• KIEAE Journal
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• v.8 no.4
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• pp.19-27
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• 2008

The carbon dioxide is brought from the energy consumption and regarded as a criteria material to estimate the Global Warming Potential. Building shares about 30% in national energy consumption and affects to environment as much as the energy consumption. But there is not enough data to forecast the amount of the carbon dioxide during the maintenance stage. Various factors are related with the energy consumption and carbon dioxide emission such as the physical area, the building exterior area, the maintenance type and location. Among these factors, the building carbon-dioxide emission can be estimated by the overall building characteristics such as the maintenance area, the number of household, the heating type, etc., The physical amount such as the thickness of the insulation and window infiltration could explained the limited scope and might not be use to estimate the total carbon-dioxide emission energy because the each value could not include or represent the overall building. In this paper, it provided the estimation model of the carbon-dioxide emission, explained by the overall building characteristics. These factors are shown as the maintenance area, no. of household, the heating type, the volume of the building, the ratio of the window to wall area etc., For providing the estimation model of th carbon-dioxide emission, it conducted the corelation analysis to filter the variables and suggested the estimation model with the power model and multiple regression model. Most of the model have a good statistics and fitted in the curve line.

• Journal of Korean Society for Atmospheric Environment
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• v.14 no.5
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• pp.499-506
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• 1998

Recently almost wastes except recycled garbage are dumped into landfill site in Korea. Landfills are significant compounds (NMOCS) are produced. NMOCS include reactive volative organic compound (VOC) and hazardous air pollutants. LAEEM (Landfill Air Emissions Estimation Model) developed by Control Technology Center, V.S. EPA is used to estimate a mount of landfill gas from all landfills. As the result, landfill gas 4,121,000 ton, carbon dioxide 2,951,000 ton, methane 1,1120,000 ton are estimated as emissions from all landfills in Korea.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.4
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• pp.387-396
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• 2003

A field study was conducted during the summer time of 2002 to determine compositions of volatile organic compounds (VOCs) emitted from vehicles and to develop source emission profiles that is applied to CMB model to estimate the source contribution of certain area. Source emission profile is widely used for the estimation of source contribution by the chemical mass balance model and have to be developed applicable for the target area of estimation. This study was aimed to develop source emission profile and estimation of source contribution of VOCs after application of the chemical mass balance (CMB) receptor model. After considering the emission inventory and other research results for the VOCs in Seoul, Korea, the sources like vehicle emission (tunnel), gas station (gasoline, diesel), solvent usage (painting operation, dry cleaning, graphic art), and gas fuels were selected for the major VOCs sources. Furthermore, ambient air samples were simultaneously collected from 09:00 to 11:00 for four days at eight different official air quality monitoring sites as receptors in Seoul during summer of 2001. Source samples were collected by canisters, and then about seventy volatile organic compounds were analyzed by gas chromatography with flame ionization detector (GC/FID). Based on both the developed source profiles and the database of the receptors, CMB model was intensively applied to estimate mass contribution of VOCs sources. Examining the source profile from the vehicle, the portion of alkanes of VOCs was highest, and then the portion of aromatics such toluene, m/p-xylene were followed. In case of gas fuel. they have their own components; the content of butane, propane, ethane was higher than any other component according to the fuel usage. The average of the source apportionment on VOCs for 8 sites showed that the major sources were vehicle emission and gas fuels. The vehicle emission source was revealed as having the highest contribution with an average of 49.6%, and followed by solvent with 21.3%, gas fuel with 16.1%, gasoline with 13.1%.

• International Journal of Control, Automation, and Systems
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• v.5 no.1
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• pp.43-50
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• 2007

Reheating furnace is an essential facility of a rod mill plant where a billet is heated to the required rolling temperature so that it can be milled to produce wire. Although it is very important to obtain information on billet temperatures, it is not feasible during furnace operation. Consequently, a billet temperature profile should be estimated. Moreover, this estimation should be done within an appropriate time interval for an on-line application. In this paper, a billet heat transfer model based on 2D FEM(Finite Element Method) with spatially distributed emission factors is proposed for an on-line billet temperature estimation and also a measurement is carried out for two extremely different furnace operation patterns. Finally, the difference between the model outputs and the measurements is minimized by using a new optimization algorithm named uDEAS(Univariate Dynamic Encoding Algorithm for Searches) with multi-step tuning strategy. The obtained emission factors are applied to a simulation for the data which are not used in the model tuning for validation.

