• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.1
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• pp.17-24
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• 2008

This study was performed to estimate non-$CO_2$ greenhouse gases (i.e., GHGs) emission from biomass burning at a local scale. Estimation of non-$CO_2$ GHGs emission was conducted using Landsat TM satellite imagery in order to assess the damage degree in burnt area and its effect on non-$CO_2$ GHGs emission. This approach of estimation was based on the protocol of the 2003 IPCC Guidelines. In this study, we used one of the most severe fire cases occurred Samcheock in April, 2004. Landsat TM satellite imageries of pre- and post-fire were used 1) to calculate delta normalized burn ratio (dNBR) for analyzing burnt area and burn severity of the Samcheok large-fire and 2) to quantify non-$CO_2$ GHGs emission from different size of the burnt area and the damage degree. The analysis of dNBR of the Samcheok large-fire indicated that the total burnt area was 16,200ha and the size of the burnt area differed with the burn severity: out of the total burnt area, the burn severities of Low (dNBR < 152), Moderate (dNBR = 153-190), and High (dNBR = 191-255) were 35%, 33%, and 32%, respectively. It was estimated that the burnt areas of coniferous forest, deciduous forest, and mixed forest were about 11,506ha (77%), 453ha (3%), and 2,978ha (20%), respectively. The magnitude of non-$CO_2$ GHGs emissions from the Samcheok large-fire differed significantly, showing 93% of CO (44.100Gg), 6.4% of CH4 (3.053Gg), 0.5% of $NO_x$ (0.238Gg), and 0.1% of $N_2O$ (0.038Gg). Although there were little changes in the total burnt area by the burn severity, there were differences in the emission of non-$CO_2$ GHGs with the degree of the burn severity. The maximum emission of non-$CO_2$ GHGs occurred in moderate burn severity, indicating 47% of the total emission.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.4
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• pp.280-287
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• 2012

The sources of greenhouse gases (GHG) at Hanyang University Ansan campus, including direct sources, indirect sources, and others, were investigated in order to establish the GHG inventory. Emission of GHG was calculated with the energy use from each source from 2007 and 2009. The indirect emission (56.7%) due to the electricity significantly contributed to total GHG emission. The scenario for the GHG reduction was designed for both campus administration and members. The reduction potential of GHG was simulated from 2007 to 2020 using Long-range Energy Alternatives Planning (LEAP) model. In case of GHG reduction scenario by campus administration, the GHG can be reduced by 63.34 ton $CO_{2eq}/yr$ for stationary combustion in the direct source, by 221.1 ton $CO_{2eq}/yr$ for mobile combustion in the direct source, and by 4,637.34 ton $CO_{2eq}/yr$ for lighting in the indirect source, compared to 2020 Business As Usual (BAU). In case of GHG reduction action scenario by campus members, the reduction potential of GHG was 1293.76 ton $CO_{2eq}/yr$. Overall, the total GHG emissions in 2020 by the both scenarios can be decreased by 24% compared to 2020 BAU.

• Convergence Security Journal
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• v.13 no.3
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• pp.39-46
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• 2013

Recently, the problem of global warming has become a globally important issues. and To solve these problems, has been receiving increasing attention for the Green IT. In these situation, IT techniques are evolving with variety services and hacking techniques. so, it is inevitable to the use of a many and diverse secure system. As a result, Carbon Dioxide emissions are expected to increase. Therefore, in this paper is analyzed the factors of security system's $CO_2$ emissions through Experiments and A case study. and is proved that is reducing $CO_2$ emissions by improving the functional restructuring of the security system. In a future, this paper is expected to serve as a valuable Information for security network design and performance improvements and to reduce Carbon Emissions in the Field of IT.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.378-384
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• 2019

