• Horticultural Science & Technology
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• v.29 no.5
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• pp.389-406
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• 2011

As part of a feasibility study for introducing carbon labeling of fruit products in Korea, we explore the use of carbon footprints for Korean kiwifruit from Gyeongnam region as a case study. In Korea, the Korean Environmental Industry and Technology Institute (KEITI) is responsible for the carbon footprint labeling certification, and has two types of certification programs: one program focuses on climate change response (carbon footprint labeling analysis) and the other on low-carbon products (reduction of carbon footprints analysis). Currently agricultural products have not yet been included in the program. Carbon labeling could soon be a prerequisite for the international trading of agricultural products. In general the carbon footprints of various agricultural products from New Zealand followed the methodology described in the ISO standards and conformed to the PAS 2050. The carbon footprint assessment focuses on a supply chain, and considers the foreground and the background systems. The basic scheme consists of four phases, which are the 'goal', 'scope', 'inventory analysis', and 'interpretation' phases. In the case of the carbon footprint of New Zealand kiwifruit the study tried to understand each phase's contribution to total GHG emissions. According to the results, shipping, orchard, and coolstore operation are the main life cycle stages that contribute to the carbon footprint of the kiwifruit supply chain stretching from the orchard in New Zealand to the consumer in the UK. The carbon emission of long-distance transportation such as shipping can be a hot-spot of GHG emissions, but can be balanced out by minimizing the carbon footprint of other life cycle phases. For this reason it is important that orchard and coolstore operations reduce the GHG-intensive inputs such as fuel or electricity to minimize GHG emissions and consequently facilitate the industry to compete in international markets. The carbon footprint labeling guided by international standards should be introduced for fruit products in Korea as soon as possible. The already established LCA methodology of NZ kiwifruit can be applied for fruit products as a case study.

• Journal of Climate Change Research
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• v.4 no.3
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• pp.235-244
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• 2013

Carbon dioxide emission estimation methods consist of four tiers according to the IPCC guideline. In this study, estimated results by tier 3 and tier 4 were compared with the theoretically calculated $CO_2$ emissions based on the mass balance approach for a gas fired power plant between March and May 2011. It was found that the relative differences were upto 17% between the measured emissions by tier 4 and theoretically estimated emissions, while the results of tier 3 were similar to those from theoretically estimated ones. The comparisons suggested the possibility of misestimation due to replacing missing, abnormal, or invalid data in continuous emissions monitoring system. When using only the data without those missing, abnormal, or invalid data, the relative differences decreased somewhat but still showed consistent differences depending on the stack. It is suggested that this differences might be due to the accuracy of the measurement instruments for the tier 4, especially, for the flow rate measurement instrument.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.6
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• pp.502-509
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• 2013

To estimate greenhouse gas (GHG) emission, we established inventory of conventional rice cultivation from farmers in Gunsan and Iksan, Jeonbuk province in 2011~2012. This study was to calculate carbon footprint and to analyse the major factor of GHGs. We carried out a sensitivity analysis using the analyzed main factors of GHGs and estimated the mitigation potential of GHGs. Also we tried to suggest agricultural methods to reduce GHGs that farmers of this case study can apply. Carbon footprint of rice production unit of 1 kg was 2.21 kg $CO_2.-eq.kg^{-1}$. Although amount of $CO_2$ emissions is largest among GHGs, methane had the highest contribution of carbon footprint on rice production system after methane was converted to carbon dioxide equivalent ($CO_2$-eq.) multiplied by the global warming potential (GWP). Source of $CO_2$ in the cultivation of rice farming is incomplete combustion of fossil fuels used by agricultural machinery. Most of the $CH_4$ emitted during rice cultivation and major factor of $CH_4$ emission is flooded paddy field in anaerobic condition. Most of the $N_2O$ emitted from rice cultivation process and major sources of $N_2O$ emission is application of fertilizer such as compound fertilizer, urea, orgainc fertilizer, etc. As a result of sensitivity analysis due to the variation in energy consumption, diesel had the highest sensitivity among the energies inputs. If diesel consumption is reduced by 10%, it could be estimated that $CO_2$ potential reduction is about 2.5%. When application rate of compound fertilizer reduces by 10%, the potential reduction is calculated to be approximately 1% for $CO_2$ and approximately 1.8% for $N_2O$. When drainage duration is decreased until 10 days, methane emissions is reduced by approximately 4.5%. That is to say drainage days, tillage, and reducing diesel consumption were the main sources having the largest effect of GHG reduction due to changing amount of inputs. Accordingly, proposed methods to decrease GHG emissions were no-tillage, midsummer drainage, etc.

