriacontane)

Benzo[ghi]perylene n-C35 (Pentatriacontane)

Coronene n-C36 (Hexatriacontane)

Dibenzo[a,e]pyrene n-C37 (Heptatriacontane)

n-C38 (Octatriacontane)

n-C39 (Nonatriacontane)

n-C40 (Tetracontane)

１１

Table 4. GC/MSD analysis condition in this study.

GC/MSD

(7890A/5975C, 7890B/5977B) Operating Conditions

Carrier Gas Helium

Flow rate 1 mL/min

Column

DB-5MS

(30 m long * 0.25 mm ID * 0.25 μm

film thickness, diphenyl-dimethyl

polysiloxane phase capillary column

Injector

Mode Splitless mode

Volume 1 ul

Temperature 280 °C

Ramp

Initial temp. 1 min at 60 °C

Rate of temp. 4 °C/min to 310 °C

Isothermal pause 15 min at 310 °C

Detector

Mass range 40~600 Da

Electron energy 70 eV

Quadrupole temp. 150 °C

Ion source temp. 230 °C

Transfer line temp. 280 °C

Solvent delay 7mins

１２

2.1.3.3. Quality assurance and quality controls (QA/QC)

Quality assurance and quality controls (QA/QC) for organic compounds was

performed and the results were described in Table 19~Table 30. In order to quantify

the organic species, calibration curves of non-polar and polar compounds were used

with 6 points of native standards and internal standard method was applied. The

coefficient of determination (r2) was 0.948 – 1.000. The concentration results below

the method detection limit (MDL) were assigned as ‘Not detected (N.D.)’ in this

study. To ascertain the recovery, 50 ㎕ of native non-polar and polar standard were

spiked on the quartz filter and extracted with ultrasonication method. The recovery

was calculated by dividing the measured value by the true value. Total 18 species of

surrogate standards were applied to monitor the potential loss of all procedure (Table

18). In this study, the acceptable recovery range and relative standard deviations

range (RSD) were 65~135 % and 20 %, respectively.

１３

2.2. Data analysis

To identify the potential emission sources, several methods were applied;

Diagnostic parameters including PAHs diagnostic ratio, Carbon number maximum

(Cmax), Carbon preference index (CPI) and Wax n-alkanes percentage (WNA), and

statistical method which is Principal component analysis (PCA).

PAHs diagnostic ratio was calculated to qualitatively identify emission sources

(Tobiszewski & Namieśnik, 2012). Low molecular weight PAHs are usually formed

while the low temperature processes are performed. On the other hand, high

temperature processes release higher molecular weight PAH compounds (Mostert,

Ayoko, & Kokot, 2010). The ratio by using Fluoranthene (Flt), Pyrene (Pyr),

Phenanthrene (PHE) and Anthracene (ANT) was used to distinguish the potential

emission sources. According to the (Behymer & Hites, 1985), the reaction half-lives

of ANT and PHE are 2.9 and 150 hours on silica gel, 0.5 and 45 hours on alumina,

and 48 and 49 hours on fly ash, respectively. ANT adsorbed on particles reacts faster

with NO2, while PHE reacts faster with OH radicals (Marusenko, 2011). The

ANT/(ANT/+PHE) ratio indicates the influence by photoreactions leading to the

ratios close to 0. Furthermore, the Flt and Pyr are 74 and 21 hours for silica gel-

adsorbed PAHs, 23 and 31 hours for alumina, and 44 and 46hours for fly ash. PYR

adsorbed on graphite and diesel particles reacts faster with NO2, but with OH

radicals the reaction rates are the same. Photoreactions are expected to shift the ratio

slightly towards higher values (Table 5).

１４

Table 5. PAHs diagnostic ratio Flt/(Flt+Pyr)

<0.4 Petrogenic source (Roberto, Lee, & Campos-Díaz,

2009) 0.4-0.5 Fossil fuel combustion

>0.5 Grass, wood, coal combustion

ANT/(ANT+PHE)

<0.1 Petrogenic (Pies et al., 2008)

>0.1 Pyrogenic

According to several studies, C21-C25, which is lower molecular weight than

C26 are indicator of diesel engine exhaust (Chellam, Kulkarni, & Fraser, 2005). C27-

C34 (especially higher odd n-alkanes such as C27, C29, C31 and C33) are known as

makers of vegetative detritus (Simoneit, 1989).

Carbon number maximum (Cmax) is used to identify source origins and maturity

of aerosols. Highly matured aerosols from fossil fuels can only emit low value of

Cmax while high Cmax comes from aerosols affected by plant wax sources (Duan, He,

& Liu, 2010).

Carbon preference index (CPI) is a well-known index for indicating the

contribution of anthropogenic or biogenic sources. A CPI value close to or less than

a value of 1 indicates a possibility of fossil fuel burning, while a value higher than 3

may show biological sources (Simoneit, 1989).

CPI𝑛−𝑎𝑙𝑘𝑎𝑛𝑒𝑠 = ∑ 𝑇𝑜𝑡𝑎𝑙 𝑜𝑑𝑑 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑎𝑟𝑏𝑜𝑛𝑠

∑ 𝑇𝑜𝑡𝑎𝑙 𝑒𝑣𝑒𝑛 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑎𝑟𝑏𝑜𝑛𝑠

Wax n-Alkanes percentage (WNA) is a tool for quantifying the contribution of

biogenic sources in aerosols (Simoneit, 1989). The value is assigned as zero when

１５

the Cn value is negative.

WNA% = ∑[𝐶𝑛 − 0.5(𝐶𝑛+1 + 𝐶𝑛−1)]

∑ 𝑛 − 𝐴𝑙𝑘𝑎𝑛𝑒𝑠× 100

１６

3. Result and Discussions

3.1 Chemical constituents

In this study, a total of 63 PM2.5 samples over a year period were analyzed. In

addition, OC, EC , ionic species and more than 100 organic compounds including

PAHs, n-alkanes, hopanes, steranes, alkylcyclohexanes, dicarboxylic acids,

benzencarboxylic acids, alkanoic acids, fatty acids, sugar, glyceride, sterols,

methoxyphenols and resin acids were identified and quantified (Table 19~Table 30).

Table 6 summarizes PM2.5 species concentrations collected in Seoul during the whole

sampling period (June 1, 2018 ~ May 27, 2019).

The average PM2.5 mass concentration during the study period was 26.4 ±

21.5 ㎍/m3. Considering the international and domestic PM2.5 criteria, this study

showed that not only 68.3% samples of mass concentration exceeded the annual

PM2.5 standards in Korea and US EPA (2012), which is 15 ㎍/m3, but also 81.0 %

samples of mass concentrations exceeded the PM2.5 criteria of WHO (2005), which

is 10 ㎍/m3. The average PM2.5 mass concentration depending on the seasonal

variations, winter (36.9 ± 15.6 ㎍/m3) and spring (35.5 ± 34.3 ㎍/m3) showed

higher value than fall (17.5 ± 11.9 ㎍/m3) and summer (17.5 ± 10.1 ㎍/m3)

relatively. The average concentration of OC and EC were 3.95 ± 2.02 ㎍/m3 and

0.46 ± 0.24 ㎍/m3, respectively. As shown in Figure 2 (B) and (C), those figures

show that most of OC and EC concentration follow the seasonal pattern of PM2.5

concentrations whereas some cases are in contrast with PM2.5 during the high

１７

concentration period which is mostly winter and spring seasons. In addition, average

OC/EC ratio is 9.01 ± 2.76 ㎍/m3. A higher value of OC/EC ratio might be presented

as indication of biomass burning (Sandradew, 2008). Furthermore, the ratio value of

OC/EC exceeding 2.0 shows higher possibility the sources origin is connected with

secondary organic aerosol (SOA) (Turpin, 1990, Chow, 1996). According to the

Figure 2 (A) and (B), the OC/EC ratios display high ratio pattern along with

relatively low temperatures (p<0.31). Thus, Seoul, especially the sampling area has

a high possibility influenced by biomass burning or SOA. The average concentration

of ionic species (NO3-, SO4

2- and NH4+) were 5.27 ± 7.08 ㎍/m3, 3.76 ± 3.01 ㎍/m3

and 2.61 ± 3.01 ㎍/m3, respectively.

