• 한국ITS학회 논문지
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• 제12권3호
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• pp.114-128
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• 2013

현재 온실가스 배출량 산정 방법은 온실가스 저감대책 효과 분석이 불가능하며 차량의 이동특성이 반영이 안 된 실정으로 이를 극복할 수 있는 온실가스 배출량 산정 방법의 필요로 본 연구가 시작되었다. 교통수요 분석을 통해 차종, 교통상황에 따른 HBEFA 배출계수로 배출량을 산정하는 방법을 통해 고양시에 적용하여 분석하였다. 본연구의 지자체단위 교통수요 추정방안을 통해 실질적인 교통 이용특성에 맞는 온실가스 배출량이 산출되었다. 온실가스 지자체별 통행요금, 속도제한 등 온실가스 저감 요인들이 교통수요 모형에 반영되어 온실가스 저감 대책에 대한 효과분석 후 환경영향을 줄일 수 있는 방안을 강구하여 온실가스 저감 대책 마련에 효율적으로 이용될 것으로 판단된다.

• 대한교통학회지
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• 제27권6호
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• pp.139-146
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• 2009

대기오염 물질배출량 중 도로이동오염원에 의한 배출량은 다른 오염원에 비해 월등히 높은 편이나 관련연구가 미흡한 실정이다. 본 연구에서는 교통량, 속도 및 기타기상 조건의 실시간 자료와 도로기하구조와 같은 도로특성인자를 반영하여, 대기오염 물질 배출에 도로환경요인이 미치는 영향을 분석하였다. 서울시의 실시간 대기오염 데이터와 교통량, 도로관련 데이터를 수집하여 대기오염 물질별 오염배출량 예측 회귀모형식을 구축하였다. 본 연구에서 얻어진 결과를 요약하면 다음과 같다. 첫째, 교통량이 증가할수록 오염물질의 측정량은 증가하며, 속도가 증가할수록 측정량은 감소한다. 둘째, 풍속, 온도, 습도가 증가할수록 측정량은 감소한다. 셋째, 교차로 형태가 복잡할수록 측정량은 감소한다. 예측모형을 검증하기 위하여 예측치와 실측치 데이터를 비교 분석한 결과 총 7곳의 도로변대기오염 측정망 중 실측치와 예측치가 가장 부합하는 측정망은 청계 4가 측정망인 것으로 나타났다. 본 연구는 실시간 대기오염배출량 데이터와 교통량 데이터, 도로환경 특성데이터를 이용하여 예측모형을 구축하여 현실적인 도로환경요인이 대기질에 미치는 영향을 설명하였다는 데 의의가 있다.

• 한국대기환경학회지
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• 제28권1호
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• pp.94-104
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• 2012

The purpose of this research is to quantify the compliance of on-road emission from a light duty diesel vehicle, based on a comparison to emission regulation standard. $NO_x$, CO and THC emissions were measured using a portable device on a selected real-world driving route with a length of approximately 22 km. On-road measurements were repeated by 10 times on a same route to reflect variability in traffic conditions. A test route was divided into 22 road links with length of 1 km to analyze emission results with higher spatial resolution. The average emissions of $NO_x$, CO and THC over total travel distance, which is approximately 220 km, were quantified to be in compliance with emission regulation standards. Under higher spatial resolution, $NO_x$ concentration exceeded a standard in 92 links out of 220 links. The extended time in stop period and the stop-and-go driving cycle were identified as two important reasons for increased $NO_x$ emissions in observed cases. Heavy traffics showed higher $NO_x$ emissions than free flow. These results indicate that the real-world vehicle emissions might exceed the compliance level associate with traffic conditions. Another interesting observation of this research is that the on-road emission characteristics can be independent to the average speed of road links with higher spatial resolution. Variability in on-road emission might not be fully described by solely relying on an average speed, because variability in traffic conditions and road conditions can influence on real-world vehicle emissions.

