• 태양에너지
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• 제12권2호
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• pp.1-8
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• 1992

본 연구는 동계 외기온 데이타의 시각별 변동특성을 파악하기 위하여 연변동 성분 및 기간변동 성분을 제거한 일변동 성분의 매 시각별 외기온 데이타에 대해서 일교차의 발생요인에 대해서 분석하였다. 또한 동계시각별 외기온의 주파수 특성에 대해서 검토하였으며 외기온 데이타의 수식화의 가능성을 제시하였다.

• Water Engineering Research
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• 제5권1호
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• pp.1-16
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• 2004

The purpose of this study is to understand the characteristics of hourly PET(Potential Evapo Transpiration) variation estimated using Penman ET model. The estimated PET using Penman model was compared with measured ET. For this study, two subwatersheds were selected, and fluxes, meteorological data and soil moisture data were measured during the summer and winter days. During the winter days, the aerodynamic term of Penman ET is much greater than that of energy term of Penman ET for dry soil condition. The opposite phenomena appeared fer wet soil condition. During the summer days, energy term is much more important factor for ET estimation compared with aerodynamic term regardless of soil moisture condition. Penman ET, measured ET, and energy term show the similar hourly variation pattern mainly because the influence of net radiation on the estimation of Penman ET is much more significant compared with other variables. Even though there are much more soil moisture in the soil during the wet days, the estimated hourly ET from Penman model and measured hourly ET have smaller values compared with those of dry days, indicating the effect of cloudy weather condition.

• 한국환경보건학회지
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• 제17권2호
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• pp.1-8
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• 1991

The stochastic variance and structures of time series data on air quality were examined by employing the techniques of autocorrelation function, variance spectrum, fourier series, ARIMA model. Among the air quality properties of atmosphere, SO$_{2}$ is one of the most siginificant and widely measured parameters. In the study, the air quality data were included hourly observations on SO$_{2}$ TSP and O$_{3}$. The data were measured by automatic recording instrument installed in Kwanghwamoon during February and March in 1991. The results of study were as follows 1. Hourly air quality series varied with the domiant 24 hour periodicity and the 12 hour periodic variation was also observed. 2. The correlation coefficients between SO$_{2}$ and O$_{3}$ is -0.4735. 3. In simulating or forecasting variation in SO$_{2}$ ARIMA models are on a useful tools. The multiplicative seasonal ARIMA (1, 1, 0) (0, 2, 1)$_{24}$ model provided satisfactory results for hourly SO$_{2}$ time series.

• 전기학회논문지
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• 제59권6호
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• pp.1041-1045
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• 2010

Short-term electric load forecasting of power systems is essential for the power system stability and the efficient power system operation. An accurate load forecasting scheme improves the power system security and saves some economic losses in power system operations. Due to scarcity of the historical same type of holiday load data, most big electric load forecasting errors occur on load forecasting for the holidays. The fuzzy linear regression model has showed good accuracy for the load forecasting of the holidays. However, it is not good enough to forecast the load of the election day. The concept of the load variation rate for the load forecasting of the election day is introduced. The proposed algorithm shows its good accuracy in that the average percentage error for the short-term 24 hourly loads forecasting of the election days is 2.27%. The accuracy of the proposed 24 hourly loads forecasting of the election days is compared with the fuzzy linear regression method. The proposed method gives much better forecasting accuracy with overall average error of 2.27%, which improved about average error of 2% as compared to the fuzzy linear regression method.

• 한국환경과학회지
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• 제23권1호
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• pp.25-37
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• 2014

In the present study, we analyzed precipitation patterns and diurnal variation trends of hourly precipitation intensity due to climate change. To that end, we used the hourly precipitation data obtained from 26 weather stations around South Korea, especially Busan, from 1970 to 2009. The results showed that the hourly precipitation was concentrated on a specific time of day. In particular, the results showed the so-called "morning shift" phenomenon, which is an increase in the frequency and intensity of hourly precipitation during the morning. The morning shift phenomenon was even more pronounced when a higher level of hourly precipitation intensity occurred throughout the day. Furthermore, in many regions of Korea, including Busan, this morning shift phenomenon became more prevalent as climate change progressed.

