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도로수송부문 온실가스 배출량 산정을 위한 간선 및 지선도로상의 교통량 추정시스템 개발 (Development of Traffic Volume Estimation System in Main and Branch Roads to Estimate Greenhouse Gas Emissions in Road Transportation Category)

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기타파일
최초등록일 2025.04.18 최종저작일 2012.06
16P 미리보기
도로수송부문 온실가스 배출량 산정을 위한 간선 및 지선도로상의 교통량 추정시스템 개발
  • 미리보기

    서지정보

    · 발행기관 : 한국대기환경학회
    · 수록지 정보 : 한국대기환경학회지 / 28권 / 3호 / 233 ~ 248페이지
    · 저자명 : 김기동, 이태정, 정원석, 김동술

    초록

    The national emission from energy sector accounted for 84.7% of all domestic emissions in 2007. Of the energyuse 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 CO2, CH4, and N2O 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 CO2 equivalent per year (kt-CO2 Eq/yr)and the total emissions from both main and branch roads was 24,152 kt-CO2 Eq/yr in Gyeonggi Province. The ratio of branch roads emission to the total was 0.28 in 2008.

    영어초록

    The national emission from energy sector accounted for 84.7% of all domestic emissions in 2007. Of the energyuse 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 CO2, CH4, and N2O 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 CO2 equivalent per year (kt-CO2 Eq/yr)and the total emissions from both main and branch roads was 24,152 kt-CO2 Eq/yr in Gyeonggi Province. The ratio of branch roads emission to the total was 0.28 in 2008.

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