１８

Table 6. Summary of PM2.5 species concentrations collected in Seoul during the whole

sampling period (June 1, 2018 ~ May 27, 2019)

Seasons Annual Spring

(Mar, April, May

2019)

Summer (Jun, Jul, Aug

2018)

Fall (Sep, Oct, Nov

2018)

Winter (Dec 2018, Jan, Feb

2019)

Species (n=63) (n=18) (n=15) (n=15) (n=15)

PM2.5 (㎍/m3) 26.4±21.5 35.5±34.3 17.5±10.1 17.5±11.9 36.9±15.6

OC (㎍/m3) 3.95±2.02 3.62±2.09 3.09±1.51 3.25±1.23 5.99±1.93

EC (㎍/m3) 0.46±0.24 0.31±0.15 0.35±0.15 0.48±0.19 0.72±0.23

OC/EC ratio 9.01±2.76 11.4±2.30 8.80±2.00 7.02±1.36 8.82±5.67

NO3- (㎍/m3) 5.27±7.08 8.90±11.8 1.80±1.79 3.04±2.62 8.03±5.47

SO42- (㎍/m3) 3.76±3.01 4.84±4.33 4.35±2.65 2.26±1.04 3.49±2.77

NH4+ (㎍/m3) 2.61±3.01 4.07±5.07 1.79±1.25 1.33±1.12 3.40±2.44

PAHs (ng/m3) Phenanthrene 0.33±0.50 0.15±0.09 0.05±0.01 0.16±0.15 0.99±0.68

Anthracene 0.10±0.04 0.08±0.04 0.07±0.02 0.09±0.02 0.15±0.05

9-Methylanthracene 0.03±0.09 0.02±0.08 0.05±0.12 N.D. 0.04±0.11

Fluoranthene 0.62±0.70 0.37±0.21 0.12±0.03 0.43±0.31 1.66±0.71

Pyrene 0.36±0.46 0.19±0.14 0.03±0.02 0.24±0.22 1.03±0.47

Retene 0.04±0.09 N.D. N.D. 0.01±0.02 0.17±0.13

Benzo[ghi]fluoranthene 0.17±0.20 0.09±0.07 0.02±0.01 0.12±0.11 0.48±0.17

Cyclopenta[cd]pyrene 0.20±0.13 0.17±0.04 0.11±0.04 0.19±0.09 0.36±0.16

Benzo[a]anthracene 0.18±0.17 0.11±0.05 0.06±0.01 0.14±0.09 0.42±0.17

Chrysene 0.37±0.38 0.25±0.15 0.07±0.04 0.28±0.19 0.95±0.28

Benzo[b]fluoranthene 0.63±0.48 0.46±0.2 0.24±0.05 0.54±0.27 1.35±0.36

Benzo[k]fluoranthene 0.12±0.13 0.09±0.06 0.01±0.02 0.11±0.08 0.31±0.09

Benzo[a]pyrene 0.23±0.19 0.16±0.09 0.07±0.02 0.19±0.11 0.51±0.14

Benzo[e]pyrene 0.21±0.19 0.12±0.09 0.09±0.07 0.19±0.12 0.46±0.19

Perylene 0.10±0.04 0.09±0.03 0.08±0.04 0.10±0.03 0.14±0.02

Indeno[1,2,3-cd]pyrene 0.24±0.19 0.16±0.08 0.08±0.02 0.21±0.11 0.54±0.12

Dibenzo[a,h]anthracene 0.02±0.03 0.00±0.01 0.00±0.01 0.01±0.02 0.05±0.03

Picene 0.04±0.03 0.03±0.02 0.01±0.02 0.03±0.03 0.08±0.01

Benzo[ghi]perylene 0.08±0.14 0.01±0.03 N.D. 0.04±0.07 0.30±0.12

Coronene 0.15±0.06 0.14±0.04 0.11±0.01 0.15±0.03 0.23±0.05

Dibenzo[a,e]pyrene 0.14±0.15 0.06±0.09 0.14±0.15 0.12±0.13 0.24±0.17

∑PAHs 4.36±4.05 2.79±1.37 1.42±0.35 3.37±2.06 10.5±3.58

１９

Table6. (Continued)


(Mar, April, May

2019)


2018)

Fall (Sep, Oct, Nov

2018)

Winter (Dec 2018,

Jan, Feb 2019)

Species (n=63) (n=18) (n=15) (n=15) (n=15)

n-Alkanes (ng/m3)

Pentadecane 0.20±0.35 0.12±0.18 N.D. 0.21±0.35 0.49±0.51

Hexadecane 0.42±0.69 0.27±0.40 0.45±1.05 0.38±0.55 0.56±0.52

Heptadecane 1.07±0.91 0.57±0.61 0.92±0.78 1.11±0.65 1.72±1.19

Octadecane 0.60±0.31 0.61±0.08 0.34±0.33 0.59±0.19 0.91±0.26

Nonadecane 0.76±0.35 0.66±0.04 0.53±0.25 0.69±0.22 1.22±0.36

Eicosane 0.89±0.62 0.71±0.17 0.44±0.16 0.73±0.25 1.77±0.66

Heneicosane 1.59±0.92 1.31±0.35 0.93±0.14 1.22±0.31 3.01±0.79

Docosane 1.91±1.56 1.56±0.73 0.69±0.46 1.38±0.53 4.25±1.28

Tricosane 1.86±1.12 1.76±0.68 0.99±0.26 1.45±0.37 3.41±1.07

Tetracosane 1.86±1.18 1.67±0.90 0.96±0.47 1.59±0.49 3.42±1.06

Pentacosane 2.36±1.09 2.31±0.97 1.54±0.46 2.14±0.65 3.59±1.06

Hexacosane 2.16±0.84 2.08±0.86 1.57±0.64 2.09±0.56 2.99±0.63

Heptacosane 4.32±1.98 4.19±1.52 3.65±1.17 3.98±1.91 5.60±2.74

Octacosane 1.69±0.93 0.98±0.87 1.45±0.79 1.99±0.79 2.37±0.72

Nonacosane 3.28±1.24 3.26±1.49 2.60±0.89 3.39±1.28 4.01±0.95

Triacontane 1.99±1.63 1.35±1.45 1.71±1.65 2.51±1.62 2.44±1.71

Hentriacontane 4.53±1.98 3.67±1.97 3.78±2.00 5.09±1.48 5.71±1.83

Dotriacontane 3.32±1.85 1.81±1.84 3.57±2.05 3.84±1.21 4.03±1.46

Tritriacontane 3.85±2.36 2.79±1.37 3.84±3.55 4.04±1.29 4.73±2.05

Tetratriacontane 3.02±0.60 2.74±0.33 3.16±0.56 2.94±0.85 3.19±0.48

Pentatriacontane 2.78±1.95 3.23±3.27 1.41±1.17 3.07±0.62 3.68±0.92

∑n-Alkanes 44.4±16.5 37.6±14.4 34.5±12.1 44.4±11.5 63.1±12.8

Hopane&Sterane (ng/m3)

ABB-20R-C27-Cholestane 0.03±0.05 0.00±0.02 0.03±0.05 0.03±0.05 0.06±0.07

17A(H)-22,29,30-

Trisnorhopane 0.06±0.06 N.D. 0.02±0.02 0.02±0.03 0.04±0.04

∑Hopane&Sterane 0.05±0.07 0.00±0.02 0.04±0.07 0.05±0.07 0.10±0.09

Alkylcyclohexanes (ng/m3)

Dibenzofuran 0.22±0.13 0.14±0.04 0.24±0.17 0.19±0.08 0.31±0.12

2-Methylnonadecane 0.08±0.10 0.46±0.39 1.00±2.23 0.49±0.36 0.73±0.32

2,6,10-Trimethylpentadecane 0.69±1.22 3.23±1.35 0.89±2.49 0.33±0.39 2.15±3.06

3-Methylnonadecane 1.61±2.33 0.15±0.04 0.09±0.04 0.14±0.05 0.36±0.13

Pentadecylcyclohexane 0.18±0.13 0.32±0.31 0.38±0.32 0.29±0.32 0.64±0.03

Methylfluoranthene 0.40±0.30 0.11±0.02 0.07±0.03 0.09±0.05 0.22±0.08

Hexadecylcyclohexane 0.12±0.07 0.24±0.30 0.38±0.31 0.45±0.28 0.55±0.23

Heptadecylcyclohexane 0.40±0.30 0.13±0.23 0.43±0.29 0.44±0.23 0.42±0.32

1-Methylchrysene 0.36±0.29 0.08±0.02 0.04±0.04 0.07±0.03 0.12±0.02

∑Alkylcyclohexanes 4.06±3.13 4.85±1.98 3.52±4.43 2.49±1.33 5.49±2.93

２０

Table6. (Continued)


(Mar, April, May

2019)


2018)

Fall (Sep, Oct, Nov

2018)

Winter (Dec 2018, Jan, Feb

2019)

Species (n=63) (n=18) (n=15) (n=15) (n=15)

Aliphatic diacids (ng/m3)

Succinic acid 16.5±8.62 21.0±8.12 17.8±10.3 11.7±5.26 15.0±7.76

Fumaric acid 1.42±0.64 1.60±0.57 1.59±0.92 1.15±0.30 1.30±0.49

∑Aliphatic diacids 17.9±9.06 22.7±8.42 19.4±11.1 12.9±5.43 16.4±8.01

Benzencarboxylic acids (ng/m3)

