• Title/Summary/Keyword: CO2 Emission

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CO2 EMISSION MEASURING METHODOLOGY DEVELOPMENT FOR ACCURACY IMPROVEMENT OF CO2 EMISSION OF CONSTRUCTION EQUIPMENT

  • Won-Suk Jang;Sun-Chan Bae;Sang-Dae Park;Suk-Hyun Kwon;Byung-Soo Kim
    • International conference on construction engineering and project management
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    • 2013.01a
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    • pp.204-208
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    • 2013
  • CO2 emission makes up more than 80% of whole green gas. Therefore CO2 is recognized as the main culprit of global warming. IPCC (Intergovernmental Panel on Climate Change) is advising the 3 methods measuring CO2 emission. TIER1 is measured CO2 emission by criteria the energy consumption, TIER2 measure by criteria the emission factor according to the emission control technique each kind of vehicle, TIER3 is measured by criteria the distance each kind of vehicle. Currently, the most of CO2 emission measurement is used by TIER1. But it is not standardized that CO2 emission measurement method have the factor as work condition each distance. Specially, it is not suggest that methodology has the condition changing load of equipment according to site condition and the same position work as construction equipment. So, this study is suggested the CO2 emission measurement methodology of construction equipment.

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The Analysis of CO2 Emission Assessment in Concrete with Smart Blast Furnace Slag (스마트 고로슬래그미분말 혼입 콘크리트의 CO2 배출량 평가에 관한 연구)

  • Kim, Tae-Hyoung;Tae, Sung-Ho;Ha, Sung-Kyun;Park, Jung-Hoon;Roh, Seung-Jun
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2012.05a
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    • pp.43-45
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    • 2012
  • As a part of recent CO2 emission reduction studies in the concrete industry with active use of concrete admixtures with low basic unit of CO2 emission such as blast furnace slag (BFS), basic unit of CO2 emission by SBFS was computed in order to assess CO2 emission by reinforced concrete building with smart blast furnace slag (SBFS). In addition, SBFS concrete was applied to the subject building for assessment of CO2 emission during material production step among construction steps. Life cycle CO2 emission assessment on the subject building was classified into 7cases according to mix ratio of BFS and SBFS.

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Comparative Evaluation of Interpolation Accuracy for $CO_2$ Emission using GIS (GIS를 활용한 이산화탄소 농도 보간 정확도 비교평가)

  • Kim, Jun-Hyun;Choi, Jin-Ho;Kim, Chung-Sil
    • Journal of Environmental Impact Assessment
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    • v.19 no.6
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    • pp.647-656
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    • 2010
  • As the $CO_2$ from buildings take up approximately 25% of the total $CO_2$ emission, the need for regulating and managing this emission is urgently required. Thus this study recognizes $CO_2$ emission status for diverse purposes and suggests accurate interpolation method for visualizing $CO_2$ emission as the basic data for regulating and managing $CO_2$ emission by applying IDW, Spline, and Kringing method. Results showed that Gaussian Function application among the Kriging methods had the highest accuracy in its estimations, with 3.049 with RMSE standards. This could be used as the basic data when visualizing $CO_2$ emission status, which is a necessity for many local and federal governments that are to regulate and manage $CO_2$ emission. This study shows that the interpolation is very appropriative method in recognizing $CO_2$ emission characteristics for regional climate change measures.

Studies on the Correlation between Germination index and CO2 Emission for Evaluation of the Maturity of Compost Products (퇴비의 부숙도 평가에 있어서 CO2 발생량과 발아지수와의 상관성 연구)

  • 백창현;이명규;김창한
    • Journal of Animal Environmental Science
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    • v.4 no.2
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    • pp.183-191
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    • 1998
  • This study was carried out to elucidate the correlation between Germination Index(G.I.) and CO2 emission for evaluation of the maturity of compost products. 13 compost samples was used for this experiment. The G.I. test was carried out on the basis of T-N 200ppm. As a result of this research, we found that CO2 emission method was good simple indicator for evaluation of maturity of compost materials, in spite of G.I. The obtain results are summarized as follows ; 1. The correlation value between the G.I. and the CO2 emission was R2 = 0.776. 2. The correlation value between EC(Electric Conductivity) and G.I. was R2 =0.7. 3. The equation calculated from G.I. and CO2 emission was G.I. = -16.7(InCO2) - 6.87. 4. From these results, we found the possibility of estimation for the value of G.I.(T-N 200ppm) from CO2 emission volume under specific condition.

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The Application of CO2 and Hydrometer Sensor for Development of Real Time Measuring Method on CO2 Emission of Construction Equipment (건설장비의 CO2배출량 실시간 측정방법 개발을 위한 CO2 및 유속센서의 활용)

  • Jang, Won-Suk;Kim, Byung-Soo
    • Korean Journal of Construction Engineering and Management
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    • v.14 no.2
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    • pp.78-86
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    • 2013
  • The researches for reduce $CO_2$ are going along animatedly in hole industry area. In construction area, the researches to minimize $CO_2$ emission are progressing variously. The researches to minimize $CO_2$ emission based on $CO_2$ emission. The method measuring $CO_2$ emission are using $CO_2$ emission coefficient on fuel consumption, LCA and an inter-industry relation table. Especially, the methods using the carbon emission coefficient based on fuel consumption are 3 types(Tier1~Tier3) of IPCC. Present, the most using method(Tier1) is using the fuel consumption and the carbon emission coefficient. But because this method do not effect each vehicle distance and driving environment, we can't calculate right $CO_2$ emission. Especially construction project's $CO_2$ emission could be different by project's characteristic. However, we can't apply these difference with present methods. So we need methodology calculating $CO_2$ emission by applying personal project's characteristic and these methodology's most important things is directly measuring $CO_2$ emission of construction equipment which use energy. The object of this study is to develop the $CO_2$ emission calculation methodology which occur in construction process, is to suggest ways to measure in real time $CO_2$ emission from construction equipment.

