• 한국대기환경학회지
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• 제22권1호
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• pp.107-116
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• 2006

The main purpose of this study is to develop the greenhouse gas emission factor for power plant using bituminous coal. The power plant is a major source of greenhouse gases among the sectors of fossil fuel combustion, thus information of its emission factors is very essential to the establishment of control strategies for the greenhouse gas emissions. These emission factors derived in this study were compared with those of U. S. EPA, AGO and CCL. The $CO_{2}$ concentrations in the flue gas were measured using NDIR analyser and the GC-FID with a methanizer. The amount of carbon (C) and hydrogen (H) in fuel was measured using an elemental analyzer. Calorific values of fuel were also measured using a calorimeter. Caloric value of bituminous coal used in the power plants were 5,957 (as received basis), 6,591 (air-dried basis) and 6,960 kcal/kg (dry basis). Our estimates of carbon emission factors were lower than those of IPCC. The CO2 emission factors for the power plants using bituminous coal were estimated to be 0.791 Mg/MWh (by carbon contents and caloric value of the fuel) and 0.771 Mg/MWh (by $CO_{2}$ concentration of the flue gas). The $CO_{2}$ emission factors estimated in this study were $3.4\sim 5.4\%$ and $4.4\sim 6.7\%$ lower than those of CCL (2003) and U. S. EPA (2002).

• 한국농공학회논문집
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• 제65권5호
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• pp.69-80
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• 2023

Carbon neutrality in agriculture can be derived from systematic GHG reduction policies based on quantitative environmental impact analysis of GHG-emitting activities. This study is to explore how to advance the calculation of carbon emissions from agricultural activities to the detailed spatial level to a spatial Tier 3 level (Tier 2.5 level), methodologically beyond the Tier 2 approach. To estimate the GHG emissions beyond the Tier 2.5 level by region for detailed spatial units, we constructed available activity data on carbon emission impact factors such as rice cultivation, agricultural land use, and livestock. We also built and verified detailed data on emission activities at the field level through field surveys. The GHG emissions were estimated by applying the latest national emission factors and regional emission factors according to the IPCC 2019 GL based on the field-level activity data. This study has significance that it explored ways to build activity data and calculate GHG emissions through statistical data and field surveys based on parcels, one of the smallest spatial units for regional carbon reduction strategies. It is expected that by utilizing the activity data surveyed for each field and the emission factor considering the activity characteristics, it will be possible to improve the accuracy of GHG emission calculation and quantitatively evaluate the effect of applying reduction policies.

• 한국기후변화학회지
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• 제8권3호
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• pp.239-245
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• 2017

This study aimed to suggest priority for developing emission factor (EF) and to develop the methodology of quantitative assessment of EF in the forestry sector. Based on the stock-difference method, 17 kinds of EFs (27 EFs based on forest types) were required to calculate the carbon emission in the forestry sector. Priority for developing EFs followed the standards, which is a development plan by the government agency, importance of carbon stock for greenhouse gas, and EFs by the species. Currently, the most urgent development of EFs was carbon fraction in biomass and carbon stock in dead wood. Meanwhile, the quantitative assessment of EF consisted of 7 categories (5 categories of compulsory and 2 categories of quality evaluation) and 12 verification factors. Category in compulsory verification consisted of administrative document, determination methodology of emission factors, emission characteristic, accuracy of measurement and analysis, and data representative. Category in quality evaluation consisted of data management and uncertainty estimates. Based on the importance of factors in the verification process, each factor was scored separately, however, the score needs to be coordinated by the government agency. These results would help build a reliable and accurate greenhouse gas inventory report of Korea.

