• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2006.11a
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• pp.275-280
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• 2006

The protection of the environment is one of today's key demanding international activities and interests. All of aspects including industry, economy and society should be changed into environmental friendly industries. The building is not exception in this trend. What is not generally realized is that building, in the lifecycle of construction, use and demolition, account for large construction, not considered with environment impact and conservation in the lifecycle. Expecially, the construction materials and components used in the construction stage has much embodied energy. And much $CO_2$ emit on the production of the construction material and component. The energy use and $CO_2$ emission would continuously diminish the limited natural resources and impact the environment such as ozon layer destruction. In this paper, it studied the estimation of the amount of energy use and $CO_2$ emission in the building construction stage, it would provide the estimation process and applied with the multifamily housing.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.22 no.3
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• pp.135-149
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• 2017

Microplastics are fractions of plastics less than 5 mm in size and can be divided into artificially manufactured primary microplastics and physically or chemically decomposed secondary microplastics. In this study, the emission source of microplastics made by the human activities is defined as the primary source of microplastics. And the primary sources of microplastics were summarized by using the literature and the emission potential of each source was estimated. As a result, this study showed that 63,000 to 216,000 ton/year of microplastics were discharged into the environment. Among primary sources, transport, tyre dust, and laundry were the major primary sources.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.1-20
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• 2022

As unmanned aerial vehicle (UAV) technology grew in popularity over the years, it was introduced for air quality monitoring. This can easily be used to estimate the sidewalk emission concentration by calculating road traffic emission factors of different vehicle types. These calculations require a simulation of the spread of pollutants from one or more sources given for estimation. For this purpose, a Gaussian plume dispersion model was developed based on the US EPA Motor Vehicle Emissions Simulator (MOVES), which provides an accurate estimate of fuel consumption and pollutant emissions from vehicles under a wide range of user-defined conditions. This paper describes a methodology for estimating emission concentration on the sidewalk emitted by different types of vehicles. This line source considers vehicle parameters, wind speed and direction, and pollutant concentration using a UAV equipped with a monocular camera. All were sampled over an hourly interval. In this article, the YOLOv5 deep learning model is developed, vehicle tracking is used through Deep SORT (Simple Online and Realtime Tracking), vehicle localization using a homography transformation matrix to locate each vehicle and calculate the parameters of speed and acceleration, and ultimately a Gaussian plume dispersion model was developed to estimate the CO, NOx concentrations at a sidewalk point. The results demonstrate that these estimated pollutants values are good to give a fast and reasonable indication for any near road receptor point using a cheap UAV without installing air monitoring stations along the road.

• Proceedings of the KSR Conference
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• 2001.10a
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• pp.392-397
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• 2001

As the air pollution caused by diesel vehicles goes worse, so non-road vehicles exhaust gas standard is strict in an foreign countries. In this paper, we calculate the amount of emission rates from Korean railroad lines and train kinds. Air pollutants emissions are calculated using by US EPA baseline in-use emission rates which is divided line-haul and switch mode. The calculated HC emissions on the railroad diesel vehicles are 1,209.1 t from Korean railroad lines.

• Journal of Korean Society of Transportation
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• v.34 no.2
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• pp.180-190
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• 2016

Atmospheric pollutants such as Nitrogen Oxides(NOx), Carbon Monoxide(CO), Carbon Dioxide($CO_2$), Particulate Matter(PM) and Hydrocarbons(HC) come from vehicle exhaust gases. Emission curves based on average travel speeds have been employed for estimating on-road emissions as well as evaluating environmental impacts of transportation plans and policies in Korea. Recently, there is a growing interest in estimation methods of vehicle emissions considering relationship between vehicle dynamic driving characteristics and emissions, and incorporating such emission estimators into traffic simulation models. MOVES Lite, a simplified version of MOVES, is one of the estimation methods. In this study, the authors performed a study to develop an adaptable version of MOVES Lite for Korea, called MOVES Lite-K. Vehicle types, driving characteristics, emission rates, and emission standards of Korea were reflected in MOVES Lite-K. The characteristics of emission calculation of MOVES Lite-K and NIER emission curves were compared and the adaptability of MOVES Lite-K were examined.