• Journal of Korean Society of Transportation
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• v.31 no.6
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• pp.90-105
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• 2013

There are lots of variations on speed, acceleration and engine power during vehicle driving. It is well known that Green House Gas emissions by these dynamic driving properties are not precisely estimated by the average speed based emission estimation model which has been currently used in Korea. MOVES are selected as an appropriate transferable model among Micro-level emission estimation models. Based on MOVES, a novel emission estimation model can be used in Korea is developed. In this model, MOVES concept of emission estimation method and the MOVES method of estimating the Micro-level emission rate map is adopted. The results from the proposed model were compared with those from the average speed based emission model. The comparison results show the estimated base emission maps are good to be applied in Korea, but needed to be adjusted to consider the vehicle size differences between the two countries. Therefore, the factors for calibrating vehicle size difference were calculated and applied to acquired the micro-level emission maps for the Korean standard vehicle types.

• Journal of the Korean Institute of Gas
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• v.7 no.2 s.19
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• pp.7-13
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• 2003

Abstract This paper presents new emission mechanism and emission estimation model in volatile organic compounds(VOCs) emission sources. Also classifies applicable emission reduction techniques and presents new economical evaluation method for each techniques. We ultimately developed VEER(VOCs Emission Estimation and Reduction) software, which is backed by above mentioned model, emission source DB, Chemical properties DB, meteorological DB, and emission factor DB. With VEER, users in enterprise, central government and local self-governing body can get reliable emission results easily, and choose suitable emission reduction techniques.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.3
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• pp.114-128
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• 2013

Greenhouse gas emissions have been an important issue in different countries because of their effects on global warming. The government has to organize greenhouse gas reduction measures suitable to regional characteristics by establishing annual implementation plans and comprehensive policies based on the UNFCCC. The transportation sector is one of the major contributors of air pollution; hence increasing need to estimate current and future traffic emissions precisely. Under these circumstances, a number of emission models have been developed recently. However, current methods of estimation cannot carry out effective analyses because it does not reflect vehicle movement characteristics. This study aims to present a new method for calculating road traffic emissions in Goyang city. A travel demand model is utilized to carry out GHG emission estimates according the traffic data (fleet composition, vehicle kilometers travelled, traffic intensity, road type, emission factors and speed). This study evaluates two approaches to estimate the road traffic emissions in Goyang City: Pollution-Emis and the Handbook of Emission Factors for Road Transport (HBEFA v.3.1) which is representative of the "average speed" and the "traffic situation" model types. The evaluation of results shows that the proposed emission estimation method may be a good practice if vigilant implementation of model inputs is observed.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.603-612
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• 2022

The study aims were to evaluate a machine-learning, algorithm-based, forest biomass-estimation model to estimate subnational forest biomass and to comparatively analyze REDD+ forest reference emission levels. Time-series Landsat satellite imagery and ESA Biomass Climate Change Initiative information were used to build a machine-learning-based biomass estimation model. The k-nearest neighbors algorithm (kNN), which is a non-parametric learning model, and the tree-based random forest (RF) model were applied to the machine-learning algorithm, and the estimated biomasses were compared with the forest reference emission levels (FREL) data, which was provided by the Paraguayan government. The root mean square error (RMSE), which was the optimum parameter of the kNN model, was 35.9, and the RMSE of the RF model was lower at 34.41, showing that the RF model was superior. As a result of separately using the FREL, kNN, and RF methods to set the reference emission levels, the gradient was set to approximately -33,000 tons, -253,000 tons, and -92,000 tons, respectively. These results showed that the machine learning-based estimation model was more suitable than the existing methods for setting reference emission levels.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.2D
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• pp.103-110
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• 2012

This study presents O/D based emission estimation model and methodology under cold- and hot-start conditions. Contrasting with existing link-based model, new model is able to estimate cold-start emissions with actual traffic characteristics. The results of the case study with new model show similar amount of emission with existing model under hot-start conditions, but five times much more than existing model under cold-start conditions. The annual social benefit estimated by this model is 56.2 hundred million won, which is 48% higher than the result from existing model. It means current green transportation policies are undervalued in terms of air quality improvement. Therefore, New model is expected to improve the objectivity of air quality evaluation results regarding green transportation policies and be applied in various transportation-environment policies.

• 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.