• Journal of Korean Society of Forest Science
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• v.84 no.3
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• pp.277-285
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• 1995

This study was conducted to understand the relationship between climatic factors and matsutake(Tricholoma matsutake) mushroom production. Data on local annual matsutake production collected from 29 locations from 1984 to 1993 were analyzed for stepwise and multiple regression with local climatic data, such as monthly maximum, minimum, and average air temperature, soil temperature, relative humidity, amount of rainfall, and number of rainy days. Correlation between monthly climatic factors and annual matsutake production was calculated in each location(Case 1), each year(Case 2), and each month(Case 3). In Case 1, number of rainy days and minimum temperature in Sep. showed positive correlation with matsutake production. In Case 2, maximum, minimum, and average temperature in June showed negative correlation with matsutake production. In Case 3, amount of precipitation in Sep. and Oct. number of rainy days in Sep., and minimum temperature in Sep. and Oct. showed positive correlation with matsutake production. In conclusion, amount of rainfall and number of rainy days in Sep. were the most important climatic factors and correlated positively with matsutake production. Below average air temperature in June was also beneficial for matsutake production.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.9
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• pp.518-525
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• 2018

In the 21st century, human beings are becoming increasingly concerned about greenhouse gas emissions as the environment changes due to climate change become serious. The temperature of Korea has risen by approximately $1.5^{\circ}C$ from 1904 to 2000, and the climate is changing gradually to a subtropical climate. As a result, the frequency of floods and droughts increases, so that the water available to humans is decreasing every year, and the cost of using city water is rising every year. The reuse of wastewater that is normally abandoned is inevitable. This study examined the monthly data for 6 months of operation by installing a reuse system of concentrated wastewater (Re R/O System) that is generated during the process of manufacturing de-ionized water (DI-Water System) used in semiconductor processing. As a result of the survey, the city water supply saved approximately $2,767m^3$ per month. The average annual greenhouse gas emissions was $1,329.07kg-CO_2$ per month due to the electricity consumption of the water reuse system. On the other hand, because of the reduction in city water supply, the average monthly average of $918.64kg-CO_2$ was reduced, and the greenhouse gas emissions were increased to $410.43kg-CO_2$ per month. If it improves some processes in the water reuse system, the amount of greenhouse gas emissions can be reduced by an average of $254.41kg-CO_2$ per month.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.25-30
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• 2016

It is critical to forecast the maximum daily and monthly demand for power with as little error as possible for our industry and national economy. In general, long-term forecasting of power demand has been studied from both the consumer's perspective and an econometrics model in the form of a generalized linear model with predictors. Time series techniques are used for short-term forecasting with no predictors as predictors must be predicted prior to forecasting response variables and containing estimation errors during this process is inevitable. In previous researches, seasonal exponential smoothing method, SARMA (Seasonal Auto Regressive Moving Average) with consideration to weekly pattern Neuron-Fuzzy model, SVR (Support Vector Regression) model with predictors explored through machine learning, and K-means clustering technique in the various approaches have been applied to short-term power supply forecasting. In this paper, SARMA and intervention model are fitted to forecast the maximum power load daily, weekly, and monthly by using the empirical data from 2011 through 2013. $ARMA(2,\;1,\;2)(1,\;1,\;1)_7$ and $ARMA(0,\;1,\;1)(1,\;1,\;0)_{12}$ are fitted respectively to the daily and monthly power demand, but the weekly power demand is not fitted by AREA because of unit root series. In our fitted intervention model, the factors of long holidays, summer and winter are significant in the form of indicator function. The SARMA with MAPE (Mean Absolute Percentage Error) of 2.45% and intervention model with MAPE of 2.44% are more efficient than the present seasonal exponential smoothing with MAPE of about 4%. Although the dynamic repression model with the predictors of humidity, temperature, and seasonal dummies was applied to foretaste the daily power demand, it lead to a high MAPE of 3.5% even though it has estimation error of predictors.