In the food wastewater treatment facilities, the water quality improvement effect and the greenhouse gas emission amount followed by the change in electricity usage through a change of the aeration tank ventilation system were evaluated. also, the amount of greenhouse gas emission followed by the change in electricity usage through the change of the sludge dewatering, storage, transporting method was also evaluated. The total GHG emission from food wastewater treatment facility improvement were divided into direct emissions from the treatment processes and indirect ones from electricity usage. The water quality improvement effect of wastewater treatment plant was found to be 63.3% for BOD removal rate, 42.0% for COD removal rate, 71.0% for SS removal rate and 39.6% for T-N removal rate. and according to the results of calculating output by applying both direct emissions of greenhouse gas (Scope 1) and the indirect emission (Scope 2) of greenhouse gas followed by changes in power consumption. It was estimated that there was a total of 276.0tCO2eq./yr(7.5%) greenhouse gas reduction effect from 3,668.8tCO2eq./yr before improvement to 3,392.8tCO2eq./yr after improvement. In this result is not due to the effects of water quality improvement of emission source, but because the reduction in electricity use has reduced the amount of greenhouse gas emissions.

• Journal of the Society of Disaster Information
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• v.17 no.1
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• pp.165-175
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• 2021

Purpose: The purpose of this study is to quantitatively present the carbon dioxide(CO₂) emission change according to the application of autonomous driving technology at the network level for waste vehicles in the metropolitan area. Method: The target year was set to 2030, and the analysis method estimated the carbon dioxide (CO₂) emissions for each road link through user equilibrium assignment when unapplied scenario. The application scenario performed traffic assignment using route data on the premise that the group was running in accordance with the application of autonomous driving technology to waste vehicles. In addition, the other means estimated the carbon dioxide emissions through user balance allocation by reflecting the results of the waste vehicle allocation. Result: As a result of the analysis, carbon dioxide(CO₂) emissions were found to be reduced by about 56.9ton/day from the national network level, and the Seoul metropolitan area was analyzed to be reduced by about 54.7ton/day. Conclusion: This study quantitatively presented environmental impacts among various social effects that autonomous driving technology will bring, and in the future, development of various analytical methodologies and related studies should be continuously conducted.

• Journal of the Korea Organic Resources Recycling Association
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• v.32 no.1
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• pp.13-19
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• 2024

The objective of this study was to assess the feasibility of a landfill project aimed at reducing greenhouse gas (GHG) from Puerto Cortes Landfill in Honduras ("Project"). The feasibility study involved surveying the status, composition and amount of waste entering the landfill, and projecting GHG emissions from the landfill. A projection of the GHG emissions with the IPCC model and based on the survey results indicated that the period 2027 to 2041 would see a total GHG emission reduction of 506,835 ton-CO₂/year, with a mean yearly GHG emission reduction of 33,789 ton-CO₂, assuming landfill gas collection is implemented, The findings of the study are expected to serve as basic data for deciding about whether and how to proceed with the Project.

• Journal of Climate Change Research
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• v.3 no.3
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• pp.195-209
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• 2012

There are four differentiated levels to quantify the amount of greenhouse gas emissions from a facility, which are Tier 1 to 4 based on the IPCC guidelines. In this study, the emission estimates from all tier levels were calculated to compare their total $CO_2$ emission results among themselves for seven facilities, including three sectors of electricity generation, municipal solid waste incineration, and cement manufacturing for three months between February and May 2011. Generally the measured $CO_2$ emissions by Tier 4 were higher than the calculated $CO_2$ emissions by Tier 3, which had been also observed for the power plants in the USA. It was found out that to obtain more reliable estimation for Tier 3, accurate analysis of the composition of the fuel used should be carried out. It was suggested that further refinement on the administrative guidelines be made to make it more robust.

• Environmental and Resource Economics Review
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• v.15 no.3
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• pp.425-450
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• 2006

The index of energy intensity(energy/GDP) has been a primary policy concern since it can clarify industry sectors which use energy intensively and generate $CO_2$ emission heavily. Although energy intensity index may be suitable for estimating $CO_2$ emission from an isolated industry sector, we need an index for induced $CO_2$ emission since industrial activities are interconnected in terms of input and output. By employing Environmental Input-Output Table 2000, this paper analyses the flow of energy demand and pollutants after first estimating an induced $CO_2$ emissions from various industrial sectors and economic activities. The paper reports higher induced $CO_2$ emissions from industry sectors with larger energy intensity since they produces goods or services retaining relatively considerable environmental load. Furthermore, it is shown that environmental load and $CO_2$ emissions in overall economy are likely increasing when the products of energy intensive industrial sector is used as inputs for less intensive sectors' production process. The result suggests we need consistent policy efforts to reduce energy intensity to lower $CO_2$ emissions.