Terephthalic Acid (1,4) 8.04±6.62 6.96±1.69 5.29±2.18 6.07±4.06 14.4±10.6

Isophthalic Acid (1,3) 1.88±0.87 2.07±0.88 1.38±0.61 1.45±0.44 2.73±0.82 1,2,4,5-

Benzenetetracarboxylic

acid 6.20±5.96 3.11±1.62 3.87±0.12 3.96±0.42 3.60±1.02

∑Benzencarboxylic acids 13.6±7.34 12.1±2.01 10.6±2.62 11.5±4.69 20.7±11.6

Alkanoic acids (ng/m3)

Dodecanoic acid 2.25±0.38 2.53±0.39 1.82±0.12 2.29±0.26 2.44±0.21

Tetradecenoic acid 1.90±0.41 2.06±0.42 1.62±0.46 1.96±0.27 2.04±0.28

Octadecanoic acid 15.9±6.25 7.73±2.81 6.81±2.79 9.55±4.15 11.7±3.65

Eicosanoic acid 8.86±3.78 4.06±0.73 3.27±0.14 3.67±0.37 4.36±0.35

Docosanoic acid 3.81±0.60 5.34±1.59 3.99±0.22 4.69±0.52 6.07±0.73

Tetracosanoic acid 4.97±1.17 6.12±1.92 4.32±0.33 5.36±0.68 6.82±0.89

∑Alkanoic acids 27.4±6.49 27.8±6.68 21.8±3.44 27.5±5.48 33.5±4.53

Fatty acids (ng/m3)

Pinonic Acid 5.78±5.26 10.8±5.23 3.69±3.44 6.89±5.22 2.07±2.48

Palmitoleic Acid 0.40±0.54 0.34±0.49 0.18±0.41 0.22±0.45 0.92±0.49

Linoleic Acid 1.06±0.71 1.51±1.11 0.74±0.43 0.93±0.19 1.12±0.66

Oleic Acid 0.27±0.76 0.33±0.59 N.D. 0.10±0.40 0.71±1.33

Linolenic Acid 0.03±0.16 N.D. N.D. N.D. 0.11±0.32

Octacosanoic Acid 6.32±2.65 6.80±3.37 5.07±2.79 6.17±2.57 7.49±0.69

Triacontanoic acid 6.63±3.20 6.63±4.26 4.86±3.57 7.27±2.17 8.12±0.91

∑Fatty acids 20.5±8.17 26.5±10.8 14.5±6.68 21.6±5.81 20.5±3.11

Sugar&Glyceride (ng/m3)

Levoglucosan 67.0±68.5 56.9±54.7 8.17±5.03 57.8±44.9 156.±53.0

Monopalmitin 2.47±0.75 2.37±0.78 1.96±0.28 2.5±0.53 3.12±0.87

Monoolein 1.12±0.61 1.01±0.75 1.25±0.45 0.85±0.72 1.37±0.38

Monostearin 0.69±0.42 0.45±0.31 0.6±0.21 0.99±0.57 0.72±0.39

∑Sugar&Glyceride 71.2±69.4 60.8±55.3 12±5.53 62.2±45.6 162±54.2

Sterols (ng/m3)

Coprostanol 0.64±0.61 0.58±0.64 0.2±0.46 0.65±0.63 1.24±0.03

Cholesterol 0.68±0.32 0.54±0.08 0.51±0.21 0.75±0.27 0.98±0.42

Cholestanol 0.30±0.22 0.46±0.01 0.05±0.15 0.28±0.23 0.47±0.02

Stigmasterol 1.80±0.56 1.91±0.14 1.39±0.76 1.85±0.55 2.14±0.22

Stigmastanol 4.21±2.24 1.88±0.07 1.82±0.04 1.89±0.07 2.02±0.08

∑Sterols 5.33±1.38 5.36±0.75 3.97±0.93 5.40±1.27 6.85±0.68

Other organic compounds (ng/m3) 3,5-Dimethoxy-4-

hydroxycinnamaldehyde 2.82±0.92 2.67±1.08 2.73±0.99 2.69±1.09 3.21±0.12

Pimaric Acid 1.60±0.26 1.51±0.07 1.45±0.09 1.52±0.11 1.96±0.32

Abietic Acid 4.47±2.19 2.14±0.13 1.75±0.64 2.16±0.19 2.59±0.35

Dehydroabietic Acid 2.14±0.49 1.78±0.71 0.98±0.39 2.08±1.12 5.18±1.64

Campesterol 2.43±1.89 2.43±0.60 1.96±0.06 2.15±0.18 2.30±0.24

∑Other organic

compounds 11.2±3.07 10.54±1.58 8.87±1.75 10.6±2.26 15.25±2.37

２１

Figure 2. Time series plots of Temperature and RH (A), OC/EC ratio and PM2.5 (B), OC and EC (C), and Ionic species (D) concentrations from June

1, 2018 to May 27, 2019

A

B

C

D

２２

The organic compounds were classified and calculated by category of its

chemical characteristics. The annual average concentration of Sugars & Glyceride

(71.2 ± 69.4 ng/m3) was the highest among other organic compounds including n-

Alkanes (44.4 ± 16.5 ng/m3), PAHs (4.36 ± 4.05 ng/m3), alkanoic acids (27.4 ± 6.49

ng/m3), aliphatic diacids (17.9 ± 9.06 ng/m3), benzencarboxylic acids (13.6 ± 7.34

ng/m3), fatty acids (20.5 ± 8.17 ng/m3), alkylcyclohexane (4.06 ± 3.15 ng/m3), sterols

(5.33 ± 1.38 ng/m3), hopane (0.05 ± 0.07 ng/m3), and other organic compounds

(methoxyphenols and resin acids; 11.2 ± 3.07 ng/m3). In order to figure out the

temporal variability in concentration over time, the concentration time series plot

was described in Figure 3, which is summed by compounds class. Furthermore, the

concentration of seasonal differences by its compounds class was shown in Figure 4

as well. These time series plots reveal the high degree of day-by-day variability

across whole compound classes, particularly during the winter. The PAHs, Sugars

and Glycerides, Sterols and other organic compounds (which includes

Methoxyphenol, resin acids as so forth) have the most prominent seasonality with

higher values in the winter and lower values in the summer. The PAHs, sterols and

methoxyphenols are markers for biomass burning, but these compounds have

important contributions from other sources as well. The remaining classes of organic

compounds have significant contributions throughout year with a less noticeable

drop in concentration during the summer. The alkanes and fatty acids show a slight

short-duration summertime increase in April to May. This effect suggests a

summertime biogenic sources originated from leaf abrasion (Rogge, 1993) and plant

wax (Simoneit & Mazurek, 1982).

２３

Figure 3. Time series plots of organic molecular marker compounds from June 1, 2018

to May 27, 2019 summed by its class

PAHs

n-Alkanes

Hopane & Sterane

Alkylcyclohexanes

Aliphatic diacids

Benzencarboxylic acids

Alkanoic acids

Fatty acids

Sugars & Glycerides

Sterols

Other organic species

２４

Figure 4. Seasonal differences of organic species by its categories in this study

２５

Polycyclic Aromatic Hydrocarbons (PAHs)

Polycyclic Aromatic Hydrocarbons (PAHs), which exist as a semi-volatile

phase, originate from incomplete combustions or pyrolysis of organic compounds

(Maliszewska-Kordybach, 1999). Total 23 individual compounds in the acceptable

range were analyzed and quantified. As shown in the Table 6, the sum of total PAHs

shows one of the smallest parts of annual organic compounds. Therefore, the PAHs

seemed to have a weak influence on the average organic compounds concentration

trends as well as identification of emission sources.

The volatility of PAHs depends on the number of rings. PAHs with 3 or 4 rings

are classified as semi-volatile and found in both gas and particulate phase. PAHs

with 5 or 6 rings are present only in the particulate phase (Tan et al., 2011). The total

average concentration of semi-volatile PAHs with 3 and 4 rings were 1.12 ± 0.78

ng/m3 and 1.57 ± 1.79 ng/m3, non-volatile PAHs with 5 and 6 rings was 1.31 ± 1.03

ng/m3 and 0.84 ± 0.73 ng/m3, respectively.

