• Korean Journal of Soil Science and Fertilizer
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• v.43 no.5
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• pp.722-727
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• 2010

This study was conducted to estimate the carbon footprint and to establish the database of the LCI (Life Cycle Inventory) for barely cultivation system. Barley production system was separated into the naked barley, the hulled barley and the two-rowed barley according to type of barley species. Based on collecting the data for operating LCI, it was shown that input of fertilizer was the highest value of 9.52E-01 kg $kg^{-1}$ for two-rowed braley. For LCI analysis focussed on the greenhouse gas (GHG), it was observed that carbon footprint were 1.25E+00 kg $CO_2$-eq. $kg^{-1}$ naked braley, 1.09E+00 kg $CO_2$-eq. $kg^{-1}$ hulled braley and 1.71E+00 $CO_2$-eq. $kg^{-1}$ two-rowed barley; especially two-rowed barley cultivation system had highest emission value as 1.09E+00 kg $CO_2$ $kg^{-1}$ barley. It might be due to emit from mainly fertilizer production for barley cultivation. Also $N_2O$ was emitted at 7.55E-04 kg $N_2O\;kg^{-1}$ barley as highest value from hulled barley cultivation system because of high N fertilizer input. The result of life cycle impcat assessment (LCIA), it was observed that most of carbon emission from barely cultivation system was mainly attributed to fertilizer production and cropping unit. Characterization value of GWP was 1.25E+00 (naked barley), 1.09E+00 (hulled barley) and 1.71E+00 (two-rowed barely) kg $CO_2$-eq. $kg^{-1}$, respectively.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.5
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• pp.705-715
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• 2010

The adoption of carbon foot print system is being activated mostly in the developed countries as one of the long-term response towards tightened up regulations and standards on carbon emission in the agricultural sector. The Korean Ministry of Environment excluded the primary agricultural products from the carbon foot print system due to lack of LCI (life cycle inventory) database in agriculture. Therefore, the research on and establishment of LCI database in the agriculture for adoption of carbon foot print system is urgent. Development of LCA (life cycle assessment) methodology for application of LCA to agricultural environment in Korea is also very important. Application of LCA methodology to agricultural environment in Korea is an early stage. Therefore, this study was carried out to find out the effect of lettuce cultivation on agricultural environment by establishing LCA methodology. Data collection of agricultural input and output for establishing LCI was carried out by collecting statistical data and documents on income from agro and livestock products prepared by RDA. LCA methodology for agriculture was reviewed by investigating LCA methodology and LCA applications of foreign countries. Results based on 1 kg of lettuce production showed that inputs including N, P, organic fertilizers, compound fertilizers and crop protectants were the main sources of major emission factor during lettuce cropping process. The amount of inputs considering the amount of active ingredients was required to estimate the actual quantity of the inputs used. Major emissions due to agricultural activities were $N_2O$ (emission to air) and ${NO_3}^-$/${PO_4}^-$ (emission to water) from fertilizers, organic compounds from pesticides and air pollutants from fossil fuel combustion in using agricultural machines. The softwares for LCIA (life cycle impact assessment) and LCA used in Korea are 'PASS' and 'TOTAL' which have been developed by the Ministry of Knowledge Economy and the Ministry of Environment. However, the models used for the softwares are the ones developed in foreign countries. In the future, development of models and optimization of factors for characterization, normalization and weighting suitable to Korean agricultural environment need to be done for more precise LCA analysis in the agricultural area.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.6
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• pp.1157-1163
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• 2012

This study was performed a comparative life cycle assessment (LCA) among three rice production systems in order to analyze the difference of greenhouse gases (GHGs) emissions and environment impacts. Its life cycle inventory (LCI) database (DB) was established using data obtained from interview with conventional, without agricultural chemical and organic farming at Gunsan and Iksan, Jeonbuk province in 2011. According to the result of LCI analysis, $CO_2$ was mostly emitted from fertilizer production process and rice cropping phase. $CH_4$ and $N_2O$ were almost emitted from rice cultivation phase. The value of carbon footprint to produce 1 kg rice (unhulled) on conventional rice production system was 1.01E+00 kg $CO_2$-eq. $kg^{-1}$ and it was the highest value among three rice production systems. The value of carbon footprints on without agricultural chemical and organic rice production systems were 5.37E-01 $CO_2$-eq. $kg^{-1}$ and 6.58E-01 $CO_2$-eq. $kg^{-1}$, respectively. Without agricultural chemical rice production system whose input amount was the smallest had the lowest value of carbon footprint. Although the yield of rice from organic farming was the lowest, its value of carbon footprint less than that of conventional farming. Because there is no compound fertilizer inputs in organic farming. Compound fertilizer production and methane emission during rice cultivation were the main factor to GHGs emission in conventional and without agricultural chemical rice production systems. In organic rice production system, the main factors to GHGs emission were using fossil fuel on machine operation and methane emission from rice paddy field.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.1
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• pp.35-44
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• 2015