• Journal of Environmental Impact Assessment
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• v.9 no.4
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• pp.257-269
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• 2000

This study is to investigate the methodology and applicability on emission control by both MECHANICAL Model and Fugitive Dust Model (FDM) through the comparison of field measurement data and calculated data. Comparing to the method of AP-42 emission fector on the production of flying dust the MECHANICAL Model was proved to be more applicable to the calculation emission rate on the various dust emission conditions on a unpaved road. The seperate calculation on annual mean emission amount and a 24working hours amount was undertaken for the easy management of fugitive dust. Dust concentration predicted by FDM is similar with a measurement value.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.3
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• pp.281-290
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• 2004

The main purpose of this study was to characterize the air pollutants emission factors in electric power plant (EPP) using fossil fuels. The electric power plant is a major air pollution source, thus knowing the emission characteristics of electric power plant is very important to develop a control strategy. The major air pollutants of concern from EPP slacks are particulate matter (PM), sulfur oxides (SOx), nitrogen oxides (NOx), carbon monoxide (CO) and heavy metals. Throughout the study, the following results are estimated - PM : 8.671E-05 ∼ 8.724E+01 PM emission (kg) per fuel burned (ton) - SOx : 4.149E-04∼7.877E+01 SOx emission (kg) per fuel burned (ton) - NOx 1.578E-02∼9.857E+00 NOx emission (kg) per fuel burned (ton) - CO : 3.800E-04∼1.291E+00 CO emission (kg) per fuel burned (ton) - Hg : 1.220E+01∼3.108E+02 Hg emission (mg) per fuel burned(ton) From the statistical analysis by Wilcoxon signed ranks test between the emission factors of ours and U.S. EPA's, we can yielded that : p 〉0.05.

• Journal of Climate Change Research
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• v.5 no.3
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• pp.199-208
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• 2014

According to "IPCC guide line for national greenhouse gas inventories" each country should develop the 'Country-specific emission factor' and apply it to estimate greenhouse gases emissions from landfill. It could reflect properties of country and make estimation more accurate. For that accuracy, developed country-specific emission factor should be assessed and be verified consistently. Developed emission factors should be assessed in terms of Representative, Emission Property, Accuracy and Uncertainty, but there is no study about weighted assessment factors under each emission variable. This study do survey targeting public officials, professors and other experts for Analytical Hierarchy Process(AHP), mostly use to make decisions, to weight assessment factors. We investigated the weighted values per Emission factor for Representative, Emission property, Accuracy and Uncertainty on AHP survey, and Representative factor was the highest, and then in the order of Emission property (0.26), Accuracy(0.22), Uncertainty (0.15).

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.7
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• pp.187-195
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• 2019

In December 2015, The Paris Agreement was adopted to undertake ambitious efforts to combat climate change. Korean government announced its goal of reducing the country's greenhouse gas emissions by up to 37% below business as usual projections by 2030 in 2015. The purpose of this study was to set up the calculation methodology of GHG emission($CO_{2e}$) in building sector and to estimate the annual GHG emission in building sector based on national energy consumption statistic. The GHG emission from buildings is about 135.8 million ton $CO_{2e}$ as of 2015, taking up about 19.6% of Korea's entire emission and is about 144.7 million ton $CO_{2e}$ in 2017. The GHG emission of building sector is increasing at annual rate of 2.0% from 2001 to 2017. The GHG emission from electricity consumption in buildings is 91.8 million ton $CO_{2e}$ in 2017, is the highest $CO_2$ emission by energy source. The results show that the intensity of GHG emission of residential building sector is $40.6kg-CO_{2e}/m^2{\cdot}yr$ and that of commercial building sector is $68.4kg-CO_{2e}/m^2{\cdot}yr$.

• Journal of Environmental Policy
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• v.12 no.4
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• pp.45-69
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• 2013

This study estimates baseline greenhouse gas emissions from transport sector when a new town is developed. It has adopted a general greenhouse gas estimation model developed by Schipper, celine, Roger(2000) for the estimation, and showed how various transport related statistics can be utilized in detail. Particularly, it has produced unit greenhouse gas emission factor per vehicle types, vehicle-km, and trip-km. To evaluate effects of greenhouse gas reduction policies, it has calculated how much emissions will be reduced from bicycle promotion. It has turned out that about 369 thousand tons of carbon dioxide will be emitted from transport sector once the 1st Geomdan New Town is developed in Incheon metropolitan city. If the policy of bicycle promotion can attract people to use bicycle as much as 5% of total trips, then it can reduce about 1,869 tons of carbon dioxide.