• 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.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.192-192
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• 2011

교토의정서에서 지구온난화의 원인이 되는 온실가스로 $CO_2$, $CH_4$, $N_2O$, HFCs, PFCs, $SF_6$를 규제하고 있다. 규제하는 6대 온실가스 가운데 $CO_2$가 가장 대표적이며, 우리나라의 연료연소에 의한 $CO_2$ 배출량은 세계 10위로 기후변화 진행속도는 세계 평균속도보다 빠르게 진행되고 있다. 이러한 기후변화에 대응하기 위하여는 온실가스 배출로 인한 DB구축 연구가 선행되어야 하며, 산림부분에 있어서는 연료의 열적특성 구명 연구가 극도로 미진한 국내현실에서 기초 data 확보를 위한 연구가 시급한 실정이다. 따라서, 본 연구에서는 산불발생 시 온실가스 배출량의 DB를 구축하기 위하여 산불발생 시 배출되는 탄소배출량을 예측하고자 산림 가연물의 연소실험을 수행 하였다. 연소실험은 산림 연료 가운데 지표연료 10가지(소나무낙엽, 굴참나무낙엽, 소나무솔방울, 밤나무밤송이껍질, 방아풀, 주름조개풀, 칡, 엉겅퀴, 김의털, 고비)를 대상으로 콘칼로리미터 장비를 이용하여 이산화탄소와 일산화탄소 배출량을 분석하였다. 탄소배출량 실험에 앞서 지표연료들의 함수율을 측정한 결과, 10가지 지표연료 가운데 고사한 연료(낙엽, 솔방울, 밤송이)는 9~24% 정도, 생연료인 초본류 6가지는 181~484% 정도인 것으로 나타났으며, 솔방울과 밤송이의 경우 9~10%로 가장 수분을 적게 함유하고 있음을 알 수 있었다. 탄소배출량 분석 결과, 50g 중량에 대한 10가지 지표연료들의 이산화탄소 총배출량은 28~98g 정도, 일산화탄소 총배출량은 0.76~4.08g 정도 배출하는 것으로 나타나 연료별 차이를 보였으며, 특히, 고사한 연료와 생연료의 탄소배출량 차이는 큰 것으로 나타났다. 일산화탄소 총배출량은 고사한 연료(소나무낙엽, 굴참나무 낙엽, 소나무 솔방울, 밤나무 밤송이)는 3.24~4.08g 정도, 생연료 초본류 6가지(방아풀, 주름조개풀, 칡, 엉겅퀴, 김의털, 고비)는 0.76~2.73g 정도 배출하는 것으로 나타났다. 이산화탄소 총배출량은 함수율이 현저히 낮은 4가지 연료(소나무 낙엽, 굴참나무 낙엽, 소나무 솔방울, 밤나무 밤송이 껍질)들은 52~98g 정도, 함수율이 높은 6가지 초본류는 28~48g 정도의 이산화탄소를 배출하는 것으로 나타났다. 따라서, 고사한 연료인 소나무 낙엽, 굴참나무 낙엽, 소나무 솔방울, 밤나무 밤송이는 초본류 보다 상대적으로 이산화탄소와 일산화탄소 배출량이 많은 것으로 나타났으며, 특히, 소나무 솔방울은 가장 많은 이산화탄소와 일산화탄소를 배출하는 것으로 나타났다. 상대적으로 방아풀과 주름조개풀은 각각 28g과 35g으로 이산화탄소 배출량이 작은 것으로 나타났다. 따라서, 산불발생 시, 소나무의 솔방울은 10가지 지표연료 가운데 상대적으로 많은 이산화탄소와 일산화탄소를 배출할 것으로 사료된다.