• Title/Summary/Keyword: Emission Category

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An E-score Development Methodology for Life Cycle Impact Assessment

  • Young-Min Park;Jai-Rip Cho
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.24 no.68
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    • pp.51-65
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    • 2001
  • This study is to make LCIA(Life Cycle Impact Assessment) easier as a methodology of environmental scores(called E-score) that integrated environmental load of each emission substance based on environmental damage such as in human health, ecosystem and resources category. The concept is to analyzes the LCI(Life Cycle Inventory) and defines the level of environment damages for human health, ecosystem and resources to objective impact assessment standard, and makes the base of marginal damage to calculate the damage factor, which can present the indication that can establish the standard value of environmental impact. First, damages to human health are calculated by fate analysis, effect analysis and damage analysis to get the damage factor of health effect as a DALY(Disability Adjusted Life Years) unit. Second, damages to ecosystem are calculated by fate analysis, effect analysis and damage analysis to get the damage factor of the effect as a PDF(Potentially Disappeared Fraction) unit through linking potentially increased disappeared fraction. Third, damages to resources are carried out by resource analysis and damage analysis for linking the lower fate to surplus energy conception to get damage factor as a MJ(Mega Joule) unit. For the ranking of relative environment load level each other, LCIA can be carried out effectively by applying this E-score methodology to the particular emission substances. A case study has been introduced for the emission substances coming out of a tire manufacturer in Korea. It is to show how to work the methodology. Based on such study result, product-designers or producers now can apply the E-scores presented in this study to the substances of emission list, and then calculate the environment load of the product or process in advance at any time and can see the environment performance comparatively and expected to contribute to the environmental improvement in view of environmental pollution prevention.

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A Study on the GHG Scope 3 Emissions Management Status of the Companies Through CDP Comparative Analysis (CDP 비교 분석을 통한 기업의 GHG Scope 3 배출관리 현황 연구)

  • Sungah Yoon;Hong-Kwan Kim;Young-Woo Chon
    • Journal of the Society of Disaster Information
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    • v.19 no.3
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    • pp.554-561
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    • 2023
  • Purpose: To urge the necessity of disclosure by identifying the relationship between the disclosure status of greenhouse gas emissions from domestic business sites and other indirect emissions to total emissions. Method: The 2021 emission data disclosed in the Carbon Disclosure Project (CDP) was collected by industry and emission category for comparative analysis. Result: The more companies that calculated and disclosed emissions by category within Scope 3, the more active they were in responding to or disclosing evaluation factors other than disclosure of emissions, and those companies were able to obtain higher grades in CDP and ESG evaluations. The number of Scope 3 calculations and disclosures was found to be high. In addition, there was a significant difference in the correlation between the number of Scope 3 disclosures by industry and the share of each scope out of the total in some manufacturing industries. Conclusion: As the number of Scope 3 disclosures, corporate ratings, and total emissions are proportional, it was confirmed that the higher the number of Scope 3 disclosures and GHG emissions, the higher the level of Scope 3 management. Based on Scope 3 emissions calculation and disclosure, effective emissions management and reduction activities are required.

Automatic Classification by Land Use Category of National Level LULUCF Sector using Deep Learning Model (딥러닝모델을 이용한 국가수준 LULUCF 분야 토지이용 범주별 자동화 분류)

  • Park, Jeong Mook;Sim, Woo Dam;Lee, Jung Soo
    • Korean Journal of Remote Sensing
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    • v.35 no.6_2
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    • pp.1053-1065
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    • 2019
  • Land use statistics calculation is very informative data as the activity data for calculating exact carbon absorption and emission in post-2020. To effective interpretation by land use category, This study classify automatically image interpretation by land use category applying forest aerial photography (FAP) to deep learning model and calculate national unit statistics. Dataset (DS) applied deep learning is divided into training dataset (training DS) and test dataset (test DS) by extracting image of FAP based national forest resource inventory permanent sample plot location. Training DS give label to image by definition of land use category and learn and verify deep learning model. When verified deep learning model, training accuracy of model is highest at epoch 1,500 with about 89%. As a result of applying the trained deep learning model to test DS, interpretation classification accuracy of image label was about 90%. When the estimating area of classification by category using sampling method and compare to national statistics, consistency also very high, so it judged that it is enough to be used for activity data of national GHG (Greenhouse Gas) inventory report of LULUCF sector in the future.