• Journal of the Korean Solar Energy Society
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• v.37 no.2
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• pp.35-45
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• 2017

The types of installation of the photovoltaic system applied to domestic residential buildings are classified as follows: Mounted modules with air circulation, semi-integrated modules with air duct behind, integrated modules with fully insulated back. In order to study generation characteristics of PV system, we verified the validity of interpretation program based on long-term measurement data of demonstration house installed in BAPV form and also analyzed the generation characteristics and performance of each installation type. The results are as follows. First, the RMSE of amount of generation and simulation according to annual daily insolation of demonstration system located in Daejeon was 0.98kWh and the range of relative error of monthly power generation was -5.8 to 3.1. Second, the average annual PR of mounted modules was 82%, semi-integrated modules 76.1% and integrated modules 71.9%. This differences were attributed to temperature loss. Third, the range of operating temperature of annual hourly photovoltaic modules was -6.5 to $61.0^{\circ}C$ for mounted modules, $-6.0{\sim}73.9^{\circ}C$ for semi-integrated modules and -5.5 to $88.9^{\circ}C$ for integrated modules. The temperature loss of each installation type was -14.0 to 16.1%, -13.8 to 21.9%, and -13.6 to 28.5%, respectively.

• Journal of Bio-Environment Control
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• v.9 no.2
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• pp.107-114
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• 2000

We constructed climagraphs for 16 regions of Korea by using the average monthly minimum air temperature, maximum air temperature and global radiation. We characterized the outside climate requirements corresponding to the climate requirements of crops in greenhouses. The climagraphs allow to decide the appropriate climate periods for greenhouse cultivation without heating and cooling equipment. These graphs may be used for analyzing climatic characteristic of a given area, selecting the suitable region and greenhouse and making a rational plan for greenhouse cropping in Korea. We found difficulty in deciding the beginning and end of greenhouse heating and cooling period due to insufficient references.

• Journal of the Korean Solar Energy Society
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• v.36 no.6
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• pp.25-35
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• 2016

In this study, the evaluation of the dynamic behavior and thermal performance of the "Façade integrated Natural circulation Solar Water Heating System" installed in the residential house was carried out. Experimental tests were performed during the all year around in the rural houses of $166m^2$ in size. Facade integrated solar collector of $5m^2$ were installed on the south-facing. Electrical heater of 1 kW capacity as an auxiliary heater was installed at the upper part of the heat storage tank. The analyzing results are as follows. (1) Monthly average solar fraction was 51 to 87% and yearly average value is 64%. (2) Hot water supply temperature in December which has the lowest solar altitude is 37 to $76^{\circ}C$. The highest working fluid temperature of solar collector in this period was below $84^{\circ}C$. The temperature difference of working fluid between the collector inlet and outlet has been shown to be around 9 to $26^{\circ}C$. (3) Overheating which is one of the biggest problems during summer did not appear at all, but rather had hot water supply temperature is rather low as $30{\sim}47^{\circ}C$ in summer than winter, which is supplied by a small solar load. The solar collecting temperature has been shown to maintain below $55^{\circ}C$. (5) The thermal performance of Facade integrated solar collector can be increase due to the reduction of heat loss to the back of the collector wall integration of the collector is reduced. As a conclusion, Facade integrated natural circulation type Solar Water Heating System is a well-functioning without any pumps or controllers, and it was found that the disadvantages of conventional solar water heaters, hot water or hot water system can be greatly improved.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.40 no.4
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• pp.444-450
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• 1995

It was very hard to gather the seeds of Eleutherococcus senticosus Max. known as a medicinal plant for they tend to drop under the high temperature condition during the summer period in Korea. Therefore, this study was conducted to select seed production site for Eleutherococcus senticosus in Korea, comparing the climate of Hokkaido of Japan, in which the seeds have been produced, with that of various place in this country. It was low that the average maximum temperature during the hottest summer two months (July and August) as a 24.4$^{\circ}C$ in Hokkaido and 21.2$^{\circ}C$ in Daegwanryeong compared with 27.4$^{\circ}C$ in Changsu. Especially in Daegwanryeong, average maximum temperature from June to September remained as low as 21$^{\circ}C$. Effective accumulated temperature(>5$^{\circ}C$) was 807$^{\circ}C$ in Hokkaido and 964$^{\circ}C$ in Daegwanryeong during the ripening period. Monthly sunshined hours from July to August were 121.7~128 hours in Daegwanryeong and 83.5~85.4 hours in Hokkaido. The Eleutherococcus senticosus sprouts at 8.5$^{\circ}C$, comes to flowering season in mid-August, and ripens during late-August and October in Hokkaido, the climate of which is similar to that of Daegwanryeong.

