• Proceedings of the Korean Environmental Health Society Conference
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• 2003.06a
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• pp.183-186
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• 2003

To evaluate the effect of air pollution on respiratory health in children, we conducted a longitudinal study in which children were asked to record their daily levels of peak expiratory flow rate using potable peak flow meter (mini-Wright) far 4 weeks. The relationship between daily PEFR and ambient air particle levels was analyzed using a mixed linear regression models including gender, age in you, weight, the presence of respiratory symptoms, and relative humidity as an extraneous variable. The daily mean concentrations of PM$\_$10/ and PM$\_$2.5/ over the study period were 64.9$\mu\textrm{g}$/㎥ and 46. l$\mu\textrm{g}$/㎥, respectively. The range of daily measured PEFR in this study was 170-481 l/min. Daily mean PEFR was regressed with the 24-hour. average PM$\_$10/ (or PM$\_$2.5/) levels, weather information such as air temperature and relative humidity, and individual characteristics including sex, weight, and respiratory symptoms. The analysis showed that the increase of air particle concentrations was negatively associated with the variability in PEFR. We estimated that the IQR increment of PM$\_$10/ or PM$\_$2.5/ were associated with 1.5 l/min (95% Confidence intervals -3.1, 0.1) and 0.8 l/min (95% Cl -1.8, 0.1) decline in PEFR. Even though this study shows negative findings on the relationship between respiratory function and air particles, it is worth noting that the findings must be interpreted cautiously because exposure measurement based on monitoring of ambient air likely results in misclassification of true exposure levels and this is the first Korean study that PM$\_$2.5/ measurement is applied as an index of air particle quality.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.28 no.6
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• pp.805-811
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• 1995

Final biomass yields (peak optical density) and growth rates (divisions/day) of seven clones of Skeletonema costatum from Korean coastal waters were measured to understand their intraspecific variations in the light intensity niche component under $25^{\circ}C$ condition. Daily growth rates of 6 of 7 S. costatum, clones were maximum at 6000 lux while that of YS4, a neritic clone, was maximum at 9000 lux. The final biomass yields of 4 of the 7 S. costatum clones were maximum at the lowest light intensity of 2000 lux. Minimum final biomass yields were found at 9000 lux in all the S. costatum clones other than an estuarine clone, HDC9. The intraspecific variations of the mean growth rate and mean final biomass yield under each of the three different light intensity in terms of the coefficient of variation were not greater than 10% in any of the 7 S. costatum clones.

• Journal of Korean Society on Water Environment
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• v.28 no.1
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• pp.137-147
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• 2012

Land surface temperature in ecohydrology is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. And there are an insufficient number of soil temperature monitoring stations. In this study, a grid-based land surface temperature prediction model is proposed. Target sites are Andong and Namgang dam region. The proposed model is run in the following way. At first, geo-referenced site specific air temperatures are estimated using a kriging technique from data collected from 60 point weather stations. Then surface soil temperature is computed from the estimated geo-referenced site-specific air temperature and normalized difference vegetation index. After the model is calibrated with data collected from observed remote-sensed soil temperature, a soil temperature map is prepared based on the predictions of the model for each geo-referenced site. The daily and monthly simulated soil temperature shows that the proposed model is useful for reproducing observed soil temperature. Soil temperatures at 30 and 50 cm of soil depth are also well simulated.

• Journal of Korean Society of Water and Wastewater
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• v.14 no.3
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• pp.281-290
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• 2000

This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. ANFIS, namely artificial intelligence, is a neural network into which fuzzy information is inputted and then processed. In this study, daily water supply was predicted through an application of network-based fuzzy inference system(ANFIS) for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water which supplied in Kwangju city. For variables choice, four analyses of input data were conducted: correlation analysis, autocorrelation analysis, partial autocorrelation analysis, and cross-correlation analysis. Input variables were (a) the amount of water supply, (b) the mean temperature, and (c) the population of the area supplied with water. Variables were combined in an integrated model. Data of the amount of daily water supply only was modelled and its validity was verified in the case that the meteorological office of weather forecast is not always reliable. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 18.46% and the average error was lower than 2.36%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

• Korean Journal of Environmental Agriculture
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• v.14 no.2
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• pp.155-162
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• 1995

To find out the relationship between duration of sunshine and mean air temperature, monthly climatic data were analyzed in several locations in Korea. Even though mean air temperature was high in summer, duration of sunshine was shorter than winter in Kangneung. Net radiation showed a positive correlation with duration of sunshine and its regression coefficient was the highest in July. An increasing rate of sensible heat flux according to the increment of sunshine hours was significantly high in April and October, but was low in July. In spring and fall, duration of sunshine was positively correlated with the daily temperature difference, but in summer and winter it was negatively correlated with maximum temperature and with the minimum temperature, respectively. In January, one hour increase in sunshine hour lowered the mean air temperature by 1 to $1.7^{\circ}C$.

• Korean Journal of Environmental Biology
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• v.18 no.1
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• pp.21-31
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• 2000

We investigated seasonal variation of microalgal assemblages, sea water temperature, salinity and suspended solid and the parameters measured daily from January 1998 to October 1999 at a nearshore shallow-water in Marian Cove, Maxwell Bay, King George Island, the Antarctic. Annual mean surface water temperature was -0.3$0^{\circ}C$ and the highest water temperature was 4.53$^{\circ}C$ (22 January 1999) and the lowest water temperature was -2.07$^{\circ}C$ (23 August 1998). Annual mean salinity was 33.38 psu, ranging from 42.80 psu (6 January 1999) to 19.50 psu (6 June 1999). Annual mean suspended solid (SS) during two years was 34.14 mgㆍ1$^{-1}$, ranging from 60.62 mgㆍ1$^{-1}$(7 March 1998) to 12.90 mgㆍ1$^{-1}$ (26 December 1998). Chlorophyll $\alpha$ (Chl $\alpha$) concentrations were measured in order to know seasonal variations of microalgae in the surface seawater. Annual mean of total Chl a concentration was 0.55$\mu\textrm{g}$ㆍ1$^{-1}$, the highest Chl $\alpha$ concentration (12.16$\mu\textrm{g}$ㆍ1$^{-1}$) appeared in 4 October 1998, the lowest Chl $\alpha$ concentration appeared 0.19$\mu\textrm{g}$ㆍ1$^{-1}$, Monthly mean total Chl $\alpha$ concentration was high in October 1998 (1.32$\mu\textrm{g}$ㆍ1$^{-1}$) and low in July on 1998 (0.28$\mu\textrm{g}$ㆍ1$^{-1}$). Annual mean nano-sized Chl $\alpha$ concentration was 0.40$\mu\textrm{g}$ㆍ1$^{-1}$, monthly mean nano -sized Chl $\alpha$ concentration was high in November 1998 (0.90$\mu\textrm{g}$ㆍ1$^{-1}$), and low in July 1999 (0.22$\mu\textrm{g}$ㆍ1$^{-1}$). Annual mean micro-sized Chl $\alpha$ concentration was 0.15$\mu\textrm{g}$ㆍ1$^{-1}$ monthly mean micro-sized Chl $\alpha$ concentration was high in October 1998 (0.81$\mu\textrm{g}$ㆍ1$^{-1}$), and low July 1998, January, February and September 1999 (0.05$\mu\textrm{g}$ㆍ1$^{-1}$). More than 65% of total Chl $\alpha$ was concentrated during spring and summer time between October and March. Microalgal variation appeared to be due to physical factors of seawater in the Antarctic nearshore from 1998 to 1999. The reason why micro-sized Chl $\alpha$ did not increase during austral summer was the bay had been frozen by decrease of water temperature. We think that total microalgal abundance was decreased because the summer microalgal abundance was determined by variation of water temperature during winter season. [Chl $\alpha$ concentration, Microalgal assembalges, Seasonal variation, the Antarctic nearshore].

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.3
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• pp.109-119
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• 2016

This study was conducted to analyze the effect of yearly changes in growing degree days (GDD) on the potential distribution and growth of Quercus mongolica in Korea. Annual tree-ring growth data of Quercus mongolica collected by the $5^{th}$ National Forest Inventory were first organized to identify the range of current distribution for the species. Yearly GDD was calculated based on daily mean temperature data from 1951 to 2010 for counties with current distribution of Q. monglica. When tree-ring growth data were analyzed through cluster analysis based on similarity of climatic