• 한국대기환경학회지
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• 제24권1호
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• pp.72-82
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• 2008

Benzene is a very harmful and toxic compound known as human carcinogen by all routes of exposure. Owing to the risky feature of benzene, several countries such as Japan, UK and EU have established the ambient air quality standard and protect from that risk of it. Korea also has designated it as one of the criteria air pollutants and established the concentration limit ($5\;{\mu}g/m^3$) in the air and is going to apply the standard from 2010. Benzene is emitted from various sources such as combustion plants, production processes, waste treatment facilities and also automobiles. Mobile source is known as one of the major emission sources of benzene. In this study, we estimated the domestic emissions of benzene from mobile source and compared the results with those of advanced countries. Mobile source was divided into 2 categories, Le., on-road source and non-road source. The total emissions of benzene from mobile source were estimated as 3,106 tons/yr and 1,612 tons/yr was emitted from on-road source and 1,494 tons/yr was from non-road source. Emission ratio of benzene from on-road source showed that 80.0% was from passenger cars, 10.1% was from taxis, 7.2% was from light-duty vehicles, 2.5% was from heavy-duty vehicles and 0.2% was from buses. In the case of non-road source, the distribution showed that 66.3% was from construction machineries, 14.5% was from locomotives, 11.7% was from ships, 7.1% was from agriculture equipments and 0.5% was from aircrafts. The cold-start emissions were estimated as 942 tons/yr and this value was almost 1.5 times greater than that for hot engine emissions (608 tons/yr). In addition, the fuel-based distribution was 65.9%, 31.1% and 2.8% from gasoline, LPG and diesel vehicles, respectively. The emission ratio from mobile source occupied 65% and 30% of total benzene emissions in USA and UK, respectively. In case of Korea, the emission ratio of benzene from mobile source occupied 29% (15% from on-road source, 14% from non-road source) which showed similar value with UK.

• 한국대기환경학회지
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• 제32권1호
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• pp.9-20
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• 2016

Ozone has been a problem in big cities. That is secondary air pollutant produced by nitrogen oxide and VOCs in the atmosphere. In order to solve this, the first to be the analysis of the $NO_x$ and VOCs. The main source of nitrogen oxide is the road mobile. Industrial sources in Seoul are particularly low, and mobile traffics on roads are large, so 45% of total $NO_x$ are estimated that road mobile emissions in Seoul. Thus, it is necessary to clarify the relation with the activity of road mobile source and $NO_x$ concentration. In this study, we analyzed the 4 locations with roadside automatic monitoring systems in their center. The V.K.T. calculating areas are set in circles with 50 meter spacing, 50 meter to 500 meter from their center. We assumed the total V.K.T. in the set radius affect the $NO_x$ concentration in the center. We used the hourly $NO_x$ concentrations data for the 4 observation points in July for the interference of the other sources are minimized. We used the intersection traffic survey data of all direction for construction of the V.K.T. data, the mobile activities on the roads. ArcGIS application was used for calculating the length of roads in the set radius. The V.K.T. data are multiplied by segment traffic volume and length of roads. As a result, the $NO_x$ concentration can be expressed as linear function formula for V.K.T. with high predictive power. Moreover we separated background concentration and concentrations due to road mobile source. These results can be used for forecasting the effect of traffic demand management plan.

• 한국재난정보학회 논문집
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• 제13권1호
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• pp.96-105
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• 2017

지구 온난화는 인류의 재앙이며, 그 주된 원인은 이산화탄소이다. 따라서 온실가스 저감을 위한 범국가적 정책이 수행되고 있으며, 정책의 수립/집행에 있어 정확한 온실가스 배출량 산정은 매우 주요하다. 도로이동오염원에 의한 온실가스 배출량 산정을 위해서는 도로구간별 CO2 배출 원단위가 필요하며, 이는 차량의 속도자료를 이용하여 산정된다. 그러나 전국 도로망에 대한 속도자료의 수집 및 분석에는 한계가 있다. 따라서 본 연구에서는 방대한 양의 차량 내비게이션 자료를 이용한 비집계방식의 도로구간 CO2 배출량 원단위 산정방법을 제시한다. 제시된 방법론은 기존 집계방식에 의한 CO2 배출 원단위보다 정확하며, 전국 도로망에 직접적으로 적용이 가능하다.

• 한국산학기술학회논문지
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• 제8권3호
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• pp.593-600
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• 2007

본 논문에서는 도로망의 사정에 따라 변화될 수 있는 자동차 애드 혹 망 성능을 연구하기 위하여 도로망을 구성하고 라우팅 프로토콜별로 적용하여 성능을 비교분석하였다. 적용한 라우팅 프로토콜은 MANET(Mobile Ad-Hoc Network)인 AODV(Ad-hoc On-Demand Distance Vector)와 DSR(Dynamic Source Routing) 프로토콜이다. AODV는 일반적으로 DSR보다 성능이 우수한 것으로 알려져 있으나 애드 혹 도로망에서 자동차의 수가 많아질 경우에는 DSR 프로토콜이 성능 면에서 비슷하거나 오히려 우세하다는 결과를 얻을 수 있었다. 시뮬레이션을 위하여 왕복 4차선을 OPNET에서 구현하고 실행하였다.

