• Korean Journal of Soil Science and Fertilizer
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• v.45 no.6
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• pp.1143-1152
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• 2012

We established a top-down methodology to estimate carbon footprint as national mean value (reference) with the statistical data on agri-livestock incomes in 2007. We also established LCI (life cycle inventory) DB by a bottom-up methodology with the data obtained from interview with farmers from 4 large-scale farms at Gunsan, Jeollabuk-do province to estimate carbon footprint in 2011. This study was carried out to compare top-down methodology and bottom-up methodology in performing LCA (life cycle assessment) to analyze the difference in GHGs (greenhouse gases) emission and carbon footprint under conventional rice cultivation system. Results of LCI analysis showed that most of $CO_2$ was emitted during fertilizer production and rice cultivation, whereas $CH_4$ and $N_2O$ were mostly emitted during rice cultivation. The carbon footprints on conventional rice production system were 2.39E+00 kg $CO_2$-eq. $kg^{-1}$ by top-down methodology, whereas 1.04E+00 kg $CO_2$-eq. $kg^{-1}$ by bottom-up methodology. The amount of agro-materials input during the entire rice cultivation for the two methodologies was similar. The amount of agro-materials input for the bottom-up methodology was sometimes greater than that for top-down methodology. While carbon footprint by the bottom-up methodology was smaller than that by the top-down methodology due to higher yield per cropping season by the bottom-up methodology. Under the conventional rice production system, fertilizer production showed the highest contribution to the environmental impacts on most categories except GWP (global warming potential) category. Rice cultivation was the highest contribution to the environmental impacts on GWP category under the conventional rice production system. The main factors of carbon footprints under the conventional rice production system were $CH_4$ emission from rice paddy field, the amount of fertilizer input and rice yield. Results of this study will be used for establishing baseline data for estimating carbon footprint from 'low carbon certification pilot project' as well as for developing farming methods of reducing $CO_2$ emission from rice paddy fields.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.4
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• pp.162-173
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• 2009

Information on the expected geographical shift of suitable zones for growing crops under future climate is a starting point of adaptation planning in agriculture and is attracting much concern from policy makers as well as researchers. Few practical schemes have been developed, however, because of the difficulty in implementing the site-selection concept at an analytical level. In this study, we suggest site-selection criteria for quality Fuji apple production and integrate geospatial data and information available in public domains (e.g., digital elevation model, digital soil maps, digital climate maps, and predictive models for agroclimate and fruit quality) to implement this concept on a GIS platform. Primary criterion for selecting sites suitable for Fuji apple production includes land cover, topography, and soil texture. When the primary criterion is satisfied, climatic conditions such as the length of frost free season, freezing risk during the overwintering period, and the late frost risk in spring are tested as the secondary criterion. Finally, the third criterion checks for fruit quality such as color and shape. Land attributes related to these factors in each criterion were implemented in ArcGIS environment as relevant raster layers for spatial analysis, and retrieval procedures were automated by writing programs compatible with ArcGIS. This scheme was applied to the A1B projected climates for South Korea in the future normal years (2011-2040, 2041-2070, and 2071-2100) as well as the current climate condition observed in 1971-2000 for selecting the sites suitable for quality Fuji apple production in each period. Results showed that this scheme can figure out the geographical shift of suitable zones at landscape scales as well as the latitudinal shift of northern limit for cultivation at national or regional scales.