Forests contain a huge amount of carbon (C) and climate change could affect forest C dynamics. This study was conducted to predict the C dynamics of Pinus densiflora and Quercus variabilis forests, which are the most dominant needleleaf and broadleaf forests in Korea, using the Korean Forest Soil Carbon (KFSC) model under the two climate change scenarios (2012-2100; Constant Temperature (CT) scenario and Representative Concentration Pathway (RCP) 8.5 scenario). To construct simulation unit, the forest land areas for those two species in the 5th National Forest Inventory (NFI) data were sorted by administrative district and stand age class. The C pools were initialized at 2012, and any disturbance was not considered during the simulation period. Although the forest C stocks of two species generally increased over time, the forest C stocks under the RCP 8.5 scenario were less than those stocks under the CT scenario. The C stocks of P. densiflora forests increased from 260.4 Tg C in 2012 to 395.3 (CT scenario) or 384.1 Tg C (RCP 8.5 scenario) in 2100. For Q. variabilis forests, the C stocks increased from 124.4 Tg C in 2012 to 219.5 (CT scenario) or 204.7 (RCP 8.5 scenario) Tg C in 2100. Compared to 5th NFI data, the initial value of C stocks in dead organic matter C pools seemed valid. Accordingly, the annual C sequestration rates of the two species over the simulation period under the RCP 8.5 scenario (65.8 and $164.2g\;C\;m^{-2}\;yr^{-1}$ for P. densiflora and Q. variabilis) were lower than those values under the CT scenario (71.1 and $193.5g\;C\;m^{-2}\;yr^{-1}$ for P. densiflora and Q. variabilis). We concluded that the C sequestration potential of P. densiflora and Q. variabilis forests could be decreased by climate change. Although there were uncertainties from parameters and model structure, this study could contribute to elucidating the C dynamics of South Korean forests in future.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.6
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• pp.1185-1194
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• 2011

This study was carried out to estimate carbon emission using LCA (Life Cycle Assessment) and to establish LCI (Life Cycle inventory) DB for lettuce production system in protected cultivation. The results of data collection for establishing LCI DB showed that the amount of fertilizer input for 1 kg lettuce production was the highest. The amounts of organic and chemical fertilizer input for 1 kg lettuce production were 7.85E-01 kg and 4.42E-02 kg, respectively. Both inputs of fertilizer and energy accounted for the largest share. The amount of field emission for $CO_2$, $CH_4$ and $N_2O$ for 1 kg lettuce production was 3.23E-02 kg. The result of LCI analysis focused on GHG (Greenhouse gas) showed that the emission value to produce 1 kg of lettuce was 8.65E-01 kg $CO_2$. The emission values of $CH_4$ and $N_2O$ to produce 1 kg of lettuce were 8.59E-03 kg $CH_4$ and 2.90E-04 kg $N_2O$, respectively. Fertilizer production process contributed most to GHG emission. Whereas, the amount of emitted nitrous oxide was the most during lettuce cropping stage due to nitrogen fertilization. When GHG was calculated in $CO_2$-equivalents, the carbon footprint from GHG was 1.14E-+00 kg $CO_2$-eq. $kg^{-1}$. Here, $CO_2$ accounted for 76% of the total GHG emissions from lettuce production system. Methane and nitrous oxide held 16%, 8% of it, respectively. The results of LCIA (Life Cycle Impact assessment) showed that GWP (Global Warming Potential) and POCP (Photochemical Ozon Creation Potential) were 1.14E+00 kg $CO_2$-eq. $kg^{-1}$ and 9.45E-05 kg $C_2H_4$-eq. $kg^{-1}$, respectively. Fertilizer production is the greatest contributor to the environmental impact, followed by energy production and agricultural material production.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.892-897
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• 2010

LCA (Life Cycle assessment) was carried out to estimate on carbon footprint and to establish of LCI (Life Cycle Inventory) database of sweetpotato production system. Based on collecting the data for operating LCI, it was shown that input of organic fertilizer was value of 3.26E-01 kg $kg^{-1}$ and it of mineral fertilizer was 1.02E-01 kg $kg^{-1}$ for sweetpotato production. It was the highest value among input for sweetpotato production. And direct field emission was 2.47E-02 kg $kg^{-1}$ during sweetpotato cropping. The result of LCI analysis focussed on greenhouse gas (GHG) was showed that carbon footprint was 4.05E-01 kg $CO_2$-eq. $kg^{-1}$ sweetpotato. Especially $CO_2$ for 71% of the GHG emission and the value was 2.88E-01 kg $CO_2$-eq. $kg^{-1}$ sweetpotato. Of the GHG emission $CH_4$, and $N_2O$ were estimated to be 18% and 11%, respectively. It might be due to emit from mainly fertilizer production (32%) and sweetpotato cultivation (28%) for sweetpotato production system. $N_2O$ emitted from sweetpotato cultivation for 90% of the GHG emission. With LCIA (Life Cycle Impact Assessment) for sweetpotato production system, it was observed that the process of fertilizer production might be contributed to approximately 90% of GWP (global warming potential). Characterization value of GWP and POCP were 4.05E-01 $CO_2$-eq. $kg^{-1}$ and 5.08E-05 kg $C_2H_4$-eq. $kg^{-1}$, respectively.

• 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.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.898-903
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• 2010

This study was carried out to estimate carbon emission using LCA (Life Cycle Assessment) and to establish LCI (Life Cycle Inventory) database of soybean production system. Based on collecting the data for operating LCI, it was shown that input of organic fertilizer was value of 3.10E+00 kg $kg^{-1}$ soybean and it of mineral fertilizer was 4.57E-01 kg $kg^{-1}$ soybean for soybean cultivation. It was the highest value among input for soybean production. And direct field emission was 1.48E-01 kg $kg^{-1}$ soybean during soybean cropping. The result of LCI analysis focussed on greenhouse gas (GHG) was showed that carbon footprint was 3.36E+00 kg $CO_2$-eq $kg^{-1}$ soybean. Especially $CO_2$ for 71% of the GHG emission. Also of the GHG emission $CH_4$, and $N_2O$ were estimated to be 18% and 11%, respectively. It might be due to emit from mainly fertilizer production (92%) and soybean cultivation (7%) for soybean production system. $N_2O$ was emitted from soybean cropping for 67% of the GHG emission. In $CO_2$-eq. value, $CO_2$ and $N_2O$ were 2.36E+00 kg $CO_2$-eq. $kg^{-1}$ soybean and 3.50E-01 kg $CO_2$-eq. $kg^{-1}$ soybean, respectively. With LCIA (Life Cycle Impact Assessment) for soybean production system, it was observed that the process of fertilizer production might be contributed to approximately 90% of GWP (global warming potential). Characterization value of GWP was 3.36E+00 kg $CO_2$-eq $kg^{-1}$.

• 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 Korean Society of Forest Science
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• v.112 no.4
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• pp.426-441
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• 2023

This study investigated the predictive accuracy of a model of landslide displacement in Jecheon-si, where a great number of landslides were triggered by heavy rain on both natural (non-clear-cut) and clear-cut slopes during August 2020. This was accomplished by applying three flow direction methods (single flow direction, SFD; multiple flow direction, MFD; infinite flow direction, IFD) and the degree of root cohesion to an infinite slope stability equation. The application assumed that the soil saturation and any changes in root cohesion occurred following the timber harvest (clear-cutting). In the study area, 830 landslide locations were identified via landslide inventory mapping from satellite images and 25 cm resolution aerial photographs. The results of the landslide modeling comparison showed the accuracy of the models that considered changes in the root cohesion following clear-cutting to be improved by 1.3% to 2.6% when compared with those not considered in the area under the receiver operating characteristics (AUROC) analysis. Furthermore, the accuracy of the models that used the MFD algorithm improved by up to 1.3% when compared with the models that used the other algorithms in the AUROC analysis. These results suggest that the discriminatory application of the root cohesion, which considers changes in the vegetation condition, and the selection of the flow direction method may influence the accuracy of landslide predictive modeling. In the future, the results of this study should be verified by examining the root cohesion and its dynamic changes according to the tree species using the field hydrological monitoring technique.