• Asian Journal of Atmospheric Environment
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• 제2권1호
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• pp.34-46
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• 2008

Emissions inputs for use in air quality modeling of Korea were generated with the emissions inventory data from the National Institute of Environmental Research (NIER), maintained under the Clean Air Policy Support System (CAPSS) database. Source Classification Codes (SCC) in the Korea emissions inventory were adapted to use with the U.S. EPA's Sparse Matrix Operator Kernel Emissions (SMOKE) by finding the best-matching SMOKE default SCCs for the chemical speciation and temporal allocation. A set of 19 surrogate spatial allocation factors for South Korea were developed utilizing the Multi-scale Integrated Modeling System (MIMS) Spatial Allocator and Korean GIS databases. The mobile and area source emissions data, after temporal allocation, show typical sinusoidal diurnal variations with high peaks during daytime, while point source emissions show weak diurnal variations. The model-ready emissions are speciated for the carbon bond version 4 (CB-4) chemical mechanism. Volatile organic carbon (VOC) emissions from painting related industries in area source category significantly contribute to TOL (Toluene) and XYL (Xylene) emissions. ETH (Ethylene) emissions are largely contributed from point industrial incineration facilities and various mobile sources. On the other hand, a large portion of OLE (Olefin) emissions are speciated from mobile sources in addition to those contributed by the polypropylene industry in point source. It was found that FORM (Formaldehyde) is mostly emitted from petroleum industry and heavy duty diesel vehicles. Chemical speciation of PM2.5 emissions shows that PEC (primary fine elemental carbon) and POA (primary fine organic aerosol) are the most abundant species from diesel and gasoline vehicles. To reduce uncertainties in processing the Korea emission inventory due to the mapping of Korean SCCs to those of U.S., it would be practical to develop and use domestic source profiles for the top 10 SCCs for area and point sources and top 5 SCCs for on-road mobile sources when VOC emissions from the sources are more than 90% of the total.

• 한국입자에어로졸학회지
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• 제8권2호
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• pp.47-54
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• 2012

Paved road dust emissions were investigated 14 times on 12 main roads in Seo-Cho Gu, Seoul, Korea by vehicle-based mobile sampling system(Road Dust Monitoring System) during September to December 2011. Also, fourteen heavy metals present in the dust samples were analyzed by ICP. ICP analysis showed that one of major source of the road dust would be urban construction. A large amount of silt was found, which might be originated mainly from building construction and open beds of trees. Trace element and pollution indices of heavy metals(Cd, Cu, Ni, Pb, Zn) on the roads adjacent to the commercial area had higher concentrations than those on the roads adjacent to the construction and residential areas because of traffic density and heavy traffic.

• 대한환경공학회지
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• 제38권5호
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• pp.269-278
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• 2016

수도권지역의 대기오염을 개선하기 위해 수도권 대기환경 개선에 관한 특별법이 제정되었고 2005년부터 시행되었다. 그 결과 수도권의 대기질은 개선되었으나 각 대책의 평가에 대한 연구는 부족하다. 이에, 본 연구는 도로이동오염원의 배출량 저감정책이 질소산화물의 농도저감에 미치는 영향을 정량적으로 분석하고자 하였다. 이를 위해 MM5-SMOKE-CMAQ 모델 시스템을 이용하여 수치모사를 수행하였다. 2007년 수도권 $NO_x$ 저감 배출량은 16,561톤으로서 4.7%의 저감률을 보였다. 여러 대책 중 제작차 배출허용기준강화 대책이 가장 효과적이었다. 지역별 삭감실적은 차이가 커서 서울의 삭감률은 인천과 경기의 약 2배에 달하였다. 결과적으로 $NO_x$ 저감의 효과는 서울 도심에 집중적으로 나타났다. 이동오염원 저감대책에 의하여 서울의 $NO_2$ 농도는 연평균 0.60 ppb (2.0%)저감되었고 인천과 경기는 각각 0.18 ppb (1.5%), 0.22 ppb (1.7%)가 저감되었다. 봄과 겨울의 저감농도는 여름과 가을에 비해 1.5~2.0배 정도 높았다. 도심과 풍하지역으로의 $NO_2$ 저감효과 분산때문에 도심지역의 $NO_x$ 배출량 저감이 직접적인 $NO_2$ 농도 저감에 효과적이지 않았다.