• 한국대기환경학회지
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• 제27권4호
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• pp.405-415
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• 2011

The objective of this study was to compare greenhouse gas emissions from road transportation by calculation methods (Tier 1, Teir 2, and Tier 3). Tier 1 based on 2006 IPCC guidelines default emission factor and amount of fuel consumption. The Tier 2 approach is the same as Tier 1 except that country-specific carbon contents of the fuel sold in road transport are used. Tier 2 based on emission factor of guidelines for local government greenhouse gas inventories (Korea Environment Corporation), the fuel consumption per one vehicle, and the registered motor vehicles. The Tier 3 approach requires detailed, country-specific data to generate activity-based emission factors for vehicle subcategories (National Institute of Environmental Research) and may involve national models. Tier 3 calculates emissions by multiplying emission factors by vehicle activity levels (e.g., VKT) for each vehicle subcategory and possible road type. VKT was estimated by using GIS road map and traffic volume of the section. The GHG average emission rate by the Tier 1 was 728,857 $tonCO_2eq$/yr, while Tier 2 and Tier 3 were 864,757 $tonCO_2eq$/yr and 661,710 $tonCO_2eq$/yr, respectively. Tier 3 was underestimated by 10.1 and 20.7 percent for the GHG emission observed by Tier 1 and Tier 2, respectively. Based on this study, we conclude that Tier 2 is reasonable GHG emissions than Tier 1 or Tier 3. But, further study is still needed to accurate GHG emission from Tier 3 method by expanding the traffic survey area and developing the model of local road traffic.

• 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.

• International Journal of Automotive Technology
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• 제7권3호
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• pp.269-276
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• 2006

Running tests on roads were conducted to clarify the influences of road infrastructure, traffic condition and vehicle's emission level to the amount of emission at local roadsides, and to reveal the operation patterns which can reduce the emission peaks. NOx emission peaks of two light duty freight diesel vehicles which have different emission levels were evaluated by using an on-board measurement system. Tests were carried out with various payload conditions and road conditions. As a result many NOx emission peaks were observed when the vehicles were starting or accelerating at intersections. The test vehicle which has higher emission level caused higher frequency and level of NOx emission peaks. Shifting up at lower engine speed in combination with lower acceleration brought out not only reduction of NOx emission peaks level but also of $CO_2$ mass emission.

• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2000년도 추계학술대회 논문집
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• pp.136-138
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• 2000

The vehicle emissions of primary air pollutants are described by the emission factor (EF), defined as the emitted mass (g) of a compound per distance (km) and vehicle. The EF can be determined by exhaust measurements from single vehicles in dynamometric tests. However, the EF of a large number of vehicles has to be measured to obtain the representative results for actual road traffic emissions. Road traffic emissions can also be determined by exhaust measurements of driving vehicles or in tunnel measurements. (omitted)

• 한국도로학회논문집
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• 제18권3호
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• pp.115-125
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• 2016

PURPOSES : This study proposes a methodology to collect data necessary for microlevel emission estimation, such as second-by-second speeds and road grades, and to accordingly estimate emissions. METHODS : To ease data collection for microlevel emission estimation, a vehicle equipped with speed- and location-recording instruments as well as equipment for measuring road geometry was used. As a case study, this vehicle and the proposed methodology were used on a 10-km-long highway in Yongin City, Korea. Emissions from the vehicle during driving were estimated in various microscale driving conditions. RESULTS : Differences in the estimated emission under different microscale driving conditions cannot be ignored. Compared with the estimations obtained when second-by-second data were not considered, CO and NOx emissions were more than threefold higher when considering second-by-second speed; similarly, CO and NOx emission estimations were higher by approximately 10% and 3%, respectively, when considering second-by-second road grade. CONCLUSIONS : The proposed method can estimate vehicle emissions under real-world driving conditions in such applications as road design and traffic policy assessments.

• 소음진동
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• 제6권6호
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• pp.843-849
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• 1996

Locations and emission characteristics of noise source of motor vehicles are great important factors to control the road traffic noise in effective ways. From results of this study on emission characteristics of engine and exhaust noise, we could find that every noise emission of different kind of vehicles has smilar pattern. The main emission locations of engine noise for the front of vehicle became the space between the road surface and bottom of the body and radiator grill, and for the side of vehicle became the space between the road surface and bottom nearby the front wheel. In case of exhaust noise of passenger-car and light truck, all the highest sound intensity level located near surface of road. But it is hard to conclude the height of noise source of driving vehicles with only results of this study. So further studies are needed to check the emission characteristics of noise.