• Journal of Environmental Health Sciences
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• v.30 no.3
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• pp.293-299
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• 2004

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 characteristics 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are compiled using passive data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled.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 is towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this study, a model of vehicle emission calculation by using real-time traffic data was studied. Traffic data, which are required on a street-by-street basis, is obtained from induction loops of traffic control system. It is possible that characteristics of hourly air pollutants emission rates is obtained from hourly traffic volume and speed. An emission rates model is allocated with a high resolution space by using geographic information system (GIS). Vehicle emission model was developed with a high resolution spatial, gridded and hourly emission rates.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2008.10a
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• pp.489-490
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• 2008

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.40-52
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• 2011

In this study, $CO_2$ emission quantities by spatial characteristics using GIS were investigated for building a $CO_2$ emission inventory. Eventually, this study provides the guidelines to build the urban spatial structure for reducing greenhouse gas and contributes to the transition to environmental friendly green city. The attribute data for GIS were energy (electricity and gas) usage in the city of Daegu for 2009 and used for Tier 1 as suggested by the IPCC guideline to estimate amount of $CO_2$ emission. The spatial data were built based on land use types categorized by building purposes with connecting building registers to cadastral maps for Daegu city. Spatial $CO_2$ emission quantities could be calculated by combining $CO_2$ emission inventory for energy and GIS. Also, $CO_2$ emission characteristics were different by land use types.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2008.10a
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• pp.190-191
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• 2008

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.5
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• pp.369-381
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• 2009

The objective of this study was to simulate surface air pollutants and to examine reliability of mobile emission for CMAQ system using an observation-based approach in the Seoul Metropolitan Area. Accurate assessment of emissions from mobile source is one of the most debatable parts in the entire emissions inventory process. For this study, we evaluated the official emission inventories of Volatile Organic Compounds (VOCs) and nitrogen oxides ($NO_x$) using an observation-based approach. In this paper, we achieved VOCs/CO and $NO_x$/CO ratios derived from ambient measurements taken from June to August of 2005 in early morning (07:00~08:00). And we compared them with those derived from the emission inventory. Based on these ratios and on the assumption that official inventory of CO emissions is reasonably accurate, mobile emissions of $NO_x$ seem to be slightly overestimated and VOCs emissions significantly underestimated. The results of simulations using modified emission of mobile source were in closer agreement with the observation results except NO. Predicted NO values based on revised $NO_x$ emissions were considerably lower than the observed values. Using modified emission inventories brings the modeled values into closer agreement with observed ozone levels in Seoul. Especially in case of CO, $NO_x$ and VOCs emission, the modified values were suitable for simulating ozone levels in Seoul and Gyeonggi. However, ozone values predicted using the modified emissions were higher than the observed and predicted values based on original emissions. According to the 95 percentile ozone concentrations, emission revised by CO, $NO_x$ and VOCs from mobile source was the best for predicting high concentration.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.2
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• pp.306-320
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• 2018

Emission inventory is the essential component for improving the performance of air quality forecasting system. This study evaluated the simulated daily mean $PM_{2.5}$ concentrations in South Korea and China for 1-year period (Sept. 2016~Aug. 2017) using air quality forecasting system which was applied by the emission inventory of E2015 (predicted CAPSS 2015 for South Korea and KORUS 2015 v1 for the other regions). To identify the impacts of emissions on the simulated $PM_{2.5}$, the emission inventory replaced by E2010 (CAPSS 2010 and MIX 2010) were also applied under the same forecasting conditions. These results showed that simulated daily mean $PM_{2.5}$ concentrations had generally suitable performance with both emission data-sets for China (IOA>0.87, R>0.87) and South Korea (IOA>0.84, R>0.76). The impacts of the changes in emission inventories on simulated daily mean $PM_{2.5}$ concentrations were quantitatively estimated. In China, normalized mean bias (NMB) showed 5.5% and 26.8% under E2010 and E2015, respectively. The tendency of overestimated concentrations was larger in North Central and Southeast China than other regions under both E2010 and E2015. Seasonal differences of NMB were higher in non-winter season (28.3% (E2010)~39.3% (E2015)) than winter season (-0.5% (E2010)~8.0% (E2015)). In South Korea, NMB showed -5.4% and 2.8% for all days, but -15.2% and -11.2% for days below $40{\mu}g/m^3$ to minimize the impacts of long-range transport under E2010 and E2015, respectively. For all days, simulated $PM_{2.5}$ concentrations were overestimated in Seoul, Incheon, Southern part of Gyeonggi and Daejeon, and underestimated in other regions such as Jeonbuk, Ulsan, Busan and Gyeongnam, regardless of what emission inventories were applied. Our results suggest that the updated emission inventory, which reflects current status of emission amounts and spatio-temporal allocations, is needed for improving the performance of air quality forecasting.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.05a
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• pp.55-56
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• 2018

In order to construct an efficient monitoring system for major port cities in Korea, the first step to build and manage related laws and institutional infrastructure with strengthen the cooperation of the relevant agencies, regional port authorities, and port corporations. Second, for the management of air pollutants emitted by ports, a management system should be established through systematic inventory source inventory and real-time monitoring system. Third, active countermeasures should be established to reduce the emission of air pollutants by sources such as ships, harbor equipment, and trucks. This will improve the air quality of major port cities and move them to clean port cities.

• 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.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1371-1373
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• 2008

Recently, the reduction of greenhouse gas (GHG) is the most important international issue. In order to control efficiently GHG emissions and reduction, it is essential to establish GHG inventory preferentially. The aim of this study was to establish the GHG inventory of Korean railroad. The GHG sources were divided into direct and indirect emissions. The GHG released from the operation of rolling stocks was classified according to operating line and the kind of car. Finally, the GHG emission of Korean railroad can be managed systematically using this GHG inventory.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.3
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• pp.231-245
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• 2002

A better knowledge of emission inventories can serve several important functions such as provision of public information, identification of primary sources, assessment of temporal and spatial trend, and analysis for national modelling studies. The purpose of this paper is to propose the new air emission source categories on the basis of the Korea Standard Industrial Classification. Hence, the paper focuses on reviewing and comparing the air emission sources categories of USEPA, and EU. The new emission source categories compose Tiers 1, 2, and 3. For Tier 1, there are 14 categories; fuel combustion-utilities, industries, and heating and others, chemical and allied product manufacturing, metals processing, and petroleum and related industries, etc. Tier 2 consists of small categories classified minutely in Tier 1. Tier 3 connects the categories of Tier 2 with the Korea Standard Industrial Classification.