• Title/Summary/Keyword: vehicle kilometer travelled

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

  • Kim, Ki-Dong;Lee, Tae-Jung;Jung, Won-Seok;Kim, Dong-Sool
    • Journal of Korean Society for Atmospheric Environment
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    • v.28 no.3
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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.

A development of CO2 emission estimation model based on the spatial configuration of street networks, building capacity and building usages (도로부문 이산화탄소 배출량 추정 모델의 개발: 도로망, 건물규모, 건물용도의 공간배치를 중심으로)

  • Kim, Young-Ook;Kim, Kyoung-Yong;Park, Hoon-Tae
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.6
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    • pp.3879-3887
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    • 2014
  • This paper presents a model to estimate the amount of $CO_2$ emitted by cars in cities. Based on the spatial configuration of street networks, building masses and usages, it first develops a deductive model to combine them in a way to account for $CO_2$ emission amount by cars. It then proceed to validate model behaviours through a series of simulations on some ideal urban settings and finally calibrate it following its real application to the five case study cities in Korea. In contrast to the conventional 'top-down' approaches, we expect our model to have high utilities, particularly in the field of urban planning and design, where we cannot but deal directly with the spatial configuration of urban components and microscopic human activities.

Comparative Study on the Methodology of Motor Vehicle Emission Calculation by Using Real-Time Traffic Volume in the Kangnam-Gu (자동차 대기오염물질 산정 방법론 설정에 관한 비교 연구 (강남구의 실시간 교통량 자료를 이용하여))

  • 박성규;김신도;이영인
    • Journal of Korean Society of Transportation
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    • v.19 no.4
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    • pp.35-47
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    • 2001
  • Traffic represents one of the largest sources of primary air pollutants in urban area. As a consequence. numerous abatement strategies are being pursued to decrease the ambient concentration of pollutants. A characteristic of most of the these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emission inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for vehicle types. The majority of inventories are compiled using passive data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. The study of current trends are towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this study, a methodology of motor vehicle emission calculation by using real-time traffic data was studied. A methodology for estimating emissions of CO at a test area in Seoul. Traffic data, which are required on a street-by-street basis, is obtained from induction loops of traffic control system. It was calculated speed-related mass of CO emission from traffic tail pipe of data from traffic system, and parameters are considered, volume, composition, average velocity, link length. And, the result was compared with that of a method of emission calculation by VKT(Vehicle Kilometer Travelled) of vehicles of category.

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