Table 7. PAHs compounds depending on its number of benzene rings

Benzene

ring PAHs compounds

3 ring Phenanthrene, Anthracene

4 ring Retene, Fluoranthene, Pyrene, Benzo[a]anthracene, Chrysene

5 ring Benzo[b]fluoranthene, Benzo[k]fluoranthene, Benzo[a]pyrene,

Benzo[e]pyrene, Dibenzo[a,h]anthracene, Picene, Perylene

6 ring Benzo[ghi]fluoranthene, Cyclopenta[cd]pyrene, Indeno[1,2,3-cd]pyrene,

Benzo[ghi]perylene, Coronene, Dibenzo[a,e]pyrene

２６

Figure 5. Monthly average concentration (ng/m3) (A) and percentage (%) (B) of PAHs

depending on the number of benzene rings in this study

A

B

２７

PAHs diagnostic ratio

A scatter plot of Flt/(Flt+Pyr) against ANT/(ANT+PHE) is shown in Figure 6

for each season. The diagnostic ratio was dominant in the upper right corner,

suggesting that the PAHs in this sampling area were relatively influenced by diverse

pyrogenic combustions, which are grass, wood, and coal combustion. Especially,

petrogenic sources were dominant in winter and spring. The lower ANT/(ANT+PHE)

value in winter months might influenced of external sources and ageing of air masses.

.

Figure 6. A scatter plot of Flt/(Flt+Pyr) against ANT/(ANT+PHE) in this study

２８

n-Alkanes

In this study, C15 to C35 were analyzed, but only C20 to C35 was described in

Figure 7. According to varied studies, low molecular weight compounds (C21-C25)

are used as a marker of diesel engine exhaust (Simoneit, 1989), and high molecular

weight species (C27-C34) are well-known as a marker of vegetative detritus

(Simoneit, 1989). As mentioned previously, the average n-Alkanes concentration

through the sampling period was 49.37±18.53 ng/m3. As shown in Figure 7, winter

(58.25±11.63 ng/m3) showed the highest concentration trend throughout all species

in n-Alkanes. Summer (32.30±11.28 ng/m3) represented the lowest trend level

among the other seasons. Spring (35.42±13.69 ng/m3) and Fall (41.46±10.98

ng/m3), on the other hand, concentration trends intersected at lower and higher

molecular weight compounds. Thus, the seasonal pattern of high concentration in

winter and low concentration in summer was displayed during this study period.

２９

Figure 7. Seasonal concentration trends of n-Alkanes in this study

To identify the emission sources related to n-Alkanes, CPI and WNA were

calculated in Table 8. Summary of carbon preference index (CPI) and the wax n-

alkanes percentage (WNA%) in this study and comparison with other studies..

According to the Cmax value throughout the year, especially C31 was dominant which

is able to show the potential source is vegetative detritus. It shows that there were

effects by the Gwanak Mt. which is the sampling site is located in.

Most of CPI values during the sampling period were close to 1 and above, which

means the effects of fossil fuel/biomass burning and biological sources were well

mixed in the area.

Along with potential emission sources assumed by Cmax and CPI value, WNA

values show that the sampling site were influenced on plant wax sources,

considerably.

３０

Table 8. Summary of carbon preference index (CPI) and the wax n-alkanes percentage

(WNA%) in this study and comparison with other studies.

Sampling site Type CPI WNA% Reference

Seoul, Korea Urban

1.76±0.40a 1.60±0.87b

1.52±0.29c

1.43±0.16d

32.2±8.36a 34.8±26.9b

22.3±9.11c

21.1±4.65d

Current study

Anmyeon Island, Korea Rural 2.2 32 Kim et al. (2018)

Beijing, China Urban 1.4-1.6 15-19 Ren et al. (2016)

Mt. Tai, China Mountain 1.3-1.8 19-31 Wang et al. (2006)

Shanghai, China Urban 1.2-1.6 19-30 Lyu et al. (2017)

Jiujiang, China Urban 1.3 19 Han et al. (2018)

Cape Hedo Okinawa,

Japan Marine 1.7 30 Wang et al. (2009)

a. Spring

b. Summer

c. Fall

d. Winter

３１

3.2 Principal Component Analysis

Based on the chemical speciation data, the comprehensive emission sources

were identified. Therefore, statistically significant and accurate classification of

emission sources is distinguished by using the organic species information and

statistical method which is Principal component analysis, referred as PCA.

Before performing the PCA, data handling process was conducted. The organic

species which were out of range of acceptable recovery and RSD (%) were

eliminated in early stage. In order to assume the high potential emission sources, the

stable molecular markers which is less influenced by its environmental condition

during transport from sources to receptors considered in this statistical models. Thus,

several compounds were excluded before the organic markers were considered as its

groups. The PAHs with less than 252 molecular weights, n-Alkanes with less than

24 carbons, n-Alkanoic acids with less than 18 carbons (Heo, 2013).

The PCA analysis is the effective tool for describing inter-correlated variables

into independent principal component (PCs) based on the orthogonal rotation called

VARIMAX and identified diverse factors using statistical software SPSS (ver. 25.0).

The factors above the eigenvalue of 1 were extracted as reasonable principal values

greater than 0.600 and these were highlighted in bold text, whereas the values below

0.300 were eliminated in the table.

As a result, total 4 factors were distinguished and were assigned as biomass

burning, secondary organic aerosols (SOAs), vehicle emission, biogenic secondary

organic aerosols, respectively (Table 9).

Factor 1 was identified as biomass burning with 44.381 % out of total variance.

As shown in Table 9, factor 1 has high loading with levoglucosan which is noticeable

as markers of biomass combustion and tracers to track the long-range transport

３２

emissions (Fraser and Lakshmanan 2000). Along with levoglucosan, sugars and

PAHs groups have high loading and those compounds group are well-known as

markers of biomass burning (Simoneit 1999; Watson 2008; Hays 2002; Hays 2005).

According to the Table 9, the factor 2 were assigned as secondary organic

aerosols with 19.745 % of variance. Factor 2 was characterized by high factor

loading values which are SO42-, NH4

+, Aliphatic acids group, OC/EC and NO32-.

Those group and compounds are also supported the possibility of factor 2 has chance

to be a SOA.

Factor 3 shows high loading of Alkycyclohexanes, hopane and sterane, and n-

Alkanes groups with 6.873 % of variance. Alkylcyclohexanes group is one of the

primary compounds in vehicle emission (Simoneit 1985). Beside, the hopane and

sterane were usually shown in the vehicle emissions and n-Alkanes were produced

in tire ware (Simoneit and Mazurek 1982; Rogge et al. 1993; Hays et al. 2002&2005).

Factor 4 is mainly described with pinonic acids with 5.935% variances. Pinonic

acid is one of the major compounds produced through photo-oxidation of a-pinen

with OH radical or ozone. Several studies presented pinonic acid in aerosols from

forest and vertified its significant roles in the formation of biogenic aerosols in

forests (Kavouras 1998; Yu 1999).

３３

Table 9. PCA analysis of PM2.5 with factor loading results during sampling period

PCA Factor 1 Factor 2 Factor 3 Factor 4

Identified sources Biomass burning

SOAs Vehicle source

Biogenic secondary

organic aerosols

OC 0.739 0.474 - -

EC 0.830 - - -

OC/EC - 0.804 - -

NO32- 0.431 0.770 - -

SO42- - 0.917 - -

NH4 - 0.880 - -

ΣPAHs 0.863 - 0.316 -

Σn-Alkanes 0.584 - 0.672 -

ΣHopane & Sterane - - 0.765 -

ΣAlkycyclohexanes - - 0.852 -

ΣAliphatic acids - 0.812 - -

ΣBenzencarboxylic acids 0.414 0.508 - -

ΣAlkanoic acids 0.873 - - -

ΣFatty acids 0.660 0.346 0.371 0.319

ΣSugars 0.729 - - -

ΣSterols 0.845 - - -

ΣMethoxyphenol 0.400 - 0.423 0.326

ΣResin acids and small quantity stuff 0.899 - - -

Levoglucosan 0.903 - - -

Picene 0.823 - - -

Pinonic acid - 0.321 - 0.717

Eigenvalues 9.320 4.146 1.443 1.246

Variance (%) 44.381 19.745 6.873 5.935

Cumulative (%) 44.381 64.125 70.998 76.933

* Bold values shows factor loading higher than 0.6

Factor loading less than 0.3 were eliminated in the table

３４

4. Conclusions

Chemical characteristics and potential emission sources of PM2.5 with organic

compounds were investigated in Gwanak district, Seoul, Korea. Samples were

collected every 6 days from June 1, 2018 to May 27, 2019.

(1) The average PM2.5 mass concentration during the study period was 26.4 ±

21.5 ug/m3. The most influenced month was February, which has

56.66±17.41 ug/m3 average PM2.5 concentrations, and September has the

lowest concentration (9.97 ± 4.86 ug/m3). During the sampling period,

winter (36.89 ± 15.59 ug/m3) and spring (35.46 ± 34.27 ug/m3) had high

concentration value than fall (16.91 ± 11.70 ug/m3) and summer (16.99 ±

10.04 ug/m3) relatively. It was able to assure that 68.3% of sampling period

exceeded the annual PM2.5 standards in Korea. Among the organic

compounds including PAHs and n-Alkanes, the total average concentration

of sugars and glyceride (71.2±69.4 ng/m3) showed the highest

concentration throughout the year.