• 한국산림과학회지
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• 제103권4호
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• pp.593-598
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• 2014

본 연구는 주요 4개 난대수종에 대한 탄소배출계수를 개발하고 이를 이용하여 탄소저장/흡수량을 산정하고자 하였다. 대상 수종은 구실잣밤나무, 동백나무, 붉가시나무 및 종가시나무였으며, 이들에 대한 탄소배출계수는 다음과 같이 도출되었다. 탄소배출계수 중 하나인 목재기본밀도는 구실잣밤나무 0.583, 동백나무 0.657, 붉가시나무 0.833, 종가시나무 0.763이었으며, 이들 계수에 대한 불확도는 5.3~17.9%의 범위에 있는 것으로 나타났다. 바이오매스 확장계수는 구실잣밤나무 1.386, 동백나무 2.621, 붉가시나무 1.701, 종가시나무 2.123이었으며, 이들에 대한 불확도는 14.7~30.5%의 범위에 있었다. 또한 뿌리 함량비는 구실잣밤나무 0.454, 동백나무 0.356, 붉가시나무 0.191, 종가시나무 0.299이었으며, 이들에 대한 불확도는 19.8~35.7%의 범위에 있는 것으로 나타났다. 목재기본밀도 등 3개의 탄소배출계수는 모두 FAO에서 권장하는 40% 이하의 불확도를 갖고 있으므로 국가고유계수로 활용할 수 있을 것으로 판단된다. 난대지역에 분포하는 주요 4개 수종에 대한 탄소저장량을 산정한 결과, 구실잣밤나무 $186.10tCO_2/ha$, 동백나무 $280.63tCO_2/ha$, 붉가시나무 $344.04tCO_2/ha$, 종가시나무 $278.91tCO_2/ha$으로 나타났으며, 연간 탄소흡수량은 $6.65tCO_2/ha/yr$, $6.25tCO_2/ha/yr$, $11.70tCO_2/ha/yr$, $12.29tCO_2/ha/yr$으로 각각 나타났다. 이러한 정보는 난대지역 상록활엽수림 경영관리에 있어 중요한 정보가 될 것이며, 기후변화에 의한 산림 식생대 변화를 대비하는 정책적 자료로 활용될 수 있을 것으로 사료된다.

• 4차산업연구
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• 제3권2호
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• pp.1-10
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• 2023

Purpose - The main purpose of the paper is to examine the variables affecting carbon emissions in different nations around the world. Research design, data, and methodology - To measure its impact on carbon emissions, secondary data has data of the top 50 Countries have been taken. The stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model have been used to quantify the factors that affect carbon emissions. A modified version using Industry 4.0 and region in fundamental STIRPAT model has been applied with the ordinary least square approach. The outcome has been measured using both the basic and extended STIRPAT models. Result - Technology found a positive determinant as well as statistically significant at the alpha level of 0.001models indicating that technological innovation helps reduce carbon emissions. In total, 4 models have been derived to test the best fit and find the highest explaining capacity of variance. Model 3 is found best fit in explanatory power with the highest adjusted R2 (97.95%). Conclusion - It can be concluded that the selected explanatory variables population and Industry 4.0 are found important indicators and causal factors for carbon emission and found constant with all four models for total CO2 and Co2 per capita.

• 한국환경과학회지
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• 제23권6호
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• pp.1131-1142
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• 2014

In this study, the variations of the carbon dioxide fluxes were investigated with soil temperatures in the grassplot and seasonal variations of carbon dioxide concentrations and fluxes were analysed. Soil temperatures, carbon dioxide concentrations and fluxes were measured on the grassplot in Pukyong National University. Field measurements were carried out 25 times from March in 2010 to March in 2011 with nine points on the grassplot. Seasonal variations of carbon dioxide concentrations and fluxes showed an inverse relation. In summer, carbon dioxide concentrations are lower and carbon dioxide fluxes are higher. In winter, carbon dioxide concentrations are higher and carbon dioxide fluxes are lower. On the grassplot, carbon dioxide emission rate increase when the soil temperature is more than $20^{\circ}C$ and the emission rate decrease when the soil temperatures are less than $10^{\circ}C$. When the accumulated rainfall for five days before measurement day is 20~100 mm, it is showed that the more rainfall, the more carbon dioxide emissions. Carbon dioxide emission rate from the grassplot to the upper atmosphere was increased or decreased by the factors such as soil temperature, growth and wither of grass and rainfall. The results of this study showed that the emission of carbon dioxide in the grassplot is dominantly controlled by seasonal factors (especially soil temperature and rainfall).