Categorization of Hazard Chemicals Potentially Discharged into Water System (수계 유출가능성이 있는 유해화학물질 분류화)

  • An, Youn-Joo;Nam, Sun-Hwa;Lee, Jae-Kwan
    • Journal of Korean Society on Water Environment
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    • v.24 no.2
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    • pp.247-259
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    • 2008
  • The utilization of a variety of hazard chemicals bears risks to human health and ecosystem. The increasing usage of various chemicals indicates the greater emission of those chemicals to water system, and the subsequent deterioration of water quality. Water system is vulnerable to many pollutants, however, there are limitations of managing a range of hazard chemicals based on insufficient legal foundations. Therefore it is needed to select hazard chemicals that can be potentially discharged into water system, and subsequently to classify a wide range of existing chemicals for better management of those chemicals. In this study, the 259 candidate chemicals of concern were selected from the lists of the toxic released inventory chemicals (148), hazard concern candidate chemicals (106), and wastewater effluent standard candidate chemicals (116). We suggested the category 1, 2, 3 and 4 of hazard chemicals potentially discharged into water system. The assessment factors considered for the classification were hazard potential, persistence and emission to water body. This work was conducted as a part of the project entitled 'Development of integrated methodology for evaluation of water environment', and the results were used to develop the monitoring lists of hazard chemicals in four major rivers in Korea.

A Study on Space Allocation Method and Calculation of GHGs Emissions in the Port (항만의 온실가스 배출량 산정 및 공간할당 방법에 관한 연구)

  • Choi, Sang Jin;Kim, Joung Hwa;Son, Ji Hwan;Hong, Hyun Su;Han, Yong hee;Kim, Jeong Soo;Cho, Kyeong Doo
    • Journal of Climate Change Research
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    • v.7 no.3
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    • pp.289-297
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    • 2016
  • In this study, we researched the emission source category and it was calculated emissions estimates from existing research or literature review related to port. In addition, we have created the basis for a policy that can reduce greenhouse gas emissions calculation based on the results of the harbor. Greenhouse gas emissions estimation results, we proposed a method for allocating the GIS space. In this study, we confirmed based on the calculated greenhouse gas emissions by sources resulting in the GIS Map Port result of the expression construct for space allocation. Based on these results, it tries to provide the basic data that can be used when you want to create a local government measures to reduce scenario in the future.

National Methane Inventory Relevant to Livestock Enteric Fermentation (가축 장내발효에 의한 국가단위 메탄 배출통계에 관한 연구)

  • Lee, H.J.;Lee, S.C.
    • Journal of Animal Science and Technology
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    • v.45 no.6
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    • pp.997-1006
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    • 2003
  • This study was conducted to investigate the national methane emission from livestock enteric fermentation. For methane emission estimation, livestock were mainly categorized to cattle, swine, poultry, sheep, goats and horses, and cattle were further sub-categorized to calves, fattening cattle, breeding cows in Hanwoo and calves, fattening cattle and lactating cows in dairy cattle. Tier 2 methane emission factors were deduced based on the characteristics of animal performances, live weight, slaughter weight, daily weight gain, and feed digestibility in each category. Tier 2 emission factors of Hanwoo range from 39 to 49 kg/head/year and it is similar to that of Tier 1(47kg/head/year). Tier 2 emission factor of dairy cattle was 107 kg/head/year and it is slightly lower than that of Tier 1(118kg/head/year). Total methane emission from livestock enteric fermentation by Tier 2 method was estimated to be 126.8 tones in 2001. The methane emissions by Hanwoo, dairy cattle, swine, goats, horses and sheep were 61.70, 47.76, 13.08, 2.25, 0.17 and 0.01 tones, respectively. By the use of Tier 2 method instead of Tier 1, the accuracy and reliability of methane emission estimates from livestock enteric fermentation in Korea is considered to be improved.

PM2.5 Simulations for the Seoul Metropolitan Area: (II) Estimation of Self-Contributions and Emission-to-PM2.5 Conversion Rates for Each Source Category (수도권 초미세먼지 농도모사 : (II) 오염원별, 배출물질별 자체 기여도 및 전환율 산정)