(2) Despite the low concentration of PAHs, the possible emission sources were

identified by using PAHs diagnostic ratio which is Flt/(Flt+Pyr) against

ANT/(ANT+PHE). It is assumed that Seoul is mostly influenced by

pyrogenic sources.

(3) N-Alkanes showed the seasonal patterns well in this study which are high

concentration in winter and low concentration in summer. According to the

n-alkanes parameters, Cmax, CPI and WNA, the sampling area was

influenced by various sources, especially vegetative detritus.

(4) The PCA was performed to identify the possible emission sources. The 4

３５

factors were identified, which are biomass burning (44.381 %), secondary

organic aerosols (SOAs) (19.745 %), vehicle emission (6.873 %), biogenic

secondary organic aerosols (5.935 %). More than half of total variances are

assigned in Factor 1 and 2, which means these PCA results suggest that

significant portion of PM2.5 in Seoul, especially those sampling area

(Gwanak district) were possibly derived from the biomass burning and

secondary organic aerosols.

(5) In order to specify and enhance the reliability of distinguishing the emission

sources, other statistical models are expected to perform to provide further

explanations of source apportionment trends.

３６

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４０

6. Supplemental Materials

Table 10. Information of target non-polar compounds (PAHs)

Category Compounds Formula MW Main fragments

(m/z)

PAHs Naphthalene C10H8 128.17 128

1-Methylnaphthalene C11H10 142.2 142, 141

2-Methylnaphthalene C11H10 142.2 142, 141, 115

2,6-Dimethylnaphthalene C12H12 156.22 156, 155, 141, 77

Acenaphthylene C12H8 152.19 152

Acenaphthene C12H10 154.21 153

Fluorene C13H10 166.22 166

Phenanthrene C14H10 178.23 178

Anthracene C14H10 178.23 178

9-Methylanthracene C15H12 192.26 192, 165

Fluoranthene C16H10 202.25 202, 101

Pyrene C16H10 202.25 202, 101

Retene C18H18 234.34 219, 234, 204

Benzo[ghi]fluoranthene C18H10 226.27 226, 113

Cyclopenta[cd]pyrene C18H10 226.27 226, 113

Benzo[a]anthracene C18H12 228.29 228, 114

Chrysene C18H12 228.29 228, 114

Benzo[b]fluoranthene C20H12 252.31 252, 126

Benzo[k]fluoranthene C20H12 252.31 252, 126

Benzo[a]pyrene C20H12 252.31 252, 126

Benzo[e]pyrene C20H12 252.31 252, 126

Perylene C20H12 252.31 252, 126

Indeno[1,2,3-cd]pyrene C22H12 276.33 276, 138

Dibenzo[a,h]anthracene C22H14 278.35 278, 139

Picene C22H14 278.35 278, 139

Benzo[ghi]perylene C22H12 276.33 276, 138

Coronene C24H12 300.35 300, 150

Dibenzo[a,e]pyrene C24H14 302.37 302, 151

４１

Table 11. Information of target non-polar compounds (n-Alkanes)

Category Compounds Formula MW Main fragments (m/z)

n-Alkanes n-C10 (Decane) C10H22 142.28 57, 71, 85, 142

n-C11 (Undecane) C11H24 156.31 57, 71, 85, 156

n-C12 (Dodecane) C12H26 170.34 57, 71, 85, 170

n-C13 (Tridecane) C13H28 184.36 57, 71, 85, 184

n-C14 (Tetradecane) C14H30 198.39 57, 71, 85, 198

n-C15 (Pentadecane) C15H32 212.42 57, 71, 85, 212

n-C16 (Hexadecane) C16H34 226.44 57, 71, 85, 226

n-C17 (Heptadecane) C17H36 240.47 57, 71, 85, 240

n-C18 (Octadecane) C18H38 254.49 57, 71, 85, 254

n-C19 (Nonadecane) C19H40 268.52 57, 71, 85, 268

n-C20 (Eicosane) C20H42 282.55 57, 71, 85, 282

n-C21 (Heneicosane) C21H44 296.57 57, 71, 85, 296

n-C22 (Docosane) C22H46 310.6 57, 71, 85, 310

n-C23 (Tricosane) C23H48 324.63 57, 71, 85, 324

n-C24 (Tetracosane) C24H50 338.65 57, 71, 85, 338

n-C25 (Pentacosane) C25H52 352.68 57, 71, 85, 352

n-C26 (Hexacosane) C26H54 366.71 57, 71, 85, 366

n-C27 (Heptacosane) C27H56 380.73 57, 71, 85, 380

n-C28 (Octacosane) C28H58 394.76 57, 71, 85, 394

n-C29 (Nonacosane) C29H60 408.79 57, 71, 85, 408

n-C30 (Triacontane) C30H62 422.81 57, 71, 85, 422

n-C31 (Hentriacontane) C31H64 436.84 57, 71, 85, 436

n-C32 (Dotriacontane) C32H66 450.87 57, 71, 85, 450

n-C33 (Tritriacontane) C33H68 464.89 57, 71, 85, 464

n-C34 (Tetratriacontane) C34H70 478.92 57, 71, 85, 478

n-C35 (Pentatriacontane) C35H72 492.95 57, 71, 85, 492

n-C36 (Hexatriacontane) C36H74 506.97 57, 71, 85, 506

n-C37 (Heptatriacontane) C37H76 521 57, 71, 85, 521

n-C38 (Octatriacontane) C38H78 535.03 57, 71, 85, 535

n-C39 (Nonatriacontane) C39H80 549.05 57, 71, 85, 549

n-C40 (Tetracontane) C40H82 563.08 57, 71, 85, 563

４２

Table 12. Information of target non-polar compounds (Hopane, Steranes,

Alkylcyclohexanes and Isoprenoids)

Category Compounds Formula MW Main fragments

(m/z)

Hopanes

/Steranes

AAA-20S-C27-

Cholestane C27H48 372.67 217, 218, 357, 372

ABB-20R-C27-

Cholestane C27H48 372.67 217, 218, 357, 372

ABB-20R-C28-

Methylcholestane C28H50 386.7 217, 218, 371, 386

17A(H)-22,29,30-

Trisnorhopane C27H46 370.65 191

ABB-20R-C29-

Ethylcholestane C29H52 400.72 218, 217, 385, 400

17A(H)-21B(H)-30-

Norhopane C29H50 398.71 191

17A(H)-21B(H)-Hopane C30H52 412.73 191

Alkylcyclo-

hexanes

/Isoprenoids

Dibenzofuran C12H8O 168.19 168, 139, 84

9-Methylfluorene C14H12 180.25 180, 165, 89, 76

2-Methylnonadecane C20H42 282.55 57, 71, 85, 239

2,6,10-

Trimethylpentadecane

(Norpristane)

C18H38 254.49 57, 71, 85, 254

3-Methylnonadecane C20H42 282.55 57, 71, 85, 253

Pentadecylcyclohexane C21H42 294.56 82, 83, 294

Methylfluoranthene C17H12 216.28 216, 107

Hexadecylcyclohexane C22H44 308.59 82, 83, 308

Heptadecylcyclohexane C23H46 322.61 82, 83, 322

Octadecylcyclohexane C24H48 336.64 82, 83, 336

Nonadecylcyclohexane C25H50 350.66 82, 83, 350

1-Methylchrysene C19H14 242.31 242, 121

2-Methylpentacosane C26H54 366.71 57, 71, 85

Squalane C30H62 422.81 183, 337, 57, 71

４３

Table 13. Information of target polar compounds (Aliphatic diacids and

Benzencarboxylic acids)

No. Compounds Formula MW Main fragments (m/z)

Aliphatic

Diacids Malonic acid C2H4O4 104.06 233, 133

(C9H20O4Si2) (248.42)

Maleic acid C4H4O4 116.07 245, 83, 133

(C10H20O4Si2) (260.44)

Succinic acid C4H6O4 118.09 247, 147

(C10H22O4Si2) (262.45)

Fumaric acid C4H4O4 116.07 245

(C10H20O4Si2) (260.44)

Glutaric acid C5H8O4 132.12 261, 158, 129

(C11H24O4Si2) (276.48)

Adipic acid C6H10O4 146.14 111, 141

(C12H26O4Si2) (290.5)

Pimelic acid C7H12O4 160.17 155, 125, 147

(C13H28O4Si2) (304.15)

Suberic acid C8H14O4 174.19 169, 117, 187

(C14H30O4Si2) (318.56)

Azelaic acid C9H16O4 188.22 129, 117, 201

(C15H32O4Si2) (332.58)

Sebacic acid C10H18O4 202.25 129, 117, 331

(C16H34O4Si2) (346.61)

Benzen-

carboxylic

acids

Terephthalic acid C8H6O4 166.13 295

(C14H22O4Si2) (310.11)

Isophthalic acid C8H6O4 166.13 149, 166, 295

(C14H22O4Si2) (310.11)

