• Journal of Animal Science and Technology
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• v.61 no.3
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• pp.122-137
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• 2019

Methane, one of the important greenhouse gas, has a higher global warming potential than that of carbon dioxide. Agriculture, especially livestock, is considered as the biggest sector in producing anthropogenic methane. Among livestock, ruminants are the highest emitters of enteric methane. Methanogenesis, a continuous process in the rumen, carried out by archaea either with a hydrogenotrophic pathway that converts hydrogen and carbon dioxide to methane or with methylotrophic pathway, which the substrate for methanogenesis is methyl groups. For accurate estimation of methane from ruminants, three methods have been successfully used in various experiments under different environmental conditions such as respiration chamber, sulfur hexafluoride tracer technique, and the automated head-chamber or GreenFeed system. Methane production and emission from ruminants are increasing day by day with an increase of ruminants which help to meet up the nutrient demands of the increasing human population throughout the world. Several mitigation strategies have been taken separately for methane abatement from ruminant productions such as animal intervention, diet selection, dietary feed additives, probiotics, defaunation, supplementation of fats, oils, organic acids, plant secondary metabolites, etc. However, sustainable mitigation strategies are not established yet. A cumulative approach of accurate enteric methane measurement and existing mitigation strategies with more focusing on the biological reduction of methane emission by direct-fed microbials could be the sustainable methane mitigation approaches.

• Journal of the Korea Organic Resources Recycling Association
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• v.23 no.3
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• pp.78-84
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• 2015

The aim of this study was to evaluate methane emission flux based on spatial methane concentration using laser methane detector, and geospatial methodology (Inverse distance weighting) at a landfill. The obtained results showed that the spatial methane concentrations were in good agreement with the methane emission fluxes. Thus, it was concluded that the methane emission flux could be derived from spatial methane concentrations. In addition, the results of the geospatial calculations showed that 12.85% of the total area contributed more than 42.21% of total flux. This suggested that the geospatial methodology might be essential in chamber method to determine accurate methane emission fluxes from landfills.

• Journal of Korean Society of Rural Planning
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• v.27 no.3
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• pp.21-33
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• 2021

Rice straw management and winter crop cultivation are crucial components for the accurate estimation of paddy methane emissions. Field-based extensive investigation of paddy organic matter management requires enormous efforts however it becomes more feasible as drone technology advances. The objectives of this study were to identify paddy fields of straw application and winter crop cultivation using drone images and to apply for the estimation of yearly methane emission. Total 35 sites of over 150ha in area were selected nationwide as the study areas. Drone images of the study sites were taken twice during summer and winter in 2018 through 2019: Summer images were used to identify paddy cultivation areas, while winter images for straw and winter crop practices. Drone-image-based identification results were used to estimate paddy methane emission and compared with conventional method. As the result, mean areas for paddy, straw application and winter crop cultivation were 118.9ha, 12.0ha, and 11.3ha, respectively. Overall rice straw application rate were greater in Gyeonggi-do(20%) and Chungcheongnam-do(12%), while winter crop cultivation was greatest in Gyeongsangnam-do(30%) and Jeolla-do(27%). Yearly mean methane emission was estimated to be 226.2kg CH₄/ha/yr in this study and about 32% less when compared to 331.8kg CH₄/ha/yr estimated with the conventional method. This was primarily because of the lower rice straw application rate observed in this study, which was less than quarter the rate of 55.62% used for the conventional method. This indicates the necessity to use more accurate statistics of rice straw application as well as winter crop practices into paddy methane emission estimation. Thus it is recommended to further study to link drone technology with satellite image analysis in order to identify organic management practices at a paddy field level over extensive agricultural area.

• Journal of the Korean Society of Mineral and Energy Resources Engineers
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• v.55 no.6
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• pp.649-659
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• 2018

In this study, after operational data for a landfill gas power plant were collected, the methane gas concentration was predicted using a deep learning method. Concentrations of methane gas, carbon dioxide, hydrogen sulfide, oxygen concentration, as well as data related to the valve opening degree, air temperature and humidity were collected from 23 pipeline bases for 88 matches from January to November 2017. After the deep learning model learned the collected data, methane gas concentration was estimated by applying other data. Our study yielded extremely accurate estimation results for all of the 23 pipeline bases.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.3
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• pp.39-49
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• 2020

Rice paddy cultivation is one of the major sources in methane (CH₄) emission of which accurate assessment would be a prerequisite for agricultural greenhouse gas management. Biomass treatment in paddy fields is an important factor that affects CH₄ emissions and thus needs to be taken into account. The objectives of this study were to apply drone images to investigate organic matter practices and to incorporate into the estimation of CH₄ emissions from paddy fields. Three study areas were selected by one from each of the three different regions of Yeongnam, Honam and Jungbu, which are the most active region in paddy cultivation. The eBee drone was used to take images of the study sites twice a year; Jul mid-season for identifying rice cultivation area; Jan for investigating rice straw management and winter crop cultivation. Based on biomass management practices, different emissions factors were assigned on an individual paddy field and CH₄ emmisions were estimated by multiplying respective areas. The ratios of rice straw application and winter crop cultivation were 1.4% and 37.2% in Hapcheon, 1.3% and 19.8% in Gimje, and 0.0% and 0.5% in Dangjin, respectively. The CH₄ emissions estimates for respective sites were 0.40 ton CH₄/year/ha, 0.34 ton CH₄/year/ha, and 0.29 ton CH₄/year/ha. On average, estimated CH₄ emissions of this study were 28.5% less than the current Tier 2 CH₄ emission estimation method.

• Journal of the Society of Disaster Information
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• v.15 no.4
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• pp.560-569
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• 2019

Purpose: Greenhouse gases are one of the major causes of global warming, a global disaster. This study aims to calculate road sector greenhouse gas emissions more precisely than conventional methods. Method: Currently, the average speed of a vehicle is used to calculate greenhouse gas emissions. In this study, GHG emissions are calculated using the speed of individual vehicles and compared with current methods. Result: It was confirmed that the existing emission estimation method underestimated about 15% in the case of carbon dioxide, about 1% in the case of nitrous oxide, and about 1% in the case of methane. Conclusion: Current methods of estimating greenhouse gas emissions were developed before 2000 and were developed to meet the limits of available data. However, with the advancement of technology, the quality of available data is now high, and new emissions estimation methods are needed. Therefore, in this study, we propose a method for estimating the velocity-based greenhouse gas emissions of individual vehicles as a more accurate method for calculating greenhouse gas emissions.