So, Kyu-Ho;Lee, Gil-Zae;Kim, Gun-Yeob;Jeong, Hyun-Cheol;Ryu, Jong-Hee;Park, Jung-Ah;Lee, Deog-Bae
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 $kg^{-1}$.
The issue of acid precipitation and related environmental problems in East Asia has been emerging. To evaluate the acidity and chemical characteristics of rainwater in Korea, its chemical properties during cultivation season from April to October were investigated at Taean in 2007. Also, to estimate the contribution of ions on its acidity, ion composition characteristics and neutralization effects by cation ions were determined. The ion balance between cations and anions values showed high correlation. The mean values of pH and EC were 4.9 and $32.9{\mu}S\;cm^{-1}$, respectively. The EC of rainwater showed seasonal characteristic, which was $91.4{\mu}S\;cm^{-1}$ with relatively low rainfall compared with other monitoring periods. $Na^+$ was the main cation followed by $NH_4{^+}$ > $Ca^{2+}$ > $H^{+}$ > $Mg^{2+}$ > $K^+$. Among these ions, $Na^{+}$ and $NH_4{^+}$ covered over 70% of total cations. In the case of anion, the order was $SO_4{^{2-}}$ > $NO_3{^-}$ > $Cl^{-}$. The mean value of sulfate, which is main anion component in the samples was $152.1{\mu}eq\;L^{-1}$. Also, 90% of soluble sulfate in rainwater was $nss-SO_4{^{2-}}$(non-sea salt sulfate). With fractional acidity and theoretical acidity of rainwater samples, $NH_4{^+}$ and $Ca^{2+}$ contributed greatly in neutralizing the rain acidity.
In Seongju, Gyengsangbuk-do, the Placenta Chamber (胎室, Taesil) of 18 sons and a son of the crown prince of King Sejong(世宗大王) is located in one place. Taesil refers to the place where the umbilical cord and placenta, which are separated when the baby is born, are placed in a jar made of pottery and stone box and then buried on the ground. The placenta chamber in Seongju has the Buncheong ware (粉靑沙器) cover buried on the ground to protect the baby's placenta. These covers are all hemispherical, with a diameter of more the 20cm. The decorations were made using black and white inlaid techniques only on the outside. The Buncheong ware cover with this shape and pattern has been confirmed only in the placenta chamber in Seongju. This study targets 6 of the Buncheong ware cover whose owners were identified, when and where they were prepared, what the stylistic features and meanings are, and where it was produced. The results of the study are as follows. First, ss a result of reviewing the production background and procurement system of this bowl, it was inferred that it was sourced from Jangheunggo (長興庫) at the central government office, between 1436 and 1439, when the event to bury the placenta of royal members in the ground was the most active. Second, it analyzed the unique features of this cover, such as the shape, pattern, and baked traces. The shape and pattern were compared to the ritual objects contained in the Sejong Silok Oryeui (『世宗實錄』 「五禮」, Five Rites of King Sejong Chronicle) and the lid of the royal placenta jar made in the 15th and 16th centuries. Third, this study suggests that the baking method was based on the shape and location of the traces remaining outside the cover. Finally, the following data were used to estimate the production site: the relationship with the 'Jagiso (磁器所, ceramic workshop) registered in the Sejong Silok Jiriji (『世宗實錄』 「地理志」, Geographical Appendix of King Sejong Chronicle); various records of contribution and dedication about the Buncheong ware made here; and the Buncheong ware and related tools excavated from the kiln site in the area. The place where the Buncheong ware cover was produced is estimated to be the most likely production site for the kiln site in Chunghyo-dong Kiln Site, located in Jeolla-do province by synthesizing the data above.
Rapid climate change and oceanic warming have increased the variability of oceanic wave heights over the past several decades. In addition, the extreme wave heights, such as the upper 1% (or 5%) wave heights, have increased more than the heights of the normal waves. This is true for waves both in global oceans as well as in local seas. Satellite altimeters have consistently observed significant wave heights (SWHs) since 1991, and sufficient SWH data have been accumulated to investigate 100-year return period SWH values based on statistical approaches. Satellite altimeter data were used to estimate the extreme SWHs at the Ieodo Ocean Research Station (IORS) for the period from 2005 to 2016. Two representative extreme value analysis (EVA) methods, the Initial Distribution Method (IDM) and Peak over Threshold (PoT) analysis, were applied for SWH measurements from satellite altimeter data and compared with the in situ measurements observed at the IORS. The 100-year return period SWH values estimated by IDM and PoT analysis using IORS measurements were 8.17 and 14.11 m, respectively, and those using satellite altimeter data were 9.21 and 16.49 m, respectively. When compared with the maximum value, the IDM method tended to underestimate the extreme SWH. This result suggests that the extreme SWHs could be reasonably estimated by the PoT method better than by the IDM method. The superiority of the PoT method was supported by the results of the in situ measurements at the IORS, which is affected by typhoons with extreme SWH events. It was also confirmed that the stability of the extreme SWH estimated using the PoT method may decline with a decrease in the quantity of the altimeter data used. Furthermore, this study discusses potential limitations in estimating extreme SWHs using satellite altimeter data, and emphasizes the importance of SWH measurements from the IORS as reference data in the East China Sea to verify satellite altimeter data.