Phthalic acid C8H6O4 166.13 147, 295

(C14H22O4Si2) (310.11)

Methylphthalic

acid

C9H8O4 180.16 309, 324

(C15H24O4Si2) (324.52)

1,2,4-Benzene-

tricarboxylic acid

C9H6O6 210.14 426

(C18H30O6Si3) (426.68)

1,2,4,5-Benzene-

tetracarboxylic

acid

C10H6O8 254.15 279, 310

(C19H30O8Si3) (458.68)

４４

Table 14. Information of target polar compounds (Alkanoic acids)


Alkanoic

acids C6:0 (Hexanoic acid, Caproic acid)

C6H12O2 116.16 73, 75, 174

(C9H20O2Si) (188.12)

C8:0 (Octanoic acid, Caprylic acid)

C8H16O2 144.21 73, 75, 201

(C11H24O2Si) (216.15)

C10:0 (Decanoic acid, Capric acid)

C10H20O2 172.27 73, 117, 229

(C13H28O2Si) (244.19)

C12:0 (Dodecanoic acid, Lauric acid)

C12H24O2 200.32 73, 117, 257

(C15H32O2Si) (272.22)

C14:0 (Tetradecenoic acid, Myristic acid)

C14H26O2 226.36 73, 117, 285

(C17H36O2Si) (300.56)

C16:0 (Hexadecanoic acid, Palmitic acid)

C16H32O2 256.42 73, 117, 313

(C19H40O2Si) (328.61)

C18:0 (Octadecanoic acid, Stearic acid)

C18H36O2 284.48 73, 117, 341

(C21H44O2Si) (356.67)

C20:0 (Eicosanoic acid, Arachidic acid)

C20H40O2 312.53 73, 117, 369

(C23H48O2Si) (384.34)

C22:0 (Docosanoic acid, Behenic acid)

C22H44O2 340.58 73, 117, 397

(C25H52O2Si) (412.77)

C24:0 (Tetracosanoic acid, Lignoceric acid)

C24H48O2 368.64 73, 117, 425

(C27H56O2Si) (440.83)

４５

Table 15. Information of target polar compounds (Fatty acids, sugars and glycerides)


Fatty acids Pinonic acid C10H16O3 184.23 73, 83, 171, 185

(C13H24O3Si) (256.41)

Palmitoleic acid C16H30O2 254.41 73, 75, 117, 311

(C19H38O2Si) (326.59)

Linoleic acid C18H32O2 280.45 73, 81, 67, 337

(C21H40O2Si) (352.28)

Oleic acid C18H34O2 282.46 335, 79

(C19H38O2Si) (254.3)

Linolenic acid C18H30O2 278.43 73, 75, 55, 339

(C23H42O2Si) (378.67)

Octacosanoic acid

(Montanic acid)

C28H56O2 424.74 73, 117, 481

(C31H64O2Si) (496.92)

Triacontanoic acid

(Melissic acid)

C30H60O2 452.8 73, 11, 509

(C33H68O2Si) (524.98)

Sugars

&Glycerides Mannosan C6H10O5 162.14 73, 204, 217, 333

(C15H34O5Si3) (378.69)

Levoglucosan C6H10O5 162.14 73, 204, 217, 333

(C15H34O5Si3) (378.69)

Monopalmitin (16:0) C19H38O4 330.5 73, 371

(C25H54O4Si2) (474.86)

Monoolein (18:1) C21H40O4 356.54 73, 129, 397

(C27H56O4Si2) (500.91)

Monostearin (18:0) C21H42O4 358.56 73, 129, 218

(C27H58O4Si2) (502.93)

４６

Table 16. Information of target polar compounds (Sterols and Methoxyphenols)


Sterols Coprostanol C27H48O 388.67 215, 355, 370, 460

(C30H56OSi) (460.86)

Cholesterol C27H46O 386.65 129, 329, 368, 458

(C30H54OSi) (458.84)

Cholestanol C27H48O 388.67 215, 355, 445, 460

(C30H56OSi) (460.86)

Stigmasterol C29H48O 412.69 129, 255, 484

(C32H56OSi) (484.88)

β-Sitosterol C29H50O 414.71 129, 397, 487

(C32H58OSi) (486.9)

Stigmastanol C29H52O 416.72 215, 383, 473, 488

(C32H60OSi) (488.9)

Methoxy-

phenols Vanillin C8H8O3 152.15 194, 193, 209

(C11H16O3Si) (224.33)

Iso-Eugenol C10H12O2 164.2 236

(C13H20O2Si) (236.38)

Acetovanillone C9H10O3 166.17 193, 208, 223, 238

(C12H18O3Si) (238.36)

Syringealdehyde C9H10O4 182.17 224, 239, 254

(C12H18O4Si) (254.35)

3,5-Dimethoxy-4-

hydroxyacetophenone

(Acetosyringone)

C10H12O4 196.2 268, 73

(C13H20O4Si) (268.38)

4-Hydroxy-3-

methoxycinnamaldehyde

(Coniferaldehyde)

C10H10O3 178.19 220, 250, 235, 192

(C13H18O3Si) (250.37)

3,5-Dimethoxy-4-

hydroxycinnamaldehyde (Cinnamaldehyde)

C11H12O4 208.21 222, 280, 250, 73

(C14H20O4Si) (280.39)

４７

Table 17. Information of target polar compounds (Resin acids)


Resin Acids Pimaric acid C20H30O2 302.45 256, 241

(C23H38O2Si) (374.64)

Iso-Pimaric acid C20H30O2 302.45 121, 120, 374

(C23H38O2Si) (374.64)

Abietic acid C20H30O2 302.45 256, 241

(C23H38O2Si) (374.64)

Dehydroabietic acid C20H28O2 300.44 239, 372

(C23H36O2Si) (372.62)

Campesterol C28H48O 400.68 129, 343, 382, 472

(C31H56OSi) (472.86)

４８

Table 18. Spike volume (ul) and final spike concentration (ng/ul) of surrogate/internal

standard used in this study

Organic group Standard name Spike

volume (ul)

Final spike

conc. (ng/ul)

PAHs

Acenaphthene-d10 50 1.072

Pyrene-d10 50 0.4

Benz[a]anthracene-d12 50 0.4

Coronene-d12 50 0.804

n-Alkanes

Pentadeane-d32 50 3.496

Eicosane-d42 50 1.604

Tetracosane-d50 50 1.52

Triacontane-d58 50 2.252

Dotriacontane-d66 50 5.24

Hexatriacontane-d74 50 6.404

Hopanes & steranes Cholestane-d4 50 0.396

Alkylcyclohexanes

Acenaphthene-d10 50 1.072

Eicosane-d42 50 1.604

Aliphatic Diacids

Succinic acid-d4 50 3.08

Tetradeanoic Acid-d27 50 3

Benzencarboxylic

acids

Phthalic Acid-d4 50 3.184

Alkanoic acids Tetradeanoic Acid-d27 50 3

Fatty acids

Heptadecanoic Acid-d33 50 1.44

Eicosanoic Acid-d39 50 1.524

Sugar & Glyceride

Levoclucosan-C13 50 1.44

Heptadecanoic Acid-d33 50 1.44

Sterols Cholesterol-D6 50 6.4

Methoxyphenols Heptadecanoic Acid-d33 50 1.44

Resin Acids Cholesterol-D6 50 6.4

４９

Table 19. Summary of quality assurance and quality controls (QAQC) data (PAHs)

Compounds R2

Recovery % (n=6) Concentration (ng/m3)

