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Title Page

Abstract

Contents

1. Introduction 11

1.1. Research Background 12

1.1.1. USA 12

1.1.2. Europe 13

1.1.3. Asia 14

1.1.4. South Korea 14

1.2. Research Strategy 15

2. Data and Method 16

2.1. Data 16

2.2. Model Simulation 17

2.2.1. Chemical Schemes 19

2.2.2. Aerosol Schemes 19

2.2.3. Emission Inventory 20

2.2.4. Meteorological Data 20

2.3. Methodology 21

2.3.1. EC-Tracer Method 21

2.3.2. Calculation of the Primary OC-to-EC Ratio 23

3. Result 24

3.1. Model Verification 24

3.1.1. WRF-Chem 24

3.1.2. EC-Tracer 25

3.2. Identification of Dominant process 28

4. Conclusion 32

5. References 34

List of Tables

Table 2.1. Model set up with main physical and chemical schemes adopted in the simulation 18

Table 3.1. Relative Contributions of SOA and POA to Total OA in Observation and Model Simulations in 6 cities 30

List of Figures

Figure 1.1. Location of the monitored sites of the studies considered in this review reporting the use of the elemental carbon (EC) tracer method for the evaluation of secondary organic carbon (SOC) PM2.5. 12

Figure 2.1. The locations of intensive stations in south Korea 17

Figure 2.2. Model domain 18

Figure 3.1. Daily Average Time Series of Aerosol Parameters during the Study Period 24

Figure 3.2. Verification Tests for Assessing Model Performance in Simulating Aerosol Parameters 25

Figure 3.3. Taylor Diagram for Evaluating Correlation and RMSE of Percentile Values in Comparison with Model Output 26

Figure 3.4. Comparison of SOA and POA between Direct Model Output and Observation Data using EC-Tracer Method with Selected Percentiles 27

Figure 3.5. Verification Tests for Organic Aerosol 28

Figure 3.6. Comparison of Modeled and Observed Total Organic Aerosols in Various Cities 29

Figure 3.7. Relative Contributions of VOCs to SOA Formation and Primary/Secondary Organic Carbon in PM2.5 Mass Concentration in Six Cities 31

초록보기

 Organic aerosol (OA) is a significant component of PM2.5 and is traditionally categorized into Primary Organic Aerosol (POA) and Secondary Organic Aerosol (SOA). However, due to the chemical complexity of OA, direct measurement of SOA and POA fractions using routine filter-based techniques is currently not available. This poses a challenge in understanding the detailed composition and sources of OA. To address this, the EC-tracer method has been widely adopted to estimate these fractions based on organic carbon (OC) and elemental carbon (EC) measurements in the field. This study proposes the EC-tracer method as an observation-based approach to distinguish periods when SOA significantly contributes to ambient OC levels from periods dominated by primary emissions of organic and elemental carbon. To assess the accuracy of this approach, concentrations generated by the WRF-Chem model, utilizing the RACM-MADE/VBS approach, are compared. This study focuses on the evaluation and comparison of the EC-Tracer method results obtained from ground-based observations and model simulation outputs at six locations in South Korea (Baengnyeongdo, Seoul, Gwangju, Daejeon, Ulsan, and Jeju) during the KORUS-AQ 2016 period (May 1st to June 10th). The observed and modeled data show moderate correlations (0.35 for SOA and 0.5 for POA) across six stations. Approximately 65% of OA is attributed to the secondary component, but the model simulations overestimate it (exceeding 80%) and underestimate the contribution of POA. Anthropogenic VOCs contribute around 72.5% to SOA formation. Taking all these factors into account, total OA (TOA) levels in Gwangju, Daejeon, Ulsan, and Seoul are statistically significant at the 99% confidence level, while Jeju and Baengnyeongdo are not statistically significant at the same confidence level.

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