• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.10
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• pp.985-993
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• 2012

In this paper, a new method is proposed to estimate the sound pressure generated from gasoline direct injection (GDI) engine. There are many noise sources as much as components in GDI engine. Among these components, fuel pump, fuel injector, fuel rail, pressure pump and intake/exhaust manifolds are major components generated from top of the engine. In order to estimate the contribution of these components to engine noise, the total sound pressure at the front of the engine is estimated by using airborne source quantification (ASQ) method. Airborne source quantification method requires the acoustic source volume velocity of each component. The volume velocity has been calculated by using the inverse method. The inverse method requires many tests and has ill-condition problem. This paper suggested a method to obtain volume velocity directly based on the direct measurement of sound intensity and particle velocity. The method is validated by using two known monopole sources installed at the anechoic chamber. Finally the proposed method is applied to the identification and contribution of noise sources caused by the GDI components of the test engine.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.5
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• pp.562-573
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• 2008

Concentrations of volatile organic compounds (VOCs) measured from the local industrial sources in Wanju industrial complex during June $2007{\sim}January$ 2008. The samples were collected from the primary sources (6 emission points) in 4 major factories in Wanju industrial complex as well as two general sources in Wanju County to elucidate the abundances of speciated VOCs and their spacial and temporal distributions depending on source bases. Industrial sources are as follows; fabricated metal manufacture, motor vehicle manufacture, rubber and plastic manufacture, and chemical manufacture factories. Two general source samples were collected from gasoline gas station and dry cleaning shop in urban area. In order to understand the near source influence at receptor, samples from the two receptor sites (one is at center of the industrial complex and the other site is at distance residential area downwind from the center) were collected with sample canister, and analyzed by using GC/MSD. The concentrations from different sources were compared and discussed. The mass contributions of the speciated VOCs to total VOCs measured from industrial sources and ambient ai r at two receptors were presented and discussed.

• Journal of Korean Society for Atmospheric Environment
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• v.21 no.1
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• pp.83-96
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• 2005

The purposes of this study were to characterize the local levels of VOCs (volatile organic compounds), to develop source profiles of VOCs, and to quantify the source contribution of VOCs using the CMB (chemical mass balance) model. The concentration of VOCs had been measured every 6-day duration in the SRO monitoring site in the Yeosu Petrochemical Industrial Complex from September 2000 to August 2002. The total of 35 target VOCs, which were included in the TO-14 designated from the U.S. EPA, was selected to be monitored in the study area. During a 24-h period, the ambient VOCs were sampled by using canisters placing about 10 ～ 15 m above the ground level. The collected canisters were then analyzed by a GC-MS in the laboratory. Aside from ambient sampling at the SRO site, the VOCs had been intensively and massively measured from 8 direct sources and 4 general sources in the study area. The results obtained in the study were as follows; first, the annual mean concentrations of the target VOCs were widely distributed regardless of monitoring sites in the Yeosu Petrochemical Industrial Complex. In particular, the concentrations of BTX (Benzene, Toluene, Xylene), vinyl chloride were higher than other target compounds. Second, based on these source sample data, source profiles for VOCs were developed to apply a receptor model, the CMB model. Third, the results of source apportionment study for the VOCs in the SRO Site were as follows; The source of petrochemical plant was apportioned by 31.3% in terms of VOCs mass. The site was also affected by 16.7% from wastewater treatment plant, 14.0% from iron mills, 8.4% from refineries, 4.4% from oil storage, 3.8% from automobiles, 2.3% from fertilizer, 2.3% from painting, 2.2% from waste incinerator, 0.6% from graphic art, and 0.4% from gasoline vapor sources.

• Journal of Environmental Science International
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• v.30 no.3
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• pp.219-234
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• 2021

Industrial emissions, mainly from industrial complexes, are important sources of ambient Volatile Organic Compounds (VOCs). Identification of the significant VOC sources from industrial complexes has practical significance for emission reduction. VOC samples were collected from July 2019 to June 2020. A Positive Matrix Factorization (PMF) receptor model was used to evaluate the VOC sources in the area. Four sources were identified by PMF analysis, including coating-1, coating-2, printing, and vehicle exhaust. The coating-1 source was revealed to have the highest contribution (41.5%), followed by coating-2 (23.9%), printing (23.1%), and vehicle exhaust (11.6%). The source showing the highest contribution was coating emissions, originating from the northwest to southwest of the sample site. It also relates to facilities that produce auto parts. The major components of VOC emissions from the coating facilities were toluene, m,p-xylene, ethylbenzene, o-xylene, and butyl acetate. Industrial emissions should be the top priority to meet the relevant control criteria, followed by vehicular emissions. This study provides a strategy for VOC source apportionment from an industrial complex, which is helpful in the development of targeted control strategies.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.12 s.117
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• pp.1185-1191
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• 2006