Field blank (n=4) MDL

PAHs Average Stdev RSD Average Stdev

Naphthalene 1.000 6.69 6.27 93.80 0.006 0.012 0.019

1-Methylnaphthalene 1.000 23.86 12.42 52.04 ND ND 0.015

2-Methylnaphthalene 1.000 24.41 13.35 54.69 0.033 0.038 0.018

2,6-Dimethylnaphthalene 1.000 63.65 9.15 14.38 ND ND 0.016

Acenaphthylene 1.000 79.90 8.14 10.19 ND ND 0.051

Acenaphthene 1.000 97.27 2.52 2.60 0.028 0.056 0.020

Fluorene 0.999 162.29 17.00 10.47 ND ND 0.009

Phenanthrene 1.000 89.92 3.35 3.72 ND ND 0.009

Anthracene 0.997 97.01 5.03 5.18 ND ND 0.012

9-Methylanthracene 0.999 94.82 3.50 3.69 0.079 0.159 0.015

Fluoranthene 1.000 99.78 1.14 1.14 ND ND 0.008

Pyrene 0.999 89.10 3.23 3.62 ND ND 0.004

Retene 0.998 78.81 1.78 2.26 ND ND 0.015

Benzo[ghi]fluoranthene 0.999 100.45 1.47 1.46 ND ND 0.005

Cyclopenta[cd]pyrene 0.995 118.88 7.20 6.06 ND ND 0.013

Benzo[a]anthracene 1.000 103.66 0.69 0.67 ND ND 0.010

Chrysene 1.000 101.52 4.55 4.48 ND ND 0.013

Benzo[b]fluoranthene 0.999 105.68 1.20 1.14 ND ND 0.016

Benzo[k]fluoranthene 1.000 113.96 4.84 4.25 0.021 0.024 0.052

Benzo[a]pyrene 1.000 92.42 5.82 6.30 ND ND 0.006

Benzo[e]pyrene 1.000 106.36 6.08 5.71 0.053 0.062 0.006

Perylene 0.999 112.53 6.95 6.18 0.048 0.055 0.012

Indeno[1,2,3-cd]pyrene 1.000 98.50 6.74 6.84 ND ND 0.000

Dibenzo[a,h]anthracene 0.999 81.31 3.57 4.39 0.008 0.015 0.021

Picene 0.999 97.89 12.19 12.46 ND ND ND

Benzo[ghi]perylene 0.997 72.39 3.76 5.19 ND ND 0.035

Coronene 0.999 80.96 9.06 11.20 ND ND ND

Dibenzo[a,e]pyrene 0.993 73.07 12.24 16.75 0.155 0.180 0.000

５０

Table 20. Summary of quality assurance and quality controls (QAQC) data (n-Alkanes)

Compounds R2



n-Alkanes Average Stdev RSD Average Stdev

n-C10 (Decane) 1.000 4.27 2.53 59.3 ND ND 0.071

n-C11 (Undecane) 1.000 NA NA NA 0.068 0.093 0.072

n-C12 (Dodecane) 1.000 NA NA NA ND ND 0.070

n-C13 (Tridecane) 1.000 NA NA NA 0.370 0.435 0.070

n-C14 (Tetradecane) 1.000 39.04 14.04 36.0 0.234 0.275 0.063

n-C15 (Pentadecane) 1.000 107.15 3.14 2.9 0.199 0.231 0.066

n-C16 (Hexadecane) 1.000 133.02 9.47 7.1 0.291 0.354 0.084

n-C17 (Heptadecane) 1.000 83.68 11.56 13.8 0.533 0.616 0.062

n-C18 (Octadecane) 1.000 86.46 3.12 3.6 0.252 0.291 0.097

n-C19 (Nonadecane) 1.000 92.66 2.51 2.7 0.306 0.355 0.031

n-C20 (Eicosane) 1.000 94.53 0.70 0.7 0.125 0.250 0.039

n-C21 (Heneicosane) 1.000 96.92 2.04 2.1 0.354 0.408 0.091

n-C22 (Docosane) 1.000 103.83 2.43 2.3 0.414 0.478 0.032

n-C23 (Tricosane) 1.000 80.41 2.18 2.7 0.429 0.496 0.034

n-C24 (Tetracosane) 0.999 85.51 3.09 3.6 0.462 0.534 0.051

n-C25 (Pentacosane) 0.999 89.81 6.41 7.1 0.569 0.658 0.018

n-C26 (Hexacosane) 0.999 88.64 4.16 4.7 0.630 0.728 0.043

n-C27 (Heptacosane) 0.995 112.75 7.55 6.7 0.882 1.019 0.040

n-C28 (Octacosane) 0.997 86.67 7.00 8.1 0.888 1.042 0.049

n-C29 (Nonacosane) 0.996 90.67 9.76 10.8 0.974 1.172 0.068

n-C30 (Triacontane) 0.996 97.16 10.24 10.5 0.870 1.023 0.058

n-C31 (Hentriacontane) 0.992 142.61 17.49 12.3 1.507 1.039 0.046

n-C32 (Dotriacontane) 0.989 125.72 16.96 13.5 0.696 1.392 0.023

n-C33 (Tritriacontane) 0.982 116.43 13.76 11.8 1.348 1.556 0.062

n-C34 (Tetratriacontane) 0.981 124.58 14.43 11.6 0.657 1.315 0.036

n-C35 (Pentatriacontane) 0.985 107.18 7.26 6.8 1.204 1.406 0.080

n-C36 (Hexatriacontane) 0.986 30.88 1.62 5.2 0.965 1.114 0.085

n-C37 (Heptatriacontane) 0.965 104.14 3.28 3.2 0.656 1.313 0.101

n-C38 (Octatriacontane) 0.969 98.53 7.22 7.3 1.117 1.290 0.071

n-C39 (Nonatriacontane) 0.971 72.02 7.04 9.8 1.667 1.933 0.195

n-C40 (Tetracontane) 0.984 117.51 14.29 12.2 0.974 1.125 0.043

５１

Table 21. Summary of quality assurance and quality controls (QAQC) data (Hopanes & Steranes)

Compounds R2



Hopanes & Steranes Average Stdev RSD Average Stdev

AAA-20S-C27-Cholestane 0.995 202.47 21.56 10.65 0.104 0.120 ND

ABB-20R-C27-Cholestane 0.999 111.27 15.06 13.53 0.051 0.058 ND

ABB-20R-C28-Methylcholestane 0.999 151.11 20.57 13.61 0.036 0.042 ND

17A(H)-22,29,30-Trisnorhopane 0.998 98.12 17.02 17.34 ND ND 0.020

ABB-20R-C29-Ethylcholestane 1.000 NA NA NA 0.119 0.138 0.000

17A(H)-21B(H)-30-Norhopane 0.999 NA NA NA 0.596 0.690 0.022

17A(H)-21B(H)-Hopane 1.000 NA NA NA 0.497 0.574 0.015

５２

Table 22. Summary of quality assurance and quality controls (QAQC) data (Alkylcyclohexanes)

Compounds R2



Alkylcyclohexanes Average Stdev RSD Average Stdev

Dibenzofuran 1.000 120.22 8.02 6.67 ND ND 0.009

9-Methylfluorene 0.999 168.43 19.87 11.80 ND ND 0.010

2-Methylnonadecane 0.997 82.15 10.99 13.37 0.258 0.299 0.017

2,6,10-Trimethylpentadecane (Norpristane)

1.000 88.64 5.10 5.75 0.138 0.231 0.016

3-Methylnonadecane 1.000 91.77 0.99 1.08 0.026 0.052 0.004

Pentadecylcyclohexane 0.996 119.07 2.49 2.09 0.303 0.350 0.008

Methylfluoranthene 0.999 123.31 2.42 1.96 ND ND 0.009

Hexadecylcyclohexane 0.996 120.66 2.92 2.42 0.304 0.351 0.008

Heptadecylcyclohexane 0.998 125.19 5.09 4.06 0.277 0.320 0.013

Octadecylcyclohexane 0.995 146.23 7.76 5.31 0.415 0.480 0.049

Nonadecylcyclohexane 0.992 153.28 9.62 6.28 0.512 0.591 0.010

1-Methylchrysene 1.000 115.74 1.93 1.67 ND ND 0.013

５３

Table 23. Summary of quality assurance and quality controls (QAQC) data (Aliphatic Diacids)

Compounds R2



Aliphatic Diacids Average Stdev RSD Average Stdev

Malonic (C3) 0.995 NA NA NA NA NA ND

Maleic (C3=) 0.999 NA NA NA 0.242 0.363 0.023

Succinic (C4) 1.000 109.30 14.86 13.60 ND ND 0.183

Fumaric (C4=) 1.000 86.33 13.30 15.40 0.036 0.108 0.014

Glutaric (C5) 1.000 155.25 88.05 56.72 0.123 0.204 0.035

Adipic (C6) 1.000 25.93 17.35 66.92 0.078 0.118 0.059

Pimelic (C7) 0.999 49.47 22.57 45.62 0.144 0.286 0.094

Suberic (C8) 0.999 63.06 20.86 37.54 ND ND 0.052

Azelaic (C9) 1.000 65.64 21.93 33.41 0.180 0.270 0.048

Sebacic (C10) 0.999 55.18 29.20 52.93 0.478 0.461 0.034

５４

Table 24. Summary of quality assurance and quality controls (QAQC) data (Benzencarboxylic acids)

Compounds R2



Benzencarboxylic acids Average Stdev RSD Average Stdev

Terephthalic Acid (1,4) 1.000 101.05 14.33 14.18 ND ND 0.074

Isophthalic Acid (1,3) 1.000 127.94 22.28 17.42 0.277 0.329 0.042

Phthalic Acid (1,2) 0.998 161.10 105.84 65.70 ND ND 0.208

Methylphthalic Acid 1.000 141.22 38.40 27.19 0.136 0.409 0.040

1,2,4-Benzenetricaboxylic Acid 0.986 87.31 20.93 23.97 ND ND 0.027

1,2,4,5-Benzenetetracarboxylic acid 0.972 98.38 7.39 7.51 ND ND 0.000

５５

Table 25. Summary of quality assurance and quality controls (QAQC) data (Alkanoic acids)