• Journal of the Korean Applied Science and Technology
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• v.34 no.4
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• pp.1046-1057
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• 2017

Country-specific emission factors should be developed and used instead of IPCC defaults to improve national GHG inventories to Tier 2 and above. Since the country-specific emission factors depend on the type of energy source, energy process, and time trend, identifying the value of each energy source is an important part of building an accurate inventory. In this study, calorific value and carbon emission factor for petroleum energy sources on the basis of calorific value conversion standard for energy source, which are notified in Korea, are collected by 2013 and 2016, and calorific value, carbon content and carbon emission factor And a comparative analysis was conducted. In addition, net calorific values and carbon emission factors calculated for each petroleum based energy source are compared with those shown in 2006 IPCC Guideline.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.1215-1224
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• 2013

Great efforts have been made worldwide to reduce the Green House Gas (GHG) emission following the "Kyoto Protocol" declared during the United Nations Framework Convention on Climate Change in 1997. Many industries have restructured to meet the standard set by the Protocol. However, no clear guidance has been established for the purpose of reducing the GHG emission in construction industry. In addition, no significant effort has been made to conserve the energy during construction activities. For more effective energy saving in construction industry, it is essential to collect data about energy consumption, quantity of environmental emissions and costs. However, most studies on sustainable construction have been concentrated on the use of equipment, maintenance and repair works during construction due to the difficulties of collecting such data. This study suggests a method to select the most environmentally friendly equipment combination for earthwork with comparing environmental loads and costs using the database of Life Cycle Inventory in the Ministry of Knowledge Economy and Ministry of Environment of Korea.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.6
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• pp.1195-1206
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• 2011

This study was conducted to apply LCA (Life cycle assessment) methodology to lettuce (Lactuca sativa L.) production systems in Namyang-ju as a case study. Five lettuce growing farms with three different farming systems (two farms with organic farming system, one farm with a system without agricultural chemicals and two farms with conventional farming system) were selected at Namyangju city of Gyeonggi-province in Korea. The input data for LCA were collected by interviewing with the farmers. The system boundary was set at a cropping season without heating and cooling system for reducing uncertainties in data collection and calculation. Sensitivity analysis was carried out to find out the effect of type and amount of fertilizer and energy use on GHG (Greenhouse Gas) emission. The results of establishing GTG (Gate-to-Gate) inventory revealed that the quantity of fertilizer and energy input had the largest value in producing 1 kg lettuce, the amount of pesticide input the smallest. The amount of electricity input was the largest in all farms except farm 1 which purchased seedlings from outside. The quantity of direct field emission of $CO_2$, $CH_4$ and $N_2O$ from farm 1 to farm 5 were 6.79E-03 (farm 1), 8.10E-03 (farm 2), 1.82E-02 (farm 3), 7.51E-02 (farm 4) and 1.61E-02 (farm 5) kg $kg^{-1}$ lettuce, respectively. According to the result of LCI analysis focused on GHG, it was observed that $CO_2$ emission was 2.92E-01 (farm 1), 3.76E-01 (farm 2), 4.11E-01 (farm 3), 9.40E-01 (farm 4) and $5.37E-01kg\;CO_2\;kg^{-1}\;lettuce$ (farm 5), respectively. Carbon dioxide contribute to the most GHG emission. Carbon dioxide was mainly emitted in the process of energy production, which occupied 67~91% of $CO_2$ emission from every production process from 5 farms. Due to higher proportion of $CO_2$ emission from production of compound fertilizer in conventional crop system, conventional crop system had lower proportion of $CO_2$ emission from energy production than organic crop system did. With increasing inorganic fertilizer input, the process of lettuce cultivation covered higher proportion in $N_2O$ emission. Therefore, farms 1 and 2 covered 87% of total $N_2O$ emission; and farm 3 covered 64%. The carbon footprints from farm 1 to farm 5 were 3.40E-01 (farm 1), 4.31E-01 (farm 2), 5.32E-01 (farm 3), 1.08E+00 (farm 4) and 6.14E-01 (farm 5) kg $CO_2$-eq. $kg^{-1}$ lettuce, respectively. Results of sensitivity analysis revealed the soybean meal was the most sensitive among 4 types of fertilizer. The value of compound fertilizer was the least sensitive among every fertilizer imput. Electricity showed the largest sensitivity on $CO_2$ emission. However, the value of $N_2O$ variation was almost zero.

