• Asian Journal of Atmospheric Environment
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• v.9 no.2
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• pp.146-157
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• 2015

Emissions of ozone precursors ($NO_x$ and VOCs) and photochemical ozone creation potentials (POCPs) of VOC emission sources were investigated in the largest port city (i.e., Busan), Korea during the year 2011. This analysis was performed using the Clean Air Policy Support System (CAPSS) national emission inventory provided by the National Institute of Environmental Research (NIER), Korea. For $NO_x$, the emissions from off-road mobile sources in Busan were the most dominant (e.g., $31,202ton\;yr^{-1}$), accounting for about 60% of the total $NO_x$ emissions. The emission from shipping of off-road mobile sources (e.g., $24,922ton\;yr^{-1}$) was a major contributor to their total emissions, amounting to 47% of the total $NO_x$ emissions due to the port-related activities in Busan. For VOCs, the emission source category of solvent usage was predominant (e.g., $36,062ton\;yr^{-1}$), accounting for approximately 82% of the total VOC emissions. Out of solvent usages, the emission from painting was the most dominant ($22,733ton\;yr^{-1}$), comprising 52% of the total emissions from solvent usages. The most dominant VOC species emitted from their sources in Busan was toluene, followed by xylene, butane, ethylbenzene, n-butanol, isopropyl alcohol, and propane. The major emission sources of toluene and xylene were found to be painting of coil coating and ship building, respectively. The value of POCP for the off-road mobile source (61) was the highest in ten major activity sectors of VOC emissions. Since the POCP value of ship transport of off-road mobile source (72) was also high enough to affect ozone concentration, the ship emission can play a significant role in ozone production of the port city like Busan.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.1
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• pp.72-82
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• 2008

Benzene is a very harmful and toxic compound known as human carcinogen by all routes of exposure. Owing to the risky feature of benzene, several countries such as Japan, UK and EU have established the ambient air quality standard and protect from that risk of it. Korea also has designated it as one of the criteria air pollutants and established the concentration limit ($5\;{\mu}g/m^3$) in the air and is going to apply the standard from 2010. Benzene is emitted from various sources such as combustion plants, production processes, waste treatment facilities and also automobiles. Mobile source is known as one of the major emission sources of benzene. In this study, we estimated the domestic emissions of benzene from mobile source and compared the results with those of advanced countries. Mobile source was divided into 2 categories, Le., on-road source and non-road source. The total emissions of benzene from mobile source were estimated as 3,106 tons/yr and 1,612 tons/yr was emitted from on-road source and 1,494 tons/yr was from non-road source. Emission ratio of benzene from on-road source showed that 80.0% was from passenger cars, 10.1% was from taxis, 7.2% was from light-duty vehicles, 2.5% was from heavy-duty vehicles and 0.2% was from buses. In the case of non-road source, the distribution showed that 66.3% was from construction machineries, 14.5% was from locomotives, 11.7% was from ships, 7.1% was from agriculture equipments and 0.5% was from aircrafts. The cold-start emissions were estimated as 942 tons/yr and this value was almost 1.5 times greater than that for hot engine emissions (608 tons/yr). In addition, the fuel-based distribution was 65.9%, 31.1% and 2.8% from gasoline, LPG and diesel vehicles, respectively. The emission ratio from mobile source occupied 65% and 30% of total benzene emissions in USA and UK, respectively. In case of Korea, the emission ratio of benzene from mobile source occupied 29% (15% from on-road source, 14% from non-road source) which showed similar value with UK.

• Environmental Engineering Research
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• v.25 no.3
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• pp.366-373
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• 2020

The autonomous vehicles (AVs) could make a positive or negative impact on reducing mobile emissions. This study investigated the changes of mobile emissions that could be caused by large-scale adoption of AVs. The factors of road capacity increase and speed limit increase impacts were simulated using a conceptual modeling approach that combines a hypothetical speed-emission function and a traffic demand model using a virtual transportation network. The simulation results show that road capacity increase impact is significant in decreasing mobile emissions until the market share of AVs is less than 80%. If the road capacity increases by 100%, the mobile emissions will decrease by about 30%. On the other hand, driving speed limit increase impact is significant in increasing mobile emissions, and the environmentally desirable speed limit was found at around 95 km/h. If the speed limit increases to 140 km/h, the mobile emissions will increase by about 25%. This is because some vehicles begin to bypass the congested routes at high speeds as speed limit increases. Based on the simulation results, it is clear that the vehicle platooning technology implemented at reasonable speed limit is one of the AV technologies that are encouraging from the environmental point of view.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.4
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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.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.3
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• pp.188-195
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• 2009

