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Source Characterization of Particulate Matter Using Molecular Markers in Incheon, Korea

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Authors
최종규
Advisor
조경덕
Major
보건대학원 보건학과
Issue Date
2013-08
Publisher
서울대학교 대학원
Keywords
PM2.5positive matrix factorization (PMF)molecular marker (MM)GC×GC-TOFMS
Description
학위논문 (박사)-- 서울대학교 보건대학원 : 보건학과 환경보건학 전공, 2013. 8. 조경덕.
Abstract
ABSTRACT

Source Characterization of Particulate Matter
Using Molecular Markers in Incheon, Korea

Jongkyu Choi
The Graduate School of Public Health
Seoul National University

Airborne particulate matter (PM) has adverse effects on human morbidity and mortality, visibility, climate change, and materials. Even though the main composition of fine particles has been reported in several studies, only 10~20% of the organic compounds has been quantified as individual organic species. In order to develop effective strategy for reducing fine particle pollution, it is very important to analyze the components and evaluate the source of particulate matter. The purpose of this study is to evaluate the characteristics of particulate matter and determine sources using molecular markers (MM).
To find out the characteristics of PM in Incheon, PM samples were collected for 1 year and analyzed for its composition. One hundred and twenty samples for fine particle (PM2.5) and TSP were collected in Incheon area from 2009 to 2010. The collected samples were analyzed for the main ingredients such as OC, EC, ions, heavy metals and other major components. In addition, water-soluble organic carbon (WSOC) and the main ingredients of organic aerosol (OA) were analyzed. The results by this analysis were used as input data of the source apportionment model, positive matrix factorization (PMF), which has been widely used as a basic model, unlike MM.
The first study was performed to elucidate the characteristics, sources, and distribution of PM2.5 and carbonaceous species in Incheon, Korea. To do this, we analyzed the major components of PM2.5 such as OC, EC, ionic, and metallic species in individual samples. Furthermore, organic species and WSOC were evaluated to characterize the influence of individual PM2.5 components. The average PM2.5 concentration (41.9 ± 9.0 μg/m3) exceeded the annual level set by the United States National Ambient Air Quality Standards (15 μg/m3). The major fraction of PM2.5 consisted of ionic species (accounting for 38.9 ± 8.8%), such as NO3-, SO42-, and NH4+, as well as organic carbon (OC) (accounting for 18.9 ± 5.1%). We also analyzed the seasonal variation in PM2.5 and secondary aerosols such as NO3- and SO42- in PM2.5. As an important aerosol indicator, WSOC (mean 4.7 ± 0.8 μg/m3, 58.9 ± 10.7% of total OC) showed a strong relationships with NO3-, SO42-, and SOC (R2 = 0.56, 0.67, and 0.65, respectively), which could represent favorable conditions for SOC formation during the sampling period. Among the individual organic aerosols measured, n-alkanes, n-alkanoic acids, levoglucosan, and phthalates were major components, whereas polycyclic aromatic hydrocarbons (PAHs), oxy-PAHs, hopanes, and cholestanes were minors. The concentration of organic compounds during smoggy periods was higher than that of non-event periods. The concentration of n-alkane and n-alkanoic acid species during the smoggy periods was 10-14 times higher than that of the normal period. Using principal component analysis coupled with multiple linear regression analysis, we identified motor vehicle/sea salt, secondary organic aerosols, combustion, biogenic/meat cooking, and soil sources as primary sources of PM2.5.
In the second study, on the basis of the analyzed chemical species in the PM2.5 samples, the sources of PM2.5 were identified using a positive matrix factorization (PMF) model. And finally nine sources of PM2.5 were determined. The major sources of PM2.5 were secondary nitrate (25.4%), secondary sulfate (19.0%), motor vehicle 1 (14.8%) with a lesser contribution from industry (8.5%), motor vehicle 2 (8.2%), biomass burning (6.1%), soil (6.1%), combustion and copper production emissions (6.1%), and sea salt (5.9%) respectively. From a paired t-test, it was found that the samples during the yellow sand periods were characterized by higher contribution from soil sources (p < 0.05). Furthermore, the possible source areas of PM2.5 emissions were determined by using the conditional probability function (CPF) and the potential source contribution function (PSCF). CPF analysis identified the motor vehicles and sea salt as possible local sources of PM2.5. PSCF analysis indicated that the possible sources for secondary particles (sulfate and nitrate) were related to the major industrial complexes in China.
In the final study, MM-PMF was preformed to evaluate the sources of PM and organic carbons. PMF model was carried out and three different analysis items were categorized. For example, first, 22 items such as OC, EC, ionic compounds and trace metals in TSP, second, 41 items in organic compounds, and third, 63 items in both TSP (22) and organic compounds (41). The nine sources of TSP were identified by the PMF analysis using 22 items. The major sources of TSP were motor vehicle (17.4%), sea salt (14.0%), secondary sulfate (13.7%), soil (12.8%), combustion (11.6%), and industry (10.8%) with the lesser contributions from non-ferrous industry (6.8%), secondary nitrate (5.4%), and road dust (3.6%). From the molecular marker-PMF analysis including only organic marker compounds (41species), the eight-sources were separated as follows: The resolved eight sources included combustion (LMW-PAHs), biomass burning, vegetative detritus (n-Alkane), benzo(a)pyrene, SOA1, SOA2, combustion (HMW-PAHs), and motor vehicle. Among them, secondary organic aerosol, PAHs, and motor vehicle were evaluated as three major sources of organic carbon sources. The source contribution of organic aerosol resolved by PMF model showed different characteristics depending on the season. The vegetative detritus and motor vehicle were increased during the summer season by the increase in biogenic/photochemical activity. However, most of the other organic sources were prominent in the winter season by the increase in the level of air pollution emission and atmospheric stability. In addition, CPF results identified possible locations for local source, which included primary sources, biomass burning/soil, motor vehicle/non-ferrous industry, vegetative detritus (n-alkane), benzo(a)pyrene, and combustion (PAHs).
Through this study, various sources of PM were evaluated by using MM-PMF analysis. Sea port and combustion sources were found as the additional PM2.5 sources that did not appear in other areas. The contribution of sea salt and soil pollutants in the coarse particle was two times as high as those in the fine particle. However, secondary organic and inorganic species generated by the oxidation reaction of primary pollutants occupied a very large portion of fine particulate matters. As a result, secondary oxidation reaction was considered as a primary cause of PM2.5. Therefore, it is very important to explain the process for finding out the sources of these secondary pollutants and to evaluate those sources in detail. Even though local sources existed, PSCF analysis indicated that a certain part of pollutants such as secondary aerosol, soil, and biomass burning have been associated with long-range transport. Another important fact was that SOA, motor vehicle, and combustion (PAHs) were identified as a major source of organic carbon. Finally, there was an increase by more than 10 times in particulate organic pollutants in the fine dust during the smog period.
This study has some important implications
first, it is first attempt to analyze and evaluate the organic constituents of particulate matter in Korea. Second, we found the chemical composition of particulate matter for more than one hundred organic and inorganic species. And finally, we could identify the contribution and major sources for particulate compounds through receptor model. This kind of characterization process for particulate organic aerosols will be a key foundation to understand the importance of the issue and be helpful to provide possible solutions which are relevant to PM reduction measures in the future.
Language
English
URI
https://hdl.handle.net/10371/120775
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Graduate School of Public Health (보건대학원)Dept. of Public Health (보건학과)Theses (Ph.D. / Sc.D._보건학과)
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