• Journal of Climate Change Research
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• v.3 no.3
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• pp.195-209
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• 2012

There are four differentiated levels to quantify the amount of greenhouse gas emissions from a facility, which are Tier 1 to 4 based on the IPCC guidelines. In this study, the emission estimates from all tier levels were calculated to compare their total $CO_2$ emission results among themselves for seven facilities, including three sectors of electricity generation, municipal solid waste incineration, and cement manufacturing for three months between February and May 2011. Generally the measured $CO_2$ emissions by Tier 4 were higher than the calculated $CO_2$ emissions by Tier 3, which had been also observed for the power plants in the USA. It was found out that to obtain more reliable estimation for Tier 3, accurate analysis of the composition of the fuel used should be carried out. It was suggested that further refinement on the administrative guidelines be made to make it more robust.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1053-1065
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• 2019

Land use statistics calculation is very informative data as the activity data for calculating exact carbon absorption and emission in post-2020. To effective interpretation by land use category, This study classify automatically image interpretation by land use category applying forest aerial photography (FAP) to deep learning model and calculate national unit statistics. Dataset (DS) applied deep learning is divided into training dataset (training DS) and test dataset (test DS) by extracting image of FAP based national forest resource inventory permanent sample plot location. Training DS give label to image by definition of land use category and learn and verify deep learning model. When verified deep learning model, training accuracy of model is highest at epoch 1,500 with about 89%. As a result of applying the trained deep learning model to test DS, interpretation classification accuracy of image label was about 90%. When the estimating area of classification by category using sampling method and compare to national statistics, consistency also very high, so it judged that it is enough to be used for activity data of national GHG (Greenhouse Gas) inventory report of LULUCF sector in the future.

• Spatial Information Research
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• v.20 no.1
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• pp.71-80
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• 2012

Carbon Point system is Climate Change Action Program by providing incentives in proportion to voluntary reduction of energy consumption such as electricity, gas and water for houses, commercial facilities. So far, existing researches have been limited to construction of GHG(Green House Gas) Inventory and have little attention to empirical impact analysis on carbon reduction policy regarding the residential section. Therefore, this paper is intended to provide convincing findings of impact analysis on carbon reduction, revolving around the carbon point system. For this, we firstly calculated the carbon emission by using electricity and gas usage data in household targeting to Seongbuk-Gu. Carrying out IPA and spatio-temporal analysis. Then, we are capable of visualizing spatial patterns from 2007 to 2009 as a macro analysis. Following that, we explored the effect on carbon point system through Ex ante-Ex post Analysis by paired t-test. To conclude, we can spatially identify the distribution with a significant difference between carbon emissions according to energy use as a micro analysis by Hot Spot to Analysis on point entities. It is to be hoped that this method will be utilized to establish various policies and to evaluate the effect of reduction of GHG.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.904-910
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• 2010

LCA (Life Cycle Assessment) carried out to estimate carbon footprint and to establish of LCI (Life Cycle Inventory) database of pepper production system. Pepper production system was categorized the field cropping (redpepper) and the greenhouse cropping (greenpepper) according to pepper cropping type. The results of collecting data for establishing LCI D/B showed that input of fertilizer for redpepper production was more than that for greenpepper production system. The value of fertilizer input was 2.55E+00 kg $kg^{-1}$ redpepper and 7.74E-01 kg $kg^{-1}$ greenpepper. Amount of pesticide input were 5.38E-03 kg $kg^{-1}$ redpepper and 2.98E-04 kg $kg^{-1}$ greenpepper. The value of field direct emission ($CO_2$, $CH_4$, $N_2O$) were 5.84E-01 kg $kg^{-1}$ redpepper and 2.81E+00 greenpepper, respectively. The result of LCI analysis focussed on the greenhouse gas (GHG), it was observed that the values of carbon footprint were 4.13E+00 kg $CO_2$-eq. $kg^{-1}$ for redpepper and 4.70E+00 kg $CO_2$-eq. $kg^{-1}$ for greenpepper; especially for 90% and 6% of $CO_2$ emission from fertilizer and pepper production, respectively. $N_2O$ was emitted from the process of N fertilizer production (76%) and pepper production (23%). The emission value of $CO_2$ from greenhouse production was more higher than it of field production system. The result of LCIA (Life Cycle Impact Assessment) was showed that characterization of values of GWP (Global Warming Potential) were 4.13E+00 kg $CO_2$-eq. $kg^{-1}$ for field production system and 4.70E+00 kg $CO_2$-eq. $kg^{-1}$ for greenhouse production system. It was observed that the process of fertilizer production might be contributed to approximately 52% for redpepper production system and 48% for greenpepper production system of GWP.