• Journal of the Korea Institute of Building Construction
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• v.9 no.4
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• pp.63-73
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• 2009

Recently, the use of lightweight panels in building structures has been increasing. Of the various lightweight panel types, styrofoam sandwich panels are inexpensive and are excellent in terms of their insulation capacity and their constructability. However, sandwich panels that include organic material are quite vulnerable to fire, and thus can numerous casualties in the event of a fire due to the lack of time to vacate and their emission of poisonous gas. On the other hand, lightweight foamed concrete is excellent, both in terms of its insulation ability and its fire resistance, due to its Inner pores. The properties of lightweight concrete is influenced by foaming agent type. Accordingly, this study investigates the insulation properties by foaming agent type, to evaluate the possibility of using light-weight foamed concrete instead of styrene foam. Our research found thatnon-heating zone temperature of lightweight foamed concrete using AP (Aluminum Powder) and FP (animal protein foaming agent) are lower than that of light-weight foamed concrete using AES (alkyl ether lactic acid ester). Lightweight foamed concrete using AES and FP satisfied fire performance requirements of two hours at a foam ratio 50, 100. Lightweight foamed concrete using AP satisfied fire performance requirements of two hours at AP ratio 0.1, 0.15. The insulation properties were better in closed pore foamed concrete by made AP, FP than with open pore foamed concrete made using AES.

• Korean Journal of Environmental Agriculture
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• v.30 no.1
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• pp.24-30
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• 2011

BACKGROUND: High input to the arable land is contributed to increasing productivity with causing the global environmental problems at the same time. Rapeseed cultivation has been forced to reassess its positive point for utilization of winter fallow field. The Objective of this study was performed to assess the environmental impact of rapeseed cultivation with double-cropping system in paddy rice on Yeonggwang district using life cycle assessment technique. METHODS AND RESULTS: For assessing each stage of rapeseed cultivation, it was collected raw data for input materials as fertilizer and pesticide and energy consumption rate by analyzing the type of agricultural machinery and working hours by 1 ton rapeseed as functional unit. Environmental impacts were evaluated by using Eco-indicator 95 method for 8 impact categories. It was estimated that 216 kg $CO_2$-eq. for greenhouse gas, 3.98E-05 kg CFC-11-eq. for ozone lazer depletion, 1.78 kg SO2-eq. for acidification, 0.28 kg $PO_4$-eq. for eutrophication, 5.23E-03 kg Pb-eq. for heavy metals, 2.51E-05 kg B(a)p-eq. for carcinogens, 1.24 kg SPM-eq. for smog and 6,460 MJ LHV for energy resource are potentially emitted to produce 1 ton rapeseed during its whole cultivation period, respectively. It was considered that 90% of these potential came from chemical fertilizer. For the sensitivity analysis, by increasing the productivity of rapeseed by 1 ton per ha, potential environmental loading was reduced at 22%. CONCLUSION(s): Fertilization affected most dominantly to the environmental burden, originated from the preuse stage, i.e. fertilizer manufacturing and transporting. It should be included and assessed an indirect emission, which is not directly emitted from agricultural activities. Recycling resource in agriculture with reducing chemical fertilizer and breeding the high productive variety might be contribute to reduce the environmental loading for the rapeseed cultivation.

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.526-535
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• 2021

Spatial sampling design plays an important role in GIS-based modeling studies because it increases modeling efficiency while reducing the cost of sampling. In the field of agricultural systems, research demand for high-resolution spatial databased modeling to predict and evaluate climate change impacts is growing rapidly. Accordingly, the need and importance of spatial sampling design are increasing. The purpose of this study was to design spatial sampling of paddy fields (11,386 grids with 1 km spatial resolution) in Korea for use in agricultural spatial modeling. A stratified random sampling design was developed and applied in 2030s, 2050s, and 2080s under two RCP scenarios of 4.5 and 8.5. Twenty-five weather and four soil characteristics were used as stratification variables. Stratification and sample allocation were optimized to ensure minimum sample size under given precision constraints for 16 target variables such as crop yield, greenhouse gas emission, and pest distribution. Precision and accuracy of the sampling were evaluated through sampling simulations based on coefficient of variation (CV) and relative bias, respectively. As a result, the paddy field could be optimized in the range of 5 to 21 strata and 46 to 69 samples. Evaluation results showed that target variables were within precision constraints (CV<0.05 except for crop yield) with low bias values (below 3%). These results can contribute to reducing sampling cost and computation time while having high predictive power. It is expected to be widely used as a representative sample grid in various agriculture spatial modeling studies.