Estimation and Feature of Greenhouse Gas Emission in Building Sector by National Energy Statistic (국가 에너지통계에 따른 건물부문 온실가스 배출량 추계 및 특성)

  • Jeong, Young-Sun;Kim, Tae-Hyoung
    • 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 $68.4kg-CO_{2e}/m^2{\cdot}yr$.

A Study on $CO_2$ Emissions with the Carbody Material of Electric Motor Unit (EMU) using Life Cycle Inventory Analysis (LCIA) (전과정목록 분석을 이용한 전동차의 구체 재질에 따른 $CO_2$ 배출량에 관한 연구)

  • Kim, Yong-Ki;Chun, Yoon-Young;Lee, Jae-Young
    • Proceedings of the KSR Conference
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    • 2006.11b
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    • pp.1123-1125
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    • 2006
  • As Kyoto protocol has been effective in 2005, the reduction of $CO_2$ emission is a global urgent problem. In Korea, the $CO_2$ emission of transportation increases continuously, which can be solved partially by the use of railroad. Therefore, it is necessary to calculate exactly the $CO_2$ emission of railroad through life cycle approach. In this study, the $CO_2$ emission of electric motor unit (EMU) was evaluated with its carboy material using life cycle inventory analysis (LCIA). Among the life cycles of EMU, $CO_2$ emission was the highest in the running phase. As the total weight of EMU was lowered, $CO_2$ emission was reduced. In conclusion, the light-weighting of EMU can reduce $CO_2$ emission efficiently.

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A Study on CO2 Emission Factor for Earth-Work Equipment Using C-FVM (C-FVM을 이용한 토공장비의 CO2 배출계수에 관한 연구)

  • Kim, Byung-Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.3
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    • pp.999-1006
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    • 2014
  • $CO_2$ emission factor for earthwork equipment was made based on fuel consumption quantity using IPCC carbon emission factor. This is presented through the carbon emission estimating guideline each facilities by the Ministry of Land, Infrastructure and Transportation in 2011. However, this method has the defect which don't apply the various condition of site. Therefor it needs the new emission factor supplemented these defects. This study will tries to estimate $CO_2$ emission with the direct measurement method using concentration flow velocity measurement (C-FVM) for earth work equipment and present the new $CO_2$ emission factor for earth work equipment after compare with emission factor of the Ministry of Land, Infrastructure and Transportation.

A Study on The Evaluation Criteria of Carbon Emission and the Development of the Evaluation Method in Apartment House (공동주택을 대상으로 한 탄소배출 평가기준 구축 및 평가방법 개발)

  • Choi, Doo-Sung;Chun, Hung-Chan
    • KIEAE Journal
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    • v.13 no.5
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    • pp.79-88
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    • 2013
  • This study creates the evaluation criteria to analyze the $CO_2$ emission quantity in the complex of apartment house among domestic buildings and proposes how to calculate the $CO_2$ emission quantity by the only simple information of apartment house. The study shows that in order to create the index of carbon emission evaluation criteria, $CO_2$ emission quantity for its input materials in these 27 apartment houses are 445,412g-$CO_2/m^2$ for apartment building, 474,322g-$CO_2/m^2$ for the basement parking lot, 483,523g-$CO_2/m^2$ for welfare facility, 729,957g-$CO_2/m^2$ for sales facility, 743,560g-$CO_2/m^2$ for other facility, 26,782g-$CO_2/m^2$ for public facility, 43,659g-$CO_2/m^2$ for landscape, 1,113g-$CO_2/m^2$ for indoor facility, 11,251g-$CO_2/m^2$ for outdoor facility and 891g-$CO_2/m^2$ for common temporary based on the average $CO_2$ emission by facility. We can also see the analysis data that in case of using the selected factors only, the rate of error is 7.51% comparing with the emission quantity by using simplified LCA method this study suggests for the whole range of apartment houses and the rate of error is average 3.24% using selective and main materials. And this it is evaluated that we can get the result which is similar to the actual $CO_2$ emission quantity with only the simple information about the apartment house.

The Measurement Method of CO2 Emission for Construction Equipment using ZigBee Sensor (ZigBee 센서를 활용한 건설장비의 CO2 배출량 측정방법)

  • Chun, Jin-Ku;Kim, Byung-Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.32 no.2D
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    • pp.167-174
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    • 2012
  • Recently, the effort to reduce $CO_2$ emission concerning certified emission reductions (CERs) is progressing lively with the institute in the center through lifecycle. However, the technique for reduce $CO_2$ emission is the first stage yet and the technique is insufficient to calculate with accuracy it. Therefore, this study tries to develop the method to measure by actual time $CO_2$ emission of construction equipment using Zigbee sensor. To review the method that calculate $CO_2$ emission, have classified the impact factors that affect at $CO_2$ emission by IPCC guideline. It also has review the application of Zigbee sensor that use wireless data communication. The reviewed result get that the measuring objects are the $CO_2$ emssion, RPM and fuel consumption of equipment, there are needs to search the year of equipment, waiting time, kind of vehicle and fuel that affect to $CO_2$ emission.