Tae-Jung Lee

The temporal variabilities in the concentrations of airborne lead and its relationship to aerosol behavior

Abstract We have made routine measurements of the mass-particle size distributions of airborne particulate matter (PM) and the associated lead (Pb) concentrations from our sampling station at the Kyung Hee University-Suwon campus in Korea during November 1989 to September 1994. The monthly Pb concentration data for the entire campaign periods varied extensively, spanning from 34 (October 1990) to 526 (February 1991) ng m−3 with the mean ± 1SD of 244 ± 119 ng m−3 (N = 56). Examinations of temporal trends in Pb distribution behavior indicate several interesting features. Whereas its annual trends appear to be affected by the deteriorating conditions of the surrounding environment (e.g. relative Pb enhancement in odd-numbered years), its seasonal trends show a very systematic and cyclic pattern that can be characterized as: a gradual decrease in concentrations across winter, spring, and summer and a moderate change after summer. A statistical analysis of our Pb data indicates the existence of generally enhanced correlations between Pb and most of environmental variables investigated concurrently. The Pb data generally exhibited strong inverse correlations with such environmental variables as temperature, relative humidity, and the amount of precipitation on one hand but positive correlations with wind-related parameters like the frequency of calmness on the other hand. Through a comparative analysis of our Pb and PM concentration data as well as their individual relationships with various environmental variables, we were able to distinguish both similarities and differences between the geochemical distribution behavior of Pb and PM in the atmosphere.

A Comparative Study on PM 10 Source Contributions in a Seoul Metropolitan Subway Station Before/After Installing Platform Screen Doors

Almost five million citizens a day are using subways as a means of traffic communication in the Seoul metropolitan. As the subway system is typically a closed environment, indoor air pollution problems frequently occurs and passengers complain of mal-health impact. Especially is well known as one of the major pollutants in subway indoor environments. The purpose of this study was to compare the indoor air quality in terms of and to quantitatively compare its source contributions in a Seoul subway platform before and after installing platform screen doors (PSD). samples were collected on the J station platform of Subway Line 7 in Seoul metropolitan area from Jun. 12, 2008 to Jan. 12, 2009. The samples collected on membrane filters using mini-volume portable samplers were then analyzed for trace metals and soluble ions. A total of 18 chemical species (Ba, Mn, Cr, Cd, Si, Fe, Ni, Al, Cu, Pb, Ti, , , , , , , and ) were analyzed by using an ICP-AES and an IC after performing proper pre-treatments of each sample filter. Based on the chemical information, positive matrix factorization (PMF) model was applied to identify the source of particulate matters. for the station was characterized by three sources such as ferrous related source, soil and road dust related source, and fine secondary aerosol source. After installing PSD, the average concentration was decreased by 20.5% during the study periods. Especially the contribution of the ferrous related source emitted during train service in a tunnel route was decreased from 59.1% to 43.8% since both platform and tunnel areas were completely blocked by screen doors. However, the contribution of the fine secondary aerosol source emitted from various outside combustion activities was increased from 14.8% to 29.9% presumably due to ill-managed ventilation system and confined platform space.

Source Identification of Ambient Size-by-Size Particulate Using the Positive Matrix Factorization Model on the Border of Yongin and Suwon

The suspended particulate matters have been collected on membrane filters and glass fiber filters by an 8-stage cascade impactor for 2 years (Sep. 2005Sep. 2007) in Kyung Hee University-Global Campus located on the border of Yongin and Suwon. The 20 chemical species (Al, Mn, Si, Fe, Cu, Pb, Cr, Ni, V, Cd, Ba, , , , , , , , and ) were analyzed by an ICP-AES and an IC after performing proper pre-treatments of each sample filter. Based on these chemical information, the PMF receptor model was applied to identify the source of ambient size-by-size particulate matters. The receptor modeling is the one of the statistical methods to achieve resonable air pollution management strategies. A total of 10 sources was identified in 9 size-ranges such as long-range transport, secondary aerosol, related source, coal combustion, sea-salt, soil, oil combustion, auto emission, incineration, and biomass burning. Especially, the secondary aerosol source assorted in fine and coarse modes was intensively studied.

