• Title/Summary/Keyword: Heavy duty road

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A Comparative Study on Fuel Consumption Depending on The Use of Lift Axle (가변축 사용여부에 따른 연료소모량 비교 연구)

  • Oh, Ju-Sam;Eo, Hyo-Kyoung
    • International Journal of Highway Engineering
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    • v.13 no.3
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    • pp.185-193
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    • 2011
  • As a Lift axle is an additional axle installed mostly in heavy freight truck, It"s introduced for the purpose of cost saving, such as logistics, fuel, tire wear and prevention of the pavement damage. However, the Effects of a lift axle are anecdotal and they have occurred often that a lift axle is used improperly by expectations of some drivers. For these reasons, this study conducts a field experiment in order to identifying the change rate of fuel consumption due to an a Lift axle using, develops the fuel consumption model of field data, and then compares the effects of a Lift axle using through application of the model. As a result, fuel consumption decreased in loading conditions that are both empty and full when not using a lift axle.

Estimating Transportation-Related Greenhouse Gas Emissions in the Port of Busan, S. Korea

  • Shin, Kang-Won;Cheong, Jang-Pyo
    • Asian Journal of Atmospheric Environment
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    • v.5 no.1
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    • pp.41-46
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    • 2011
  • The port of Busan is the fifth busiest container port in the world in terms of total mass of 20-foot equivalent units transported. Yet no attempts have been made to estimate the greenhouse gas (GHG) emissions from the port of Busan by accounting for all port-related activities of the various transportation modes. With these challenges in mind, this study estimates the first activity-based GHG emissions inventory in the port of Busan, which consists of four transportation modes: marine vessels, cargo-handling equipment, heavy-duty trucks, and railroad locomotives. The estimation results based on the most recent and complete port-related activity data are as follows. First, the average annual transportation GHG emission in the port of Busan during the analysis period from 2000 to 2007 was 802 Gg $CO_2$-eq, with a lower value of 773 Gg $CO_2$-eq and an upper value of 813 Gg $CO_2$-eq. Second, the increase in the transportation-related GHG emissions in the port of Busan during the analysis period can be systematically explained by the amount of cargo handled ($R^2$=0.98). Third, about 64% of total GHG emissions in the port of Busan were from marine vessels because more than 40% of all maritime containerized trade flows in the port were transshipment traffic. Fourth, approximately 22% of the total GHG emissions in the port of Busan were from on-road or railroad vehicles, which transport cargo to and from the port of Busan. Finally, the remaining 14% of total GHG emissions were from the cargo handling equipment, such as cranes, yard tractors, and reach stackers.

Korea Emissions Inventory Processing Using the US EPA's SMOKE System

  • Kim, Soon-Tae;Moon, Nan-Kyoung;Byun, Dae-Won W.
    • Asian Journal of Atmospheric Environment
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    • v.2 no.1
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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.

Evaluation of the Impact of Fuel Economy by Each of Driving Modes for Medium-Size Low-Floor Bus (중형저상버스의 개별주행모드에 따른 연료소비율 평가)

  • Jung, Jae-wook;Ro, Yun-sik;Ahn, Byong-kyu
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.9
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    • pp.133-140
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    • 2016
  • The Ministry of Land, Infrastructure and Transport has introduced low-floor buses, which are convenient for passengers getting on and off the bus and for the handicapped. The standard bus model is 11 m long and uses compressed natural gas (CNG). However, this model has drawbacks in narrow rural road conditions such as those in farming and fishing villages and mountainous areas, as well as difficulty in refueling since CNG facilities are not readily available. In this study, running resistance values were obtained by coasting performance tests on actual roads using a Tata Daewoo LF-40 model with three different weight conditions: curb vehicle weight (CVW), half vehicle weight (HVW), and gross vehicle weight (GVW).The test methods include WHVC, NIER-06, and constant-speed driving at 60 km/h. These tests were used to measure the fuel economy of vehicles other than the target vehicles to obtain the combined fuel economy. The energy efficiency was highest in the case of CVW. In the WHVC mode, the fuel consumption rates of HVW and GVW were typically 3.5% and 12% higher than that of CVW, respectively. In constant-speed driving, the fuel efficiency of HVW was higher than that of CVW. Further research is required to analyze the exhaust gas data.