The radiated noise of the excavator is composed of the various noise sources such as the diesel engine, cooling fan and hydraulic system, so the noise reduction for each noise source is required. In this study, the source contribution analysis for these principal noise sources is performed by using the noise source removal method. And to reduce the noise due to each one, the various experiments and analyses are studied. On the basis of these results, the proper noise reduction countermeasures are derived to develop the excavator satisfied the $2^{nd}$ noise regulation of EU.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.1
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• pp.19-30
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• 2017

The altitudinal potential source contribution function (PSCFa) method was developed by considering topography and height of back trajectories. The PSCFa calculated on the contributions of trans-boundary transport to the hourly mean concentrations of aerosol optical depth (AOD) of the Aerosol Robotic Network (AERONET) in the Distributed Regional Aerosol Gridded Observation Networks (DRAGON) KORea-US Air Quality (KORUS-AQ) campaign from March 31 to July 1 in 2016. Eastern China ($33^{\circ}N{\sim}35^{\circ}N$ and $119^{\circ}E{\sim}121^{\circ}E$) can be the major source of trans-boundary pollution to the western area in South Korea resulted from PSCFa (0~700 m). In this study, AOD by Moderate Resolution Imaging Spectroradiometer (MODIS) was compared to verify the source regions. Regionally, the effects of the long-range transport of pollutants from the eastern China on air quality in south Korea have become more significant over this period.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.1
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• pp.100-107
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• 2008

The objective of this study was to quantitatively estimate PM-10 source contribution in Gumi City, Korea. Ambient PM-10 samples were collected by a high volume air sampler, which operated for 84 different days with a 24-h sampling basis, from June 14,2001 though May 19, 2003. The filter samples were analyzed for determining 13 inorganic elements, 3 anions, and a total carbon. The study has intensively applied a receptor model, the PMF (Positive Matrix Factorization) model. The results from PMF modeling indicated that a total of seven sources were independently identified and each source was contributed to the ambient Gumi City from secondary sulfate (34%), motor vehicle (26%), soil relation (5%), field burning (3%), industrial relation (3%), secondary nitrate (22%), and incinration (7%) in terms of PM-10 mass, respectively.

• Journal of Korean Society for Atmospheric Environment
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• v.26 no.5
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• pp.543-553
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• 2010

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 $PM_{10}$ 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 $PM_{10}$ and to quantitatively compare its source contributions in a Seoul subway platform before and after installing platform screen doors (PSD). $PM_{10}$ 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 $PM_{10}$ 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, $Na^+$, $NH_4^+$, $K^+$, $Mg^{2+}$, $Ca^{2+}$, $Cl^-$, and ${SO_4}^{2-}$) 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. $PM_{10}$ 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 $PM_{10}$ 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.

• The Journal of the Acoustical Society of Korea
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• v.23 no.4
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• pp.316-323
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• 2004

Recent trend of installation of highly efficient and high Power engine in vehicles has increased complaints about exterior noise being made while travelling. To examine the sources of outer noise of vehicles controlled by regulations. using lead wrapping method. Pass-by noise tests have been conducted as opening each defined source one by one. The sources of outer noise have been found and the rate of noise contribution has been produced. The results of the tests have been applied to put noise-reducing objects in the order, and counter plans effective to reduce noise have been devised.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.6
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• pp.431-436
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• 2002

The interior sound pressure level of the Korean high-speed train(KHST) is predicted by geometrical acoustic method. For the Purpose of assuring the prediction of Interior noise of KHST by the geometrical acoustic scheme, calculated sound level values of the Korean train express(KTX) by Identical geometrical method are compared with measured values of KTX prototype vehicle by experiment. Contribution of individual sound source of KHST vehicle Into the interior response positions is calculated and sound sources are classified in influential order. Hence, it is reasonable approach to reduce sound power of most contributing noise source first. Sensitivity of the interior response position's sound pressure level (SPL) with respect to train wall sections' transmission loss are carried on and acoustically sensitive spot is identified, for example window area for passenger cabin case. Those contribution and sensitivity analysis results are suggested to design quieter train efficiently.