Compounds R2



Alkanoic acids Average Stdev RSD Average Stdev

C6:0 (Hexanoic acid, Caproic acid) 0.261 NA NA NA ND ND NA

C8:0 (Octanoic acid, Caprylic acid) 0.001 NA NA NA ND ND NA

C10:0 (Decanoic acid, Capric acid) 0.969 55.05 10.19 18.51 0.035 0.033 4.730

C12:0 (Dodecanoic acid, Lauric acid) 0.997 105.84 3.60 3.40 0.820 0.778 0.246

C14:0 (Tetradecenoic acid, Myristic acid) 1.000 92.37 6.72 7.28 0.294 0.350 0.115

C16:0 (Hexadecanoic acid, Palmitic acid) 0.999 130.07 27.02 20.77 0.693 1.367 1.826

C18:0 (Octadecanoic acid, Stearic acid) 0.998 129.45 21.28 16.44 0.816 1.521 0.506

C20:0 (Eicosanoic acid, Arachidic acid) 0.994 100.87 3.33 3.30 1.286 1.525 0.064

C22:0 (Docosanoic acid, Behenic acid) 0.990 114.06 10.45 9.16 1.180 1.771 0.038

C24:0 (Tetracosanoic acid, Lignoceric acid) 0.985 110.67 11.60 10.48 1.313 1.970 0.053

５６

Table 26. Summary of quality assurance and quality controls (QAQC) data (Fatty acids)

Compounds R2



Fatty acids Average Stdev RSD Average Stdev

Pinonic Acid 1.000 68.93 10.40 15.09 ND ND 1.090

Palmitoleic Acid (C16:1) 1.000 83.78 7.42 8.85 ND ND 0.051

Linoleic Acid (18:2) 0.997 98.97 1.65 1.67 0.356 0.425 0.239

Oleic Acid (C18:1) 0.989 80.39 14.46 17.99 ND ND 0.150

Linolenic Acid 0.981 68.02 8.26 12.14 ND ND 0.291

Octacosanoic Acid 0.955 112.98 8.62 7.63 ND ND 0.000

Triacontanoic acid 0.948 119.52 7.56 6.32 2.346 3.566 ND

５７

Table 27. Summary of quality assurance and quality controls (QAQC) data (Sugar & glyceride)

Compounds R2



Sugar & Glyceride Average Stdev RSD Average Stdev

Mannosan 0.998 43.59 7.05 16.18 0.088 0.174 0.041

Levoglucosan 1.000 103.57 0.99 0.96 ND ND 0.044

Monopalmitin (16:0) 0.990 121.24 4.05 3.34 0.597 0.708 0.023

Monoolein (18:1) 0.973 130.13 4.93 3.79 0.470 0.704 0.000

Monostearin (18:0) 0.996 85.78 4.81 5.61 0.120 0.147 0.083

５８

Table 28. Summary of quality assurance and quality controls (QAQC) data (Sterols)

Compounds R2



Sterols Average Stdev RSD Average Stdev

Coprostanol 0.997 124.17 1.58 1.27 ND ND 0.068

Cholesterol 1.000 109.05 0.49 0.45 0.105 0.208 0.080

Cholestanol 1.000 93.78 2.60 2.77 0.102 0.202 0.048

Stigmasterol 1.000 116.30 0.93 0.80 ND ND 0.000

B-Sitosterol 0.997 139.57 1.93 1.38 0.978 1.470 0.000

Stigmastanol 1.000 121.28 1.73 1.43 ND ND 0.000

５９

Table 29. Summary of quality assurance and quality controls (QAQC) data (Methoxyphenols)

Compounds R2



Methoxyphenols Average Stdev RSD Average Stdev

Vanillin 0.954 NA NA NA ND ND 2.725

Iso-Eugenol 0.074 NA NA NA ND ND 94.545

Acetovanillone 0.985 31.95 11.64 36.41 ND ND 1.799

Syringaldehyde 0.991 50.62 13.52 26.71 ND ND 0.250

3,5-Dimethoxy-4-hydroxyacetophenone 0.995 62.87 13.60 21.64 ND ND 0.401

4-Hydroxy-3-methoxycinnamaldehyde 0.997 62.91 3.13 4.97 ND ND 0.000

3,5-Dimethoxy-4-hydroxycinnamaldehyde 0.999 77.32 2.61 3.38 ND ND ND

６０

Table 30. Summary of quality assurance and quality controls (QAQC) data (Resin Acids)

Compounds R2



Resin Acids Average Stdev RSD Average Stdev

Pimaric Acid 0.998 126.85 3.21 2.53 ND ND ND

Iso-Pimaric Acid 0.997 158.22 5.50 3.48 1.53 2.30 ND

Abietic Acid 0.999 105.70 2.23 2.11 ND ND 0.037

Dehydroabietic Acid 0.994 120.36 4.96 4.12 0.21 0.25 0.018

Campesterol 0.999 131.77 2.00 1.52 0.42 0.84 ND

６１

국문 초록

서울시 관악구 대기 중 PM2.5의 유기성분 특성

정소영

서울대학교 보건대학원

환경보건학과 대기환경전공

초미세먼지(PM2.5)는 주요 대기오염물질 중 하나로 대기 중 공기역학

적 직경이 2.5um 이하인 입자상 물질을 말한다. PM2.5는 다양한 자연적∙

인위적 오염원으로부터 배출되는데, 이는 사람의 건강뿐만 아니라 우리

가 생활하는 환경에도 영향을 미친다. PM2.5는 발암성이 있는 1급 발암

물질로 분류되며, 노출 시 심혈관계 및 호흡기계 질환을 유발할 수 있고,

시정거리를 감소시킬 뿐만 아니라, 기후변화에도 직간접적인 영향을 미

친다. 대기 중 PM2.5의 구성성분 중 대부분을 차지하는 유기탄소는 수많

은 개별 유기성분들로 구성되어 있으며, 이러한 유기성분들은 다양한 오

염원으로부터 배출되어 오염원의 독특한 배출 특성을 나타내기 때문에,

대기 중 PM2.5 오염원을 보다 정확히 추정하기 위해서는 PM2.5내의 유

기성분의 농도 특성 파악이 필요하다. 본 연구에는 2018년 6월부터

６２

2019년 5월까지 서울대학교 보건대학원 옥상에서 채취된 PM2.5 내의

유기탄소, 원소탄소, 개별 유기성분과 같은 화학적 특성 분석하고, 이를

통해 주성분 분석을 이용하여 서울시 관악구의 오염원을 추정하고자 하

였다.

PM2.5의 화학적 특성 분석을 위해 저용량 에어 샘플러와 고용량 에어

샘플러를 이용하여 6일간격으로 63개씩에 해당하는 샘플을 채취하였다.

대상 기간 중 PM2.5의 평균 질량 농도는 26.4 ± 21.5 ug/m3로, 겨울철

인 2월(56.7±17.41 ug/m3)에 최고농도로 나타났으며, 여름철인 9월

(9.97 ± 4.86 ug/m3)에 최저농도인 것으로 나타났다. 분석된 개별 유

기성분의 전체 평균 농도는 212.17±102.71 ug/m3 이며, 이 중 sugar

류가 가장 높은 농도 기여도를 갖는 것으로 나타났다(71.2±69.4

ng/m3). PAHs diagnostic을 통해 추정된 PAHs 오염원은 연소에 의한

오염원 영향을 나타내는 것으로 보였으며, n-Alkanes을 이용한 Cmax,

CPI, WNA 인자들을 통해 다양한 오염원, 특히 생물 기원 오염원의 영

향이 두드러지게 나타났다. 이는 관악산 주변의 식물 등의 오염원이 n-

Alkanes의 발생에 기여한 것으로 추정된다. 앞서 분석한 대기중 화학적

특성 분석을 통해 주성분 분석(Principal Component Analysis, PCA)을

수행하여 1년동안 관악구에 영향을 미친 잠정적인 오염원을 추정하였다.

주성분 분석을 통해 총 4개의 오염원 인자들을 구분하였으며, 이는 생물

성연소(Biomass burning, 44.381%), 이차 유기 에어로졸 오염원

(Secondary organic aerosols, SOA, 19.745%), 자동차 오염원(Vehicle

emission, 6.873%), 생물기원 이차 유기 에어로졸 오염원(Biogenic

６３

secondary organic aerosols, 5.935%)으로 분류되었다. 따라서 본 연구

가 진행된 서울시 관악구의 PM2.5는 주로 생물성 연소와 이차 유기 에

어로졸 오염원의 영향을 받은 것으로 추정된다.

주요어: 초미세먼지(PM2.5), 유기성분(Organic compounds), 유기 분

자 마커(Organic molecular marker), 배출원 추정(Source

identification), 주성분분석(Principal component analysis, PCA)

학번: 2018-21005

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