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 봄 학술논문 발표대회
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• pp.155-156
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• 2023

This study aims to analyze the factors that cause differences in the evaluation results of the life cycle carbon emissions assessment of buildings in both Korea and China as part of the methodology research of building life cycle assessment for Chinese buildings to promote building life cycle assessment in China. Specifically, it examines the building LCA standards of Korea and the standard for building carbon emission calculation in China as mentioned in the green building certification systems of both countries. Based on the investigation of the two standards, the life cycle carbon emissions of the evaluation target building were evaluated using the building life cycle assessment methods of both countries, and the influencing factors that cause differences in the life cycle carbon emission assessment results of the two countries were analyzed.

• 오토저널
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• 제3권1호
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• pp.46-53
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• 1981

This paper describes emission control of hydrocarbon and carbon-monoxide due to oxidizing catalyst. The experiment was performed on a precious metal pelleted catalyst(Pt). The factors of the efficiency for purification due to oxidizing catalyst are space velocity, temperature, composition of exhaust gas and supplementary air. The experiment was carried out to control the factors of efficiency for purification. The results of experimental study show that temperature of catalytic converter, supplementary air and space velocity affected the efficiency for purification of hydrocarbon and carbon monoxide.

• 한국기후변화학회지
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• 제6권4호
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• pp.357-366
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• 2015

This study was conducted to estimate carbon stocks of Quercus serrata with drawing volume of trees in each tree height and DBH applying the suitable stem taper equation and tree specific carbon emission factors, using collected growth data from all over the country. Information on distribution area, tree number per hectare, tree volume and volume stocks were obtained from the $5^{th}$ National Forest Inventory (2006~2010), and method provided in IPCC GPG was applied to estimate carbon storage and removals. Performance in predicting stem diameter at a specific point along a stem in Quercus serrata by applying Kozak's model,$d=a_1DBH^{a_2}a_3^{DBH}X^{b_1Z^2+b_2ln(Z+0.001)+b_3{\sqrt{Z}}+b_4e^Z+b_5({\frac{DBH}{H}})}$, which is well known equation in stem taper estimation, was evaluated with validations statistics, Fitness Index, Bias and Standard Error of Bias. Consequently, Kozak's model turned out to be suitable in all validations statistics. Stem volume tables of Quercus serrata were derived by applying Kozak's model and carbon stock tables in each tree height and DBH were developed with country-specific carbon emission factors ($WD=0.65t/m^3$, BEF=1.55, R=0.43) of Quercus serrata. As a result of carbon stock analysis by age class in Quercus serrata, carbon stocks of IV age class (11,358 ha, 36.5%) and V age class (10,432; 33.5%) which take up the largest area in distribution of age class were 957,000 tC and 1,312,000 tC. Total carbon stocks of Quercus serrata were 3,191,000 tC which is 3% compared with total percentage of broad-leaved forest and carbon sequestration per hectare(ha) was 3.8 tC/ha/yr, $13.9tCO_2/ha/yr$, respectively.

• 한국기후변화학회지
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• 제7권4호
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• pp.513-520
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• 2016

Korea's energy consumption has been constantly increasing. Final energy consumption was increased by an annual average of 2.9% compared to 2010. The consumption of all energy sources except for its oil was increased during the same time. While electric demand has increased coal consumption increased rapidly. Therefore, calorfic value and carbon emission factor development can improve the quality of Korea's greenhouse gas inventory. Calorific value is the amount of heat generated while burning coal. Caloric value is one of the most important factors in the development of carbon emission factors. Calorific value is used as the basis for the analysis of the various energy statistics. This study has calculated the other bituminous coal and coking coal's calorfic value by the data received from domestic coal-fired power plants and steel manufacturer. Calorofic value's trend analysis period is the year of 2010~2014. Through analyzing the carbon content it was calculated the carbon emission factor. The bituminous coal and coking coal's uncertainty analysis was performed using a Monte Carlo simulation.