IPCC Guidelines have been updated after the first official announcement to get more precise estimation of GHG emissions. The goal of this study is to evaluate the implications of the IPCC Guidelines improvements including equations of country-specific parameter values for estimating GHG emissions for rice cultivation on the agricultural sector. In addition, we analyze the effects of emission factors associated with organic amendment applications. The results of this study are as follows; (1) the total GHG emissions of rice cultivation based on 1996 IPCC GL are 28% lower than those estimated by 2006 IPCC GL with the same year data; (2) GHGs can be reduced up to 60% through the assumption of organic fertilizer applications; (3) Jeonnam and Chungnam are the worst regions for GHG emissions on rice cultivation and Chungbuk shows the highest reduction rate of GHG emissions, about 40%.

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.