Kim, Yongwon;Byeon, Sangdon;Park, Jinseok;Woo, Soyoung;Kim, Seongjoon
Journal of Korea Water Resources Association
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v.54
no.10
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pp.819-833
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2021
This study is to evaluate applicability of linkage modeling using PHABSIM (Physical Habitat Simulation System) and SWAT (Soil and Water Assessment Tool) and to estimate ecological flow for target fishes of Andong downstream (4,565.7 km2). The SWAT was established considering 2 multi purpose dam (ADD, IHD) and 1 streamflow gauging station (GD). The SWAT was calibrated and validated with 9 years (2012 ~ 2020) data of 1 stream (GD) and 2 multi-purpose dam (ADD, IHD). For streamflow and dam inflows (GD, ADD and IHD), R2, NSE and RMSE were 0.52 ~ 0.74, 0.48 ~ 0.71, and 0.92 ~ 2.51 mm/day respectively. As a result of flow duration analysis for 9 years (2012 ~ 2020) using calibrated streamflow, the average Q185 and Q275 were 36.5 m3/sec (-1.4%) and 23.8 m3/sec (0%) respectively compared with the observed flow duration and were applied to flow boundary condition of PHABSIM. The target stream was selected as the 410 m section where GD is located, and stream cross-section and hydraulic factors were constructed based on Nakdong River Basic Plan Report and HEC-RAS. The dominant species of the target stream was Zacco platypus and the sub-dominant species was Puntungia herzi Herzenstein, and the HSI (Habitat Suitability Index) of target species was collected through references research. As the result of PHABSIM water level and velocity simulation, error of Q185 and Q275 were analyzed -0.12 m, +0.00 m and +0.06 m/s, +0.09 m/s respectively. The average WUA (Weighted Usable Area) and ecological flow of Zacco platypus and Puntungia herzi Herzenstein were evaluated 76,817.0 m2/1000m, 20.0 m3/sec and 46,628.6 m2/1000m, 9.0 m3/sec. This results indicated Zacco platypus is more adaptable to target stream than Puntungia herzi Herzenstein.
This study aimed to estimate the photosynthetic capacity of tomato plants grown in a semi-closed greenhouse using temperature response models of plant photosynthesis by calculating the ribulose 1,5-bisphosphate carboxylase/oxygenase maximum carboxylation rate (Vcmax), maximum electron transport rate (Jmax), thermal breakdown (high-temperature inhibition), and leaf respiration to predict the optimal conditions of the CO2-controlled greenhouse, for maximizing the photosynthetic rate. Gas exchange measurements for the A-Ci curve response to CO2 level with different light intensities {PAR (Photosynthetically Active Radiation) 200µmol·m-2·s-1 to 1500µmol·m-2·s-1} and leaf temperatures (20℃ to 35℃) were conducted with a portable infrared gas analyzer system. Arrhenius function, net CO2 assimilation (An), thermal breakdown, and daylight leaf respiration (Rd) were also calculated using the modeling equation. Estimated Jmax, An, Arrhenius function value, and thermal breakdown decreased in response to increased leaf temperature (> 30℃), and the optimum leaf temperature for the estimated Jmax was 30℃. The CO2 saturation point of the fifth leaf from the apical region was reached at 600ppm for 200 and 400µmol·m-2·s-1 of PAR, at 800ppm for 600 and 800µmol·m-2·s-1 of PAR, at 1000ppm for 1000µmol of PAR, and at 1500ppm for 1200 and 1500µmol·m-2·s-1 of PAR levels. The results suggest that the optimal conditions of CO2 concentration can be determined, using the photosynthetic model equation, to improve the photosynthetic rates of fruit vegetables grown in greenhouses.