Identifying Ambient PM 2.5 Sources and Estimating their Contributions by Using PMF : Separation of Gasoline and Diesel Automobile Sources by Analyzing ECs and OCs

The purpose of this study was to identify sources and to estimate their contributions to the border of Yongin-Suwon area, based on the analysis of the mass concentration and the associated inorganic elements, ions and carbon components. The contribution of sources were estimated by using a positive matrix factorization (PMF) model to identify air emission sources. For this study, samples were collected from May, 2007 to April, 2008. The inorganic elements were analyzed by an ICP-AES. The ionic components in were analyzed by an Ie. The carbon components were also analyzed by DRI/OGC analyzer. After performing PMF modeling, a total of 12 sources were identified and their contributions were quantitatively estimated. The contributions from each emission source were as follows: 11.3% from oil combustion source, 3.4% from bus/highway source, 5.8% from diesel vehicle source, 4.7% from gasoline vehicle source, 8.8% from biomass burning source, 15.1 % from secondary sulfate, 5.2% from secondary nitrate source, 13.4% from industrial related source, 4.1% from Cl-rich source, 19.6% from soil related source, 1.0% from aged sea salt, and 7.4% from coal combustion source, respectively. This study provides basic information on the major sources affecting air quality, and then it will help to effectively control in this study area.

Quantitative Estimation of Precipitation Scavenging and Wind Dispersion Contributions for PM 10 and NO 2 Using Long-term Air and Weather Monitoring Database during 2000~2009 in Korea

Long-term air and weather data monitored during the period of 2000 to 2009 were analyzed to quantitatively estimate the precipitation scavenging and wind dispersion contributions of ambient and in Korea. Both air pollutants and meteorological data had been respectively collected from 120 stations by the Ministry of Environment and from 20 weather stations by the Korea Meteorological Administrations in all parts of Korea. To stochastically identify the relation between a meteorological factor and an air pollutant, we initially defined the SR (scavenging ratio) and the DR (dispersion ratio) to separately calculate the precipitation and wind speed effects on the removal of a specific air pollutant. We could then estimate the OSC (overall scavenging contribution) and the ODC (overall dispersion contribution) with considering sectoral precipitation and wind speed probability density distributions independently. In this study, the SRs for both and were generally increased with increasing the amounts of precipitation and then the OSCs for and were estimated by 22.3% and 15.7% on an average in Korea, respectively. However, the trend of the DR was quite different from that of SR. The DR for was increased with increasing wind speed up to 2.5 m/s and further the DR for showed a minimum in the range of . The ODCs for and were estimated by 14.9% and 1.0% in Korea, respectively. Finally, we have also provided an interesting case study observed in Seoul.

Comparison of Greenhouse Gas Emissions from Road Transportation of Local Government by Calculation Methods

The objective of this study was to compare greenhouse gas emissions from road transportation by calculation methods (Tier 1, Teir 2, and Tier 3). Tier 1 based on 2006 IPCC guidelines default emission factor and amount of fuel consumption. The Tier 2 approach is the same as Tier 1 except that country-specific carbon contents of the fuel sold in road transport are used. Tier 2 based on emission factor of guidelines for local government greenhouse gas inventories (Korea Environment Corporation), the fuel consumption per one vehicle, and the registered motor vehicles. The Tier 3 approach requires detailed, country-specific data to generate activity-based emission factors for vehicle subcategories (National Institute of Environmental Research) and may involve national models. Tier 3 calculates emissions by multiplying emission factors by vehicle activity levels (e.g., VKT) for each vehicle subcategory and possible road type. VKT was estimated by using GIS road map and traffic volume of the section. The GHG average emission rate by the Tier 1 was 728,857 /yr, while Tier 2 and Tier 3 were 864,757 /yr and 661,710 /yr, respectively. Tier 3 was underestimated by 10.1 and 20.7 percent for the GHG emission observed by Tier 1 and Tier 2, respectively. Based on this study, we conclude that Tier 2 is reasonable GHG emissions than Tier 1 or Tier 3. But, further study is still needed to accurate GHG emission from Tier 3 method by expanding the traffic survey area and developing the model of local road traffic.

Characteristics of Ionic Components in Size-resolved Particulate Matters in Suwon Area

The main purpose of this study was to investigate air quality trends of ambient aerosol with obtaining size-fractionated information. The suspended particulate matters were continuously collected on membrane filters and glass fiber filters by an 8-stage cascade impactor for 2 years (Sep. 2005 Sep. 2007) in Kyung Hee University-Global Campus. 8 ionic species (, , , , , , , and ) were analyzed by an IC after performing proper pretreatments of each sample filter. The average concentration levels of each ion were of , of , of , of , of , of , of , and of , respectively. The distribution pattern of , , , , and was bi-modal and two peaks appeared in the range of and , respectively. On the other hand, , , and showed patterns of uni-modal distribution, mostly abounded in the fine mode group.