• Ocean and Polar Research
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• 제31권1호
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• pp.63-70
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• 2009

Eutrophicated water fed through Mankyeong River and Dongjin River into the new Saemankeum Lakemight seriously affect the water quality and phytoplankton community in the lake. To obtain control reference data for the later studies on environmental changes due to the construction of the Saemankeum Sea Wall, we performed a monthly investigation on the physico-chemical properties of the water and phytoplankton community at 3 stations in the Mankyeong River Estuary over 14 months starting from September 1999. Water temperature ranged from $0.3{\sim}32.9^{\circ}C$ due to the typical seasonal variations in temperate on the coasts and salinity exhibited a wide annual range of $0.2{\sim}33.7$ psu along with regular and huge hourly variations according to tidal cycles. Inorganic nutrients were supplied from rivers to the monitoring station and the whole lake. The average concentration of total-N, $6.99\;mg{\cdot}l^{-1}$, was higher than the water quality for agricultural use with peak values occurring in winter. Species composition showed a seasonal succession pattern, where a high diversity was observedin summer and autumn and vice versa in winter. Hourly variations of water properties in the "Mankyeong bridge" Station were quite regular and well in accordance with the daily tidal cycles. The different degree of sea water intrusion during the flood tide at each of the 3 stations exhibited a different range and variation pattern of water temperature and salinity throughout a day. Hourly changes in species composition were in harmony with the daily tidal cycles, resulting in extremely variable spatio-temporal variation.

• 한국환경과학회지
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• 제12권10호
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• pp.1033-1041
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• 2003

Hourly data of PM10 concentration collected from nine automatic air quality monitoring stations in Busan from 1999 to 2002 were analyzed to evaluate the spatio-temporal variation and meteorological characteristics of PM10 episodes in Busan metropolitan area. Mean concentrations ranged from 47$\mu\textrm{g}$/㎥ to 77$\mu\textrm{g}$/㎥. For most stations, mean seasonal hourly concentrations are lowest in summer and highest in spring. PM10 episode above daily mean standard(150$\mu\textrm{g}$/㎥) exhibited a maximum frequency at Gamjeondong and a minimum at Dongsamdong, and a maximum in March and a minimum in July and August. The diurnal variation of PM10 episode days is strongly influenced by traffic loads and meteorological conditions.

• 한국환경과학회지
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• 제21권8호
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• pp.953-963
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• 2012

The annual variations of the urban heat island in Busan is investigated using surface temperature data measured at 3 automatic weather stations(AWSs) for the 5 years period, 2006 to 2010. Similar to previous studies, the intensity of the urban heat island is calculated using the temperature difference between downtown(Busanjin, Dongnae) and suburb(Gijang). The maximum hourly mean urban heat island are $1.4^{\circ}C$ at Busanjin site, 2300LST and $1.6^{\circ}C$ at Dongnae site, 2100LST. It occurs more often at Dongnae than Busanjin. Also the maximum hourly mean urban heat island appears in November at both sites. The urban heat island in Busan is stronger in the nighttime than in the daytime and decreases with increasing wind speed, but it is least developed in summer. Also it partly causes the increasement of nighttime PM10 concentration.

• 한국환경과학회지
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• 제14권11호
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• pp.1035-1047
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• 2005

By using hourly $NO_2$ concentration data$(1998\~2000)$ at the Busan Metropolitan City air qualify monitoring sites, characteristics of daily mean value of $NO_2$ concentration was discussed in space and time. The correlation between $NO_2$ concentration and other relating air pollutants was analyzed by using SAS program and meteorological parameters as well. After choosing representative 4 areas, this study used hourly concentration data$(1998\~2000)$ from air quality monitoring sites on $NO_2,\;NO,\;O_3,\;CO,\;SO_2\;and\;PM_{10}$. Typical metropolitan characteristics of two peaks in a day was shown in the variation of $NO_2$ concentration of Busan city.

• 물과 미래
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• 제15권3호
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• pp.23-36
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• 1982

The stochastic variations and structures of time series data on water quality were examined by employing the techniques of autocorrelation function, variance spectrum, Fourier series, autoregressive model and ARIMA model. These time series included hourly and daily observation on DO, turbidity, conductivity pH and water temperature. The measurement was made by automatic recording instrument at Noryangjin and Dook-do located in the downstream part of Han River during 1975 and 1976. Hourly water quality time series varied with the dominant 24-hour periodicity, and the 12-hour periodicity was also observed. An important factor affecting 24-hour periodic variation of DO is believed to be photosynthesis by algae. These phenomena might be attributable to periodic discharges of municipal sewage. Noryangjin site showed the more distinct 12-hour periodicity than Dook-do site did, and tidal effect might be responsible for the difference. The water quality, as measured by DO and turbidity, was better in the afternoon compared with the quality in the morning. This change can be explained by the periodic variation of DO, temperature and the amount of municipal wewage discharge. It was also observed that the water temperature at Noryangjin was higher than the temperature at Dook-do. This difference might have been caused by the pollutants that were added to the section between two sites. The correlation coefficients between some of the variables were fairly high. For example, the coefficient was -0.88 between DO and water temperature, 0.75 between turbidity and river flow, and 0.957 between water temperature and air temperature. The lag time of heat transfer from the air to the water was estimated as 24 days. The first order auto-regressive model was appropriate for explaning standardized hourly DO time series. The ARIMA model of (1, 0, 0) type provided relatively satisfactory results for daily DO time series after the removal of significant harmonic value.