Moon, Jong Pil;Bang, Ji Woong;Hwang, Jeongsu;Jang, Jae Kyung;Yun, Sung Wook
Journal of Bio-Environment Control
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v.30
no.4
/
pp.419-428
/
2021
In order to develope a mobile-based greenhouse energy calculation program, firstly, the overall thermal transmittance of 10 types of major covers and 16 types of insulation materials were measured. In addition, to estimate the overall thermal transmittance when the cover and insulation materials were installed in double or triple layers, 24 combinations of double installations and 59 combinations of triple installations were measured using the hotbox. Also, the overall thermal transmittance value for a single material and the thermal resistance value were used to calculate the overall thermal transmittance value at the time of multi-layer installation of covering and insulating materials, and the linear regression equation was derived to correct the error with the measured values. As a result of developing the model for estimating thermal transmittance when installing multiple layers of coverings and insulating materials based on the value of overall thermal transmittance of a single-material, the model evaluation index was 0.90 (good when it is 0.5 or more), indicating that the estimated value was very close to the actual value. In addition, as a result of the on-site test, it was evaluated that the estimated heat saving rate was smaller than the actual value with a relative error of 2%. Based on these results, a mobile-based greenhouse energy calculation program was developed that was implemented as an HTML5 standard web-based mobile web application and was designed to work with various mobile device and PC browsers with N-Screen support. It had functions to provides the overall thermal transmittance(heating load coefficient) for each combination of greenhouse coverings and thermal insulation materials and to evaluate the energy consumption during a specific period of the target greenhouse. It was estimated that an energy-saving greenhouse design would be possible with the optimal selection of coverings and insulation materials according to the region and shape of the greenhouse.
The 2nd Geostationary Ocean Color Imager (GOCI-II) is the successor to the Geostationary Ocean Color Imager (GOCI), which employs one near-ultraviolet wavelength (380 nm) and eight visible wavelengths(412, 443, 490, 510, 555, 620, 660, 680 nm) and three near-infrared wavelengths(709, 745, 865 nm) to observe the marine environment in Northeast Asia, including the Korean Peninsula. However, the multispectral radiance image observed at satellite altitude includes both the water-leaving radiance and the atmospheric path radiance. Therefore, the atmospheric correction process to estimate the water-leaving radiance without the path radiance is essential for analyzing the ocean environment. This manuscript describes the GOCI-II standard atmospheric correction algorithm and its initial phase validation. The GOCI-II atmospheric correction method is theoretically based on the previous GOCI atmospheric correction, then partially improved for turbid water with the GOCI-II's two additional bands, i.e., 620 and 709 nm. The match-up showed an acceptable result, with the mean absolute percentage errors are fall within 5% in blue bands. It is supposed that part of the deviation over case-II waters arose from a lack of near-infrared vicarious calibration. We expect the GOCI-II atmospheric correction algorithm to be improved and updated regularly to the GOCI-II data processing system through continuous calibration and validation activities.
This study was conducted to estimate annual trends and the environmental effects in the racing records of Jeju horses. The Korean Racing Authority (KRA) collected 48,645 observations for 2,167 Jeju horses from 2002 to 2019. Racing records were preprocessed to eliminate errors that occur during the data collection. Racing times were adjusted for comparison between race distances. A stepwise Akaike information criterion (AIC) variable selection method was applied to select appropriate environment variables affecting racing records. The annual improvement of the race time was -0.242 seconds. The model with the lowest AIC value was established when variables were selected in the following order: year, budam classification, jockey ranking, trainer ranking, track condition, weather, age, and gender. The most suitable model was constructed when the jockey ranking and age variables were considered as random effects. Our findings have potential for application as basic data when building models for evaluating genetic abilities of Jeju horses.
Variability is one of the major characteristics of Active Galactic Nuclei (AGN), and it is used for understanding the energy generation mechanism in the center of AGN and/or related physical phenomena. It it known that there exists a time lag between AGN light curves simultaneously observed at different wavelengths, which can be used as a tool to estimate the size of the area that produce the radiation. In this paper, We present long term near-infrared variability of optically bright type 1 AGN using the Wide-field Infrared Survey Explorer data. From the Milliquas catalogue v6.4, 73 type 1 QSOs/AGN and 140 quasar candidates are selected that are brighter than 18 mag in optical and located within 5 degree around the ecliptic poles. Light curves in the W1 band (3.4 ㎛) and W2 band (4.6 ㎛) during the period of 2010-2019 were constructed for these objects by extracting multi-epoch photometry data from WISE and NEOWISE all sky survey database. Variability was analyzed based on the excess variance and the probability Pvar. Applying both criteria, the numbers of variable objects are 19 (i.e., 26%) for confirmed AGN and 12 (i.e., 9%) for AGN candidates. The characteristic time scale of the variability (τ) and the variability amplitude (σ) were derived by fitting the DRW model to W1 and W2 light curves. No significant correlation is found between the W1/W2 magnitude and the derived variability parameters. Based on the subsample that are identified in the X-ray source catalog, there exists little correlation between the X-ray luminosity and the variability parameters. We also found four AGN with changing W1-W2 color.
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