• 한국대기환경학회지
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• 제28권4호
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• pp.454-465
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• 2012

The Korean government decided to reduce 30% of GHG (greenhouse gas) emissions BAU in 2020. Since many efforts to reduce emissions are urgently needed in Korea, the central administrative organization urges local governments to establish their own reduction schemes. Among many GHG emission categories, the emission from mobile source in Gyeonggi Province accounted for 25.3% of total emissions in 2007 and further the emission from road transport sector occupied the most dominant portion in this transportation category. The objective of this study was to compare 3 types of GHG emissions from road transport sector in 31 local cities/counties of Gyeonggi Province, which have been estimated by Tier 1, Tier 2, and Tier 3 methodologies. As results, the GHG emission rates by the Tier 1 and Tier 2 were $19,991kt-CO_2\;Eq/yr$ and $18,511kt-CO_2\;Eq/yr$, respectively. On the other hand, the emission rate by Tier 3 excluding a branch road emission portion was $18,051kt-CO_2\;Eq/yr$. In addition, the total emission rate including all the main and branch road portions in Gyeonggi Province was $24,152kt-CO_2\;Eq/yr$, which was estimated by a new Tier 3 methodology. Based on this study, we could conclude that Tier 3 is a reasonable methodology than Tier 1 or Tier 2. However, more accurate and less uncertain methodology must be developed by expanding traffic survey areas and adopting a suitable model for traffic volumes.

• 한국대기환경학회지
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• 제28권3호
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• pp.233-248
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• 2012

The national emission from energy sector accounted for 84.7% of all domestic emissions in 2007. Of the energy-use emissions, the emission from mobile source as one of key categories accounted for 19.4% and further the road transport emission occupied the most dominant portion in the category. The road transport emissions can be estimated on the basis of either the fuel consumed (Tier 1) or the distance travelled by the vehicle types and road types (higher Tiers). The latter approach must be suitable for simultaneously estimating $CO_2$, $CH_4$, and $N_2O$ emissions in local administrative districts. The objective of this study was to estimate 31 municipal GHG emissions from road transportation in Gyeonggi Province, Korea. In 2008, the municipalities were consisted of 2,014 towns expressed as Dong and Ri, the smallest administrative district unit. Since mobile sources are moving across other city and province borders, the emission estimated by fuel sold is in fact impossible to ensure consistency between neighbouring cities and provinces. On the other hand, the emission estimated by distance travelled is also impossible to acquire key activity data such as traffic volume, vehicle type and model, and road type in small towns. To solve the problem, we applied a hierarchical cluster analysis to separate town-by-town road patterns (clusters) based on a priori activity information including traffic volume, population, area, and branch road length obtained from small 151 towns. After identifying 10 road patterns, a rule building expert system was developed by visual basic application (VBA) to assort various unknown road patterns into one of 10 known patterns. The expert system was self-verified with original reference information and then objects in each homogeneous pattern were used to regress traffic volume based on the variables of population, area, and branch road length. The program was then applied to assign all the unknown towns into a known pattern and to automatically estimate traffic volumes by regression equations for each town. Further VKT (vehicle kilometer travelled) for each vehicle type in each town was calculated to be mapped by GIS (geological information system) and road transport emission on the corresponding road section was estimated by multiplying emission factors for each vehicle type. Finally all emissions from local branch roads in Gyeonggi Province could be estimated by summing up emissions from 1,902 towns where road information was registered. As a result of the study, the GHG average emission rate by the branch road transport was 6,101 kilotons of $CO_2$ equivalent per year (kt-$CO_2$ Eq/yr) and the total emissions from both main and branch roads was 24,152 kt-$CO_2$ Eq/yr in Gyeonggi Province. The ratio of branch roads emission to the total was 0.28 in 2008.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2338-2356
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• 2019

Vehicular ad-hoc network (VANET) is the name of technology, which uses 'mobile internet' to facilitate communication between vehicles. The aim is to ensure road safety and achieve secure communication. Therefore, the reliability of this type of networks is a serious concern. The reliability of VANET is dependent upon proper communication between vehicles within a given amount of time. Therefore a new formula is introduced, the terms of the new formula correspond 1 by 1 to a class special ST route (SRORT). The new formula terms are much lesser than the Inclusion-Exclusion principle. An algorithm for the Source-to-Terminal reliability was presented, the algorithm produced Source-to-Terminal reliability or computed a Source-to-Terminal reliability expression by calculating a class of special networks of the given network. Since the architecture of this class of networks which need to be computed was comparatively trivial, the performance of the new algorithm was superior to the Inclusion-Exclusion principle. Also, we introduce a mobility metric called universal speed factor (USF) which is the extension of the existing speed factor, that suppose same speed of all vehicles at every time. The USF describes an exact relation between the relative speed of consecutive vehicles and the headway distance. The connectivity of vehicles in different mobile situations is analyzed using USF i.e., slow mobility connectivity, static connectivity, and high mobility connectivity. It is observed that $p_c$ probability of connectivity is directly proportional to the mean speed ${\mu}_{\nu}$ till specified threshold ${\mu}_{\tau}$, and decreases after ${\mu}_{\tau}$. Finally, the congested network is connected strongly as compared to the sparse network as shown in the simulation results.