• Journal of Forest and Environmental Science
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• v.37 no.4
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• pp.315-322
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• 2021

The aim of this study was to investigate the sensitivity to environmental stress, and changes in the photosynthesis capacity in Abies koreana seedlings by age and to suggest the most effective age for restoration. To identify these physiological characteristics of A. koreana, the chlorophyll fluorescence and photosynthetic capacity of 1-, 2-, 3-, 5- and 6-year-old A. koreana seedlings were observed from June 2020 to June 2021. The maximum quantum efficiency of Photosystem II (Fv/Fm), a chlorophyll fluorescence measurement parameter, was strongly positively correlated with the monthly average temperature (1-year-old seedling: r=0.8779, 2-year-old seedling: r=0.8605, 3-year-old seedling: r=0.8697, 5-year-old seedlings: r=0.8085, and 6-year-old seedlings: r=0.8316). The Fv/Fm values were the lowest in winter (November 2020-March 2021). In addition, the Fv/Fm values of 1-, 2-, and 3-year-old seedlings in winter were lower than that of 5- and 6-year-old seedlings, while the Fv/Fm values in summer were relatively higher than those in winter. Further, the Fv/Fm values of seedlings of all ages decreased in August 2020, when the monthly average temperature was the highest. In particular, 1-year-old to 3-year-old seedlings showed Fv/Fm values less than 0.8. Further, the photosynthetic capacity measured in August 2020 increased with increasing seedling age. The analysis of variance results for summer Fv/Fm values showed significant differences in age-specific averages (p<0.05), and Duncan's multiple range test showed significant differences between 5- and 6-year-old seedlings and 1-, 2-, and 3-year-old seedlings (p<0.05). These results suggested that the 5- and 6-year-old seedlings were less sensitive to environmental stress and showed better photosynthetic capacity than the 1-, 2-, and 3-year-old seedlings. Therefore, 5-year-old or older A. koreana seedlings can be used as restoration materials because they can show increased adaptability and stable growth during transplantation due to their relatively high environmental resistance and photosynthetic capacity.

• Atmosphere
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• v.16 no.2
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• pp.111-124
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• 2006

This study examines seasonal variability of the surface energy balance at the King Sejong Station, Antarctica, using measurements and estimates of the components related to the balance for the period of 1996 to 2004. Annual average of downward shortwave radiation at the surface is 81 $Wm^{-2}$ which is 37% of the extraterrestrial value, with the monthly maximum of 188 $Wm^{-2}$ in December and the minimum of 8 $Wm^{-2}$ in June. These values are relatively smaller than those at other stations in Antarctica, which can be attributed to higher cloudy weather conditions in Antarctic front zone. Surface albedo varies between ~0.3 in the austral summer season and ~0.6 in the winter season. As a result, the net shortwave radiation ranges from 117 $Wm^{-2}$ down to 3 $Wm^{-2}$ with annual averages of 43 $Wm^{-2}$. Annual average of the downward longwave radiation shows 278 $Wm^{-2}$, ranging from 263 $Wm^{-2}$ in August to 298 $Wm^{-2}$ in January. The downward longwave radiation is verified to be dependent strongly on the air temperature and specific humidity, accounting for 74% and 79% of the total variance in the longwave radiation, respectively. The net longwave radiation varies between 25 $Wm^{-2}$ and 40 $Wm^{-2}$ with the annual averages of 30 $Wm^{-2}$. Accordingly, the annual average energy balance is dominated by radiative warming of a positive net all-wave radiation from September to next March and radiative cooling of a negative net all-wave radiation from April to August. The net all-wave radiative energy gain and loss at the surface is mostly balanced by turbulent flux of sensible and latent heat. The soil heat flux is of negligible importance in the surface energy balance.

• Journal of the Korean Institute of Gas
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• v.23 no.5
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• pp.52-58
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• 2019

In this study, we have developed a forecasting model for city- gas acceptance. City-gas corporations have to report about city-gas sale volume next year to KOGAS. So it is a important thing to them. Factors influenced city-gas have differences corresponding to usage classification, however, in city-gas acceptence, it is hard to classificate. So we have considered tha outside temperature as factor that influence regardless of usage classification and the model development was carried out. ARIMA, one of the traditional time series analysis, and LSTM, a deep running technique, were used to construct forecasting models, and various Ensemble techniques were used to minimize the disadvantages of these two methods.Experiments and validation were conducted using data from JB Corp. from 2008 to 2018 for 11 years.The average of the error rate of the daily forecast was 0.48% for Ensemble LSTM, the average of the error rate of the monthly forecast was 2.46% for Ensemble LSTM, And the absolute value of the error rate is 5.24% for Ensemble LSTM.