• IE interfaces
• /
• v.22 no.4
• /
• pp.317-328
• /
• 2009

For a comprehensive understanding of human impact on a change of the global climate, it is necessary to obtain reliable information on man-induced fluxes of greenhouse gases (GHGs) into the atmosphere. Intergovernmental Panel on Climate Change (IPCC) guidelines (IPCC 1996, IPCC 2000, IPCC2006) provide the methods and procedures of estimating the national GHG emission inventories. Particularly, IPCC 2006 contains new chapter of key conceptions uncertainties, including the types of uncertainties and assessment methods of uncertainties in GHG emission inventories. In this paper, a compact and clear survey on volume 1 of IPCC 2006, which contains the general information on inventory compilation, uncertainty and guidance on the choice of methods, and QC/QA, is given with emphasis on uncertainty analysis.

• Resources Recycling
• /
• v.25 no.5
• /
• pp.28-35
• /
• 2016

The purpose of this study was to estimate greenhouse gas emissions using IPCC 1996 Guideline Tier 1, Good Practice Guidance 2000 Tier 2 and IPCC 2006 Guideline First Order Decay methods from landfill disposal facility. In addition, a comparative analysis evaluating the pros and cons of each method based on assumptions and default factors was considered for each method. The greenhouse gas emission computed using IPCC 1996 Guideline Tier 1 method (2,760 ton/yr) was higher than the estimation of GPG 2000 Tier 2 and IPCC 2006 Guideline First Order Decay Model which showed 1500 and 880 ton/yr respectively between 2000 and 2013.

• Journal of Environmental Impact Assessment
• /
• v.21 no.3
• /
• pp.409-415
• /
• 2012

Post-kyoto regime has been discussing with the GHG reduction commitment. GHG energy target management system also has been applied for the domestic measures in the country. Universities are major emission sources for GHG. It is very important for campus to built the GHG inventory system and estimate the potential GHG emission reduction. In general, GHG inventory on the campus was taken by the IPCC guidance with the classification of scope 1, 2, and 3. Electricity was the highest portion of GHG emission on the campus as 5,053.90 $tonsCO_2eq/yr$ in 2009. Manufacturing sector was the second high emission and meant GHG in laboratory. Potential GHG reduction was planned by several assumptions such as installation of occupancy sensor, exchanging LED lamp and photovoltaic power generation. These reduction scenarios was simulated by LEAP model. In 2020, outlook of GHG emission was estimated by 17,435.98 tons of $CO_2$ without any plans of reduction. If the reduction scenarios was applied in 2020, GHG emission would be 16,507.60 tons of $CO_2$ as 5.3% potential reduction.

• Journal of Climate Change Research
• /
• v.7 no.4
• /
• pp.443-450
• /
• 2016

The major greenhouse gases (GHGs) in agricultural sector are methane ($CH_4$), nitrous oxide ($N_2O$), carbon dioxide ($CO_2$). GHGs emissions are estimated by pertinent source category in a guideline book from Intergovernmental Panel on Climate Change (IPCC) such as methane from rice paddy, nitrous oxide from agricultural soil and crop residue burning. The methods for estimation GHGs emissions in agricultural sector are based on 1996 and 2006 IPCC guideline, 2000 and 2003 Good Practice Guidance. In general, GHG emissions were calculated by multiplying the activity data by emission factor. The total GHGs emission is $10,863Gg\;CO_2-eq$. from crop cultivation in agricultural sector in 2013. The emission is divided by the ratio of greenhouse gases that methane and nitrous oxide are 64% and 34%, respectively. Each gas emission according to the source categories is $7,000Gg\;CO_2-eq$. from rice paddy field, $3,897Gg\;CO_2-eq$. from agricultural soil, and $21Gg\;CO_2-eq$. from field burning, respectively. The GHGs emission in agricultural sector had been gradually decreased from 1990 to 2013 because of the reduction of cultivation. In order to compare with indirect emissions from agricultural soil, each emission was calculated using IPCC default factors (D) and country specific emission factors (CS). Nitrous oxide emission by CS applied in indirect emission, as nitrogen leaching and run off, was lower about 50% than that by D.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.14 no.3
• /
• pp.236-256
• /
• 2011

Forest carbon stocks change due to land use change is an important data required by UNFCCC(United Nations framework convention on climate change). Spatially explicit estimation of forest carbon stocks based on IPCC GPG(intergovernmental panel on climate change good practice guidance) tier 3 gives high reliability. But a current estimation which was aggregated from NFI data doesn't have detail forest carbon stocks by polygon or cell. In order to improve an estimation remote sensing and GIS have been used especially in Europe and North America. We divided research trends in main countries into 4 categories such as remote sensing, GIS, geostatistics and environmental modeling considering spatial heterogeneity. The easiest way to apply is combination NFI data with forest type map based on GIS. Considering especially complicated forest structure of Korea, geostatistics is useful to estimate local variation of forest carbon. In addition, fine scale image is good for verification of forest carbon stocks and determination of CDM site. Related domestic researches are still on initial status and forest carbon stocks are mainly estimated using k-nearest neighbor(k-NN). In order to select suitable method for forest in Korea, an applicability of diverse spatial data and algorithm must be considered. Also the comparison between methods is required.

• Journal of Climate Change Research
• /
• v.6 no.4
• /
• pp.303-310
• /
• 2015

This study was conducted to estimate of carbon stock and greenhouse gas (GHGs) removals by tree species and forest type at Gangwon province. We used a point sampling data with permanent sample plots in national forest inventory and national emission factors. GHGs emissions was caclulated using the stock change method related to K-MRV and IPCC guidance. Total carbon stock and greenhouse gas removals were high in deciduous forest and species than in coniferous. The range of annual net greenhouse gas emissions in other deciduous species was from $-11,564.83Gg\;CO_2\;yr^{-1}$ to $-13,500.60Gg\;CO_2\;yr^{-1}$ during 3 years (2011~2013). On the other hand, coniferous forest was temporally converted to source due to reducing of growing stock in 2012. It was that growing stocks and forest area were likely to reduce by the deforestation and clear cutting. This study did not consider other carbon pools (soil and dead organic matter) due to the lack of data. This study needs to complement the activity data and emission factors, and then will find the way to calculate the greenhouse gas emissions and removals in the near future.

• Journal of Korean Society of Forest Science
• /
• v.96 no.3
• /
• pp.235-244
• /
• 2007

Potentials of AR CDM project in North Korea are assessed and feasible land area for AR CDM project is estimated. According to our estimation, There could be 515,000 hectares of forest lands deforested before 1990 in North Korea and 8,854 hectares at the regional level of Gae-sung City, which are eligible for AR CDM project, based on researches of satellite image analyses conducted from 1980's to 1990's. A baseline scenario assumed 44.73 tones of carbon stored in soil per hectare with no vegetation above ground remained during the project period following the default value of IPCC's Good Practice Guidance for LULUCF considering soil structure, climate and land use of the project area. The scenario also assumes that black rocust (Robinia pseudoacacia) is planted and the CDM project is implemented for 20 years. The costs for producing greenhouse gases CER (certified emission reduction) credits include costs of tree planting and forest management, and costs of project negotiation and transactions for issuing the credits. It is estimated that 376 tones of carbon dioxide per hectare can be accumulated and 503 temporary CER credits per hectare and 265 long-term CER credits per hectare could be produced during the project period. It is estimated to cost US$ 4.04 and US$ 7.67 to provide one unit of temporary credit and long-term credit, respectively. These values can be regarded as the cost of conferring emission commitment of a country or a private entity. However, it is not clear which option is better economically because the replacement periods are different in these two cases.