Identification of PM 10 Chemical Characteristics and Sources and Estimation of their Contributions in a Seoul Metropolitan Subway Station

Since the underground transportation system is a closed environment, indoor air quality problems may seriously affect many passengers` health. The purpose of this study was to understand characteristics in the underground air environment and further to quantitatively estimate source contributions in a Seoul Metropolitan subway station. The was intensively collected on various filters with aerosol samplers to obtain sufficient samples for its chemical analysis. Sampling was carried out in the M station on the Line-4 from April 21 to 28, July 13 to 21, and October 11 to 19 in the year of 2010 and January 11 to 17 in the year of 2011. The aerosol filter samples were then analyzed for metals, water soluble ions, and carbon components. The 29 chemical species (OC1, OC2, OC3, OC4, CC, PC, EC, Ag, Al, Ba, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Si, Ti, V, Zn, , , , , , , , ) were analyzed by using ICP-AES, IC, and TOR after proper pretreatments of each sample filter. Based on the chemical information, positive matrix factorization (PMF) model was applied to identify the sources and then six sources such as biomass burning, outdoor, vehicle, soil and road dust, secondary aerosol, ferrous, and brakewear related source were classified. The contributions rate of their sources in tunnel are 4.0%, 5.8%, 1.6%, 17.9%, 13.8% and 56.9% in order.

Property Analysis of Municipal Solid Waste and Estimation of CO 2 Emissions from Waste Incinerators

Carbon dioxide () is known to be a major greenhouse gas partially emitted from waste combustion facilities. According to the greenhouse gas emission inventory in Korea, the quantity of the gas emitted from waste sector in 2005 represents approximately 2.5 percent of all domestic greenhouse gas emission. Currently, the emission rate of greenhouse gas from the waste sector is relatively constant partly because of both the reduced waste disposal in landfills and the increased amounts of waste materials for recycling. However, the greenhouse gas emission rate in waste sectors is anticipated to continually increase, mainly due to increased incineration of solid waste. The objective of this study was to analyze the property of Municipal Solid Waste (MSW) and estimate emissions from domestic MSW incineration facilities. The emission rates obtained from the facilities were surveyed, along with other two methods, including Tier 2a based on 2006 IPCC Guideline default emission factor and Tier 3 based on facility specific value. The emission rates were calculated by using concentrations and gas flows measured from the stacks. Other parameters such as waste composition, dry matter content, carbon content, oxidation coefficient of waste were included for the calculation. The average emission rate by the Tier 2a was 34,545 ton/y, while Tier 3 was 31,066 ton/y. Based on this study, we conclude that Tier 2a was overestimated by 11.2 percent for the emission observed by Tier 3. Further study is still needed to determine accurate emission rates from municipal solid waste incineration facilities and other various combustion facilities by obtaining country-specific emission factor, rather than relying on IPCC default emission factor.

Identification of Atmospheric PM 10 Sources and Estimating Their Contributions to the Yongin-Suwon Bordering Area by Using PMF

The purpose of this study was to extensively identify sources and to estimate their contributions to the study area, based on the analysis of the mass concentration and the associated inorganic elements, ions, and total carbon. The contribution of sources was estimated by applying a receptor method because identifying air emission sources were effective way to control the ambient air quality. particles were collected from May to November 2007 in the Yongin-Suwon bordering area. samples were collected on quartz filters by a high-volume air sampler. The inorganic elements (Al, Mn, V, Cr, Fe, Ni, Cu, Zn, Cd, Pb, Si, Ba, Ti and Ag) were analyzed by an ICP-AES after proper pre-treatments of each sample. The ionic components of these samples (, , , , , , , and ) were analyzed by an IC. The carbon components (OC1, OC2, OC3, OC4, OP, EC1, EC2 and EC3) were also analyzed by DRI/OGC analyzer. Source apportionment of was performed using a positive matrix factorization (PMF) model. After performing PMF modeling, a total of 8 sources were identified and their contribution were estimated. Contributions from each emission source were as follows: 13.8% from oil combustion and industrial related source, 25.4% from soil source, 22.1% from secondary sulfate, 12.3% from secondary nitrate, 17.7% from auto emission including diesel (12.1%) and gasoline (5.6%), 3.1% from waste incineration and 5.6% from Na-rich source. This study provides information on the major sources affecting air quality in the receptor site, and therefore it will help us maintain and manage the ambient air quality in the Yongin-Suwon bordering area by establishing reliable control strategies for the related sources.