• 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 CROP SCIENCE
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• v.65 no.4
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• pp.346-352
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• 2020

Currently, many studies are being conducted to cope with climate changes due to global warming and abnormal weather. The objective of this study was to investigate the effects of weather on the growth, yield components, and quality of soybeans using weather data from 2017 and 2018. The average temperature in 2018 was higher than that in 2017 from R1 to R5 of the growth stage for all cultivars. On the other hand, precipitation in 2018 was reduced compared to that in 2017 for Daewon and Daepung-2ho. It was observed that the flowering date in 2018 was earlier than that in 2017 for Daewon and Daepung-2ho, but the flowering date for Pungsannamul in 2018 was similar to that in 2017. Simulating soil water content with the estimation model (AFKAE0.5) determined that there were fewer drought dates in 2017 than those in 2018, and drought lasted from R1 to early R5 of the growth stage in 2018. Soybean growth in 2017 was better than that in 2018, and seed yield and 100-seed weight of soybean were higher in 2017 than those in 2018 for all cultivars. The seed size in 2017 was larger than that in 2018 for all cultivars. Oil content in 2017 was higher than that in 2018; in particular, the difference between both years was observed for Daewon and Daepung-2ho. Protein content was higher in 2018 than that in 2017; however, there were different levels for each cultivar. Thus, these results indicate that the yield component and quality of soybeans are affected by high temperature and drought.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.63 no.2
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• pp.140-148
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• 2018

As the global warming causing desertification increase, there is growing concern about damage of crops. It was to investigate how the treatment with hydrogen peroxide before leaf development affects the growth and yield of sorghum for minimizing a damage of crops to drought. The germination experiment was conducted at alternating temperature of $25^{\circ}C/20^{\circ}C$(12 hr/12 hr) under water stress condition of 0 ~ -0.20 MPa adjusted with PEG solution containing 0 and 10 mM $H_2O_2$. In order to know the effect of foliar application of hydrogen peroxide on the growth of sorghum, 10 mM hydrogen peroxide was treated to leaves at 3-leaf stage of sorghum growing in greenhouse conditions. Seed germination rate was increased by 20% in hydrogen peroxide treatment as compared to the Control. under water stress conditions (-0.15 ~ -0.20 MPa). The length of seedlings was also on the rise by the hydrogen peroxide treatment. In the greenhouse pot experiment, the morphological characteristics (plant height, stem diameter, leaf length, and leaf number) and physiological characteristics (chlorophyll content, chlorophyll fluorescence (Fv/Fm), stomatal conductance) were higher in the plants treated with hydrogen peroxide under the drought stress condition than those of plants of $H_2O$ treatment. Experiment conducted with the soil moisture gradient system showed that the foliar application of hydrogen peroxide increased photosynthetic ability of sorghum plant with respect to SPAD value and stomatal conductance and rooting capacity (root weight and root length) under drought condition. Generally, hydrogen peroxide treatment in sorghum increased the tolerance to drought stress and maintained better growth due to ameliorating oxidative stress.

• The Journal of Engineering Geology
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• v.33 no.2
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• pp.275-291
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• 2023

Global warming has made the polar regions more accessible, leading to increased demand for the construction of new resource-development plants in oil-rich permafrost regions. The selection of locations of resource-development plants in permafrost regions should consider the surface displacement resulting from thawing and freezing of the active layer of permafrost. However, few studies have considered surface displacement in the selection of optimal locations of resource-development plants in permafrost region. In this study, Analytic Hierarchy Process (AHP) analysis using a range of geospatial information variables was performed to select optimal locations for the construction of oil-sands development plants in the permafrost region of southern Athabasca, Alberta, Canada, including consideration of surface displacement. The surface displacement velocity was estimated by applying the Small BAseline Subset Interferometric Synthetic Aperture Radar technique to time-series Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar images acquired from February 2007 to March 2011. ERA5 reanalysis data were used to generate geospatial data for air temperature, surface temperature, and soil temperature averaged for the period 2000~2010. Geospatial data for roads and railways provided by Statistics Canada and land cover maps distributed by the North American Commission for Environmental Cooperation were also used in the AHP analysis. The suitability of sites analyzed using land cover, surface displacement, and road accessibility as the three most important geospatial factors was validated using the locations of oil-sand plants built since 2010. The sensitivity of surface displacement to the determination of location suitability was found to be very high. We confirm that surface displacement should be considered in the selection of optimal locations for the construction of new resource-development plants in permafrost regions.