• 한국기후변화학회지
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• 제9권4호
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• pp.445-452
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• 2018

The field of agriculture, forestry, and other land-use (AFOLU) is concerned with greenhouse emissions of agriculture (crop and livestock), as is the field of land-use, land-use change, and forestry (LULUCF). The 1996 IPCC guideline and the 2006 IPCC guideline are used in combination for calculation of greenhouse gas emission from the agricultural sector, and the 2003 IPCC guideline is used for that from the land-use sector. In this research, we analyzed GHG emissions of the cropland sector in AFOLU based on the 2006 IPCC guideline. The results showed that GHG emissions of 1990 was $-504Gg{\cdot}CO_2-eq$, while that of the last year was $2,871Gg{\cdot}CO_2-eq$. Compared with the 2003 methodology, total emissions according to the 2006 IPCC was lower except in 1997 and 2003. This trend is due to difference of analyzed emission sources, lower default values, and global warming potential by the 2006 IPCC. The results are estimated using limited data at the Tier 1 level and the first issue to be solved is the activity data from the land-use change matrix. Although this result should be improved, it can be used as the basis for calculating GHG emissions of the AFOLU sector.

• 농촌계획
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• 제19권4호
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• pp.125-135
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• 2013

Analysis and evaluation of uncertainty is adopting the advanced methodology among the methods for greenhouse gas emission assessment that was defined in GPS2000 (Good practice guideline 2000) and GPG-LULUCF (GPG Land Use, Land-Use Change and Forestry). In 2006 IPCC guideline, two approaches are suggested to explain the uncertainty for each section with a national net emission and a prediction value on uncertainty as follows; 1) Spread sheet calculation based on the error propagation algorithm that was simplified with some assumptions, and 2) Monte carlo simulation that can be utilized in general purposes. There are few researches on the agricultural field including greenhouse gas emission that is generated from livestock and cultivation lands due to lack of information for statistic data, emission coefficient, and complicated emission formula. The main objective of this study is to suggest an evaluation method for the uncertainty of greenhouse gas emission in agricultural field by means of intercomparison of the prediction value on uncertainties which were estimated by spread sheet calculation and monte carlo simulation. A statistic analysis for probability density function for uncertainty of emission rate was carried out by targeting livestock intestinal fermentation, excrements treatment, and direct/indirect emission from agricultural lands and rice cultivation. It was suggested to minimize uncertainty by means of extraction of emission coefficient according to each targeting section.