• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.93-105
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• 2014

This study evaluated the relative efficiency of mobile emission reduction countermeasures through a Data Envelopment Analysis (DEA) approach and determined the priority of countermeasures based on the efficiency. Ten countermeasures currently applied for reducing greenhouse gases and air pollution materials were selected to make a scenario for evaluation. The reduction volumes of four air pollution materials(CO, HC, NOX, PM) and three greenhouse gases($CO_2$, $CH_4$, $N_2O$) for the year 2027, which is the last target year, were calculated by utilizing both a travel demand forecasting model and variable composite emission factors with respect to future travel patterns. To estimate the relative effectiveness of reduction countermeasures, this study performed a super-efficiency analysis among the Data Envelopment Analysis models. It was found that expanding the participation in self car-free day program was the most superior reduction measurement with 1.879 efficiency points, followed by expansion of exclusive bus lanes and promotion of CNG hybrid bus diffusion. The results of this study do not represent the absolute data for prioritizing reduction countermeasures for mobile greenhouse gases and air pollution materials. However, in terms of presenting the direction for establishing reduction countermeasures, this study may contribute to policy selection for mobile emission reduction measures and the establishment of systematic mid- and long-term reduction measures.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.73-82
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• 2017

As of December 2016, the number of registered automobiles in Korea exceeds 21million. As a result, greenhouse gas emission by transportation sector are increasing every year. It was concluded that the development of the driving strategy considering the driving behavior and the road conditions, which are known to affect the fuel efficiency and the greenhouse gas emissions, could be the most effective fuel economy improvement. Therefore, this study aims to develop a fuel efficient driving strategy in a complex linear section with uphill and curved sections. The road topography was designed according to 'Rules about the Road Structure & Facilities Standards'. Various scenarios were selected. After generating the speed profile, it was applied to the Comprehensive Modal Emission Model and fuel consumption was calculated. The scenarios with the lowest fuel consumption were selected. After that, the fuel consumption of the manual driver's driving record and the selected optimal driving strategy were compared and analyzed for verification. As a result of the analysis, the developed optimal driving strategy reduces fuel consumption by 21.2% on average compared to driving by manual drivers.

• Journal of Korean Society of Transportation
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• v.33 no.3
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• pp.237-246
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• 2015

Operation and Maintenance in road infrastructure is repetitive carbon emissions activities to preserve the road in its originally constructed condition. In the view of road planning and construction, operation, and maintenance of life cycle, operation and maintenance stage quantification of carbon emissions is very important because it is easily accessible activities to reduce carbon emissions in road infrastructure that existing and new road. However, carbon emissions estimation in operation and maintenance stage is yet to do, because data collection is so hard and carbon emissions estimation methodology is very complicated. In this study, a basic unit of carbon emission in the operation and maintenance stage of the road infrastructure was developed in order to get the quantitative determination of carbon that occurring. Carbon emissions of the Expressway and Common state road was calculated by using the basic unit of carbon emission and application plan of basic unit of carbon emission are presented.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.162-176
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• 2021

Recently, Autonomous Vehicle(AV) has been expected to solve various transportation problems. s the problem of environmental pollution become serious, research to reduce pollution is needed. However, empirical research on AV related pollution is insufficient. Based on this background, this study analyzed network performance changes and CO₂ emissions introduc AVs and Electric Vehicles(EV) in eight intersections. The results show that when AVs with internal combustion engines were, the effect of carbon reduction over the network was insignificant. On the other hand, it was that the total amount of CO₂ generated in the network decreased significantly when EVs and autonomous electric vehicles were emissions in the transportation sector.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.77-84
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• 2016

In 2012, total GHG emissions in transport sector reached 88 Million ton CO2eq. The emissions generated in the road accounted for 94% of the transport sector. Currently, there are many efforts to operate an education and campaign for eco-driving. However study for eco-friendly vehicle control considering road alignment is limited. Therefore, the purpose of this study is to address fuel-efficient driving strategy in horizontal curve section. To fulfill the goal, designed ideal freeway horizontal curve road follows regulations about road structure. And safety speed is calculated for considering vehicle's safety on horizontal curve road. Authors composed the acceleration and deceleration scenario for each horizontal curve section and generated the speed profiles that are limited by the safety speed. Speed profiles are converted into force that horizontal curve affect to fuel consumption. Then, we calculated fuel consumption using Comprehensive Modal Emission Model. Then, we developed eco-driving strategy by selecting most fuel-efficient scenario. To validate this strategy, we selected study site and compared fuel consumption for eco and manual driving. As the result, fuel consumption when driver used eco-driving was lessened by 20.73% than that of manual driving.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.1
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• pp.297-304
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• 2013

Due to its excessive $CO_2$ emissions, road transport sector becomes a target for emission reduction strategies. Although precise and reliable emissions inventories are necessary for evaluating plans and strategies, developing the region-wide inventory is a difficult task mainly because of a lack of data including travel patterns and modal volumes in the reginonal context. Most existing inventory methodologies employ fuel sale data within the target region, which ignores actual regional traffic patterns and thus not suited to its geographical context. To overcome these problems, this study develops region-wide $CO_2$ emissions inventory methodology by utilizing the Korea Transport DB (KTDB). KTDB provides a number of useful information and data, such as road network with which one can identify in and out trips over the entire region, traffic volumes of various modes, distance of travel, travel speed and so on. A model of equations that allow the computation of volume of $CO_2$ emitting from the road transport activities within the target region is developed. Using the model, numerical analyses are performed for the case of Busan Metropolitan City to demonstrate the applicability of the developed model. This study is indeed exploratory in the sense that using the existing data, it develops the $CO_2$ emissions inventory methodology which can produce better results than those from conventional fuel sales methodology. This study also suggests further reresarch directions to develop more refined methodologies in region-wide basis.

• 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.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.247-256
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• 2012

Recently, estimation of greenhouse gas (GHG) emission has continuously emerged as an important global issue. This study compares various statistical methods for estimation of fuel consumption, which is necessary for calculation of GHG emission in road transportation sector. Existing methods have focused on using merely transportation fuel supply or distance traveled for calculation of fuel consumption. Estimates of GHG emission based on fuel supply, however, cannot reflect various vehicle types or model year. This study suggests and compares, from statistical point of view, several methods, which can be applied to estimate fuel consumption of each vehicle, by combining distance traveled and fuel efficiency (mileage), and total fuel consumption of all vehicles. It also suggests practical measures that can reflect vehicle types and model year to suggested methods for future research.

• Journal of Environmental Science International
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• v.18 no.7
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• pp.747-754
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• 2009

In this study, which aims to estimate the volume of greenhouse gas emitted by road transportation vehicles in Changwon City, the emission rate was calculated on the basis of the actual traffic volume measured at major crossroads and compared with the results obtained from the methodology used to estimate the greenhouse gas emissions of road transportation provided in the IPCC 2006 GL guidelines (Tier 1, Tier 3). Analysis of the results of the comparison showed that the Tier 1 methodology, which was applied in the estimation of the rate of greenhouse gas emissions, carries a high probability of underestimation, while the Tier 3 methodology carries a relatively high probability of overestimation. Therefore, when considering the assignment of permissible rates of emission to local governments, the application of the methodology, i.e. whether one uses Tier 1 or Tier 3, may result in a large difference in the rate of allowable emissions. It is suggested that a method based on the actual volume of traffic would be the most reasonable one with regard to the development of a realistic plan.

• 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.