Generally. mobile sources of air pollution were classified in on-road and non-road. Due to increased registration number of construction equipment in Korea. updated emission factors for non-road mobile sources, such as construction machinery. should be developed. NONROAD model of U.S. EPA already has introduced transient adjustment factors and sulfur adjustment factors for emission factors of diesel powered engine. In addition to this. European Environment Agency (EEA) has proposed emission factors for off-road machinery including several types of construction equipment. In this study. six types of construction equipment, such as excavator. forklift, loader, crane, roller and bulldozer, were studied to estimate emission factors based on total registration status in Korea. Total 445 construction equipments between 2004 and 2007 model year were tested with KC1-8 mode and air pollutants (CO, THC, $NO_x$, and PM) were measured. After statistical estimation and calculation, emission factors for CO, THC, $NO_x$, and PM for excavator, forklift, loader, crane, roller and bulldozer were provided and compared with previous emission factors. Moreover, updated emission factors for six types of construction equipment in this study were verified after comparison with emission factors of U.S. EPA. Finally, estimated emission amounts of four air pollutants were suggested according to six types of construction equipment.

• Journal of the Society of Disaster Information
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• v.13 no.1
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• pp.96-105
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• 2017

Global warming, mainly caused by CO2, is one of the on­going cataclysms of the human race. The nation­wide policy to reduce greenhouse gases (GHG) has been enforced, for which it is crucial to estimate reliable GHG emissions. The unit load of road­section CO2 emission (URSCE) is a prerequisite for the evaluation of GHG emissions from road mobile source, and it is mainly computed using vehicular velocity source. Unfortunately, there is real­world limitations to collect and analyse representative speed data for nation­wide road network. To tackle this problem, a method for the evaluation of URSCE, proposed in this study, is based on a disaggregated way using big GPS vehicle data. The method yields more accurate URSCE than an current aggregated data based approach and can be directly employed for nation­wide road systems.

• 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.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.86-87
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• 2021

As non-road mobile pollutants such as construction equipment are emerging as the main cause of air pollutants emission, construction equipment regulations are gradually strengthening. Research was conducted by correcting the emission coefficient to calculate and predict air pollutant emissions of construction equipment, but it did not reflect site variables such as field and equipment conditions that affect actual emissions. This study derived an Artificial Neural Network emission prediction model based on the actual emission data of excavators and trucks measured at the site and proposed a platform to predict the emission of air pollutants at the site according to the working size and conditions. Through this, it is possible to establish an eco-friendly process plan using a model from the construction plan.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.5
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• pp.269-278
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• 2016

In order to improve air quality in the Seoul Metropolitan Area (SMA), the "Special Act on Seoul Metropolitan Air Quality Improvement" has been enforced since 2005. The strategy has resulted in some reduction of air pollution, but there has not been much research into the quantitative impact analysis of each separate preventive countermeasure. Therefore, we analyzed nitrogen oxide reduction resulting from implementation of the emission control plan for on-road mobile sources. The MM5-SMOKE-CMAQ model system was employed for air quality prediction. Reduced $NO_x$ emissions for SMA was 16,561 ton, 4.7% of reduction rate, in 2007. One countermeasure, tighter acceptable standards for manufacturing vehicles, dominated other countermeasures for effective $NO_x$ emission control. Large spatial differences in reduced emissions, those for Seoul being twice that of Incheon and Gyeonggi, showed greater $NO_x$ emission reduction impact in the heart of the metropolitan complex. The $NO_2$ concentration decreased by 0.60 ppb (2.0%), 0.18 ppb (1.5%), and 0.22 ppb (1.7%) in Seoul, Incheon, and Gyeonggi, respectively. Concentration decreases in spring and winter were larger, 1.5~2.0 times, than summer and fall. However, the $NO_2$ reduction impact did not correspond directly to local $NO_x$ emission controls in the city area because of the natural flow and dispersion, both urban and downwind.

• International Journal of Highway Engineering
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• v.15 no.4
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• pp.167-175
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• 2013

PURPOSES : The objective of this study is to investigate the capability of the combined model of traffic simulation, emission and air dispersion models on the impact analysis of air quality of mobile sources such as vehicles. METHODS : The improvement of the quality of life brings about the increasing interest of the public environment. Many endeavors including the travel demand management, the application of the state-of-the-art ITS technologies, the promotion of eco-friendly vehicles have been tried in transportation area to reduce the modal emissions. Especially, it is expected that the increasing number of eco-friendly vehicles in the road network would be able to reduce the pipe-tail emissions tremendously. From this perspective, we have performed a study on the impact analysis of the popularization of the eco-friendly vehicle in the place of the fossil fuel energy powered vehicles on the surrounding air quality using the combined framework of microscopic traffic simulation, emission and air dispersion model. RESULTS : The combined model successfully captured the effect of moving to the eco-friendly vehicles on the air quality, and the results showed that the increasing usage of eco-friendly vehicles can improve the surrounding air quality tremendously and that the air dispersion model plays a crucial role in the investigation of the air quality change around the main corridor. CONCLUSIONS : This study demonstrated the capability of the combined model showing the spatio-tempral change of emission concentration.