  • Kim, Soontae;Bae, Changhan;Yoo, Chul;Kim, Byeong-Uk;Kim, Hyun Cheol;Moon, Nankyoung
    • Journal of Korean Society for Atmospheric Environment
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    • v.33 no.4
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    • pp.377-392
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    • 2017
  • A set of BFM (Brute Force Method) simulations with the CMAQ (Community Multiscale Air Quality) model were conducted in order to estimate self-contributions and conversion rates of PPM (Primary $PM_{2.5}$), $NO_x$, $SO_2$, $NH_3$, and VOC emissions to $PM_{2.5}$ concentrations over the SMA (Seoul Metropolitan Area). CAPSS (Clean Air Policy Support System) 2013 EI (emissions inventory) from the NIER (National Institute of Environmental Research) was used for the base and sensitivity simulations. SCCs (Source Classification Codes) in the EI were utilized to group the emissions into area, mobile, and point source categories. PPM and $PM_{2.5}$ precursor emissions from each source category were reduced by 50%. In turn, air quality was simulated with CMAQ during January, April, July, and October in 2014 for the BFM runs. In this study, seasonal variations of SMA $PM_{2.5}$ self-sensitivities to PPM, $SO_2$, and $NH_3$ emissions can be observed even when the seasonal emission rates are almost identical. For example, when the mobile PPM emissions from the SMA were 634 TPM (Tons Per Month) and 603 TPM in January and July, self-contributions of the emissions to monthly mean $PM_{2.5}$ were $2.7{\mu}g/m^3$ and $1.3{\mu}g/m^3$ for the months, respectively. Similarly, while $NH_3$ emissions from area sources were 4,169 TPM and 3,951 TPM in January and July, the self-contributions to monthly mean $PM_{2.5}$ for the months were $2.0{\mu}g/m^3$ and $4.4{\mu}g/m^3$, respectively. Meanwhile, emission-to-$PM_{2.5}$ conversion rates of precursors vary among source categories. For instance, the annual mean conversion rates of the SMA mobile, area, and point sources were 19.3, 10.8, and $6.6{\mu}g/m^3/10^6TPY$ for $SO_2$ emissions while those rates for PPM emissions were 268.6, 207.7, and 181.5 (${\mu}g/m^3/10^6TPY$), respectively, over the region. The results demonstrate that SMA $PM_{2.5}$ responses to the same amount of reduction in precursor emissions differ for source categories and in time (e.g. seasons), which is important when the cost-benefit analysis is conducted during air quality improvement planning. On the other hand, annual mean $PM_{2.5}$ sensitivities to the SMA $NO_x$ emissions remains still negative even after a 50% reduction in emission category which implies that more aggressive $NO_x$ reductions are required for the SMA to overcome '$NO_x$ disbenefit' under the base condition.

Evaluating Spatiality of Green-House Gas Emission in Building Site ("대" 지목에 의거한 온실가스 분포의 공간성 평가)

  • Kim, Jun-Hyun;Um, Jung-Sup
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2010.06a
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    • pp.94-102
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    • 2010
  • These days the land category is the most specific basis of legal for land use or land use form that is determined by the main use of land. Even if same land building site, it is used very various like a detached house, a row house, a multiplex house, a villa, an apartment, a mixed-use Apartments, commercial building, fallow land etc. There is a need of variety analysis in order to apply greenhouse gas emission or statistics assessment for standard of classification. Therefore, This study measured carbon dioxide by for different government agencies of maps by land use time, season, elevation, space, area of floating population. As a result, The emission characteristic was high l.78 times, on average of l.35 times in winter compared with summer, when the temperatures increased 11C, the carbon dioxide is 22ppm high in the afternoon, A commercial building is high 4.04 times compare with detached house.

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Change of Ammonia Consumption with Gas Turbine Output in DeNOx System for a 580 MW Combined Cycle Power Plant (580 MW급 복합발전소 탈질설비에서 가스터빈 출력에 따른 암모니아 소모량 변화)

  • Jang, Yong-Woo;Yoo, Ho-Seon
    • Plant Journal
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    • v.15 no.3
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    • pp.23-28
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    • 2019
  • In this study, ammonia consumption by gas turbine output was adjusted to find out the amount of ammonia consumption that complies with the enhanced Air Quality Preservation Act and internal regulation emission standards in SCR type DeNOx System for a 580 MW Sejong Combined Cycle Power Plant. For measurements, the gas turbine output was varied to 50, 99, 149, 198 MW and ammonia consumption was adjusted with the combustion gas and ammonia supply conditions fixed at each stage. When the emission limit were change from 10 ppm to 8 ppm, ammonia consumption was increased from 78, 93, 105, 133 kg/h to 89, 113, 132, 176 kg/h. The increase rate of ammonia consumption was 14, 22, 26, 32% per output category compared to the 10 ppm emission limit, which was shown to increase as output increased.

Development of tool condition monitoring system using unsupervised learning capability of the ART2 network

  • Choii, Gi-Sang
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10b
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    • pp.1570-1575
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    • 1991
  • The feasibility of using an adaptive resonance network (ART2) with unsupervised learning capability for too] wear detection in turning operations is investigated. Specifically, acoustic emission (AE) and cutting force signals were measured during machining, the multichannel AR coefficients of the two signals were calculated and then presented to the network to make a decision on tool wear. If the presented features are significantly different from previously learned patterns associated with a fresh tool, the network will recognize the difference and form a new category m worn tool. The experimental results show that tool wear can be effectively detected with or without minimum prior training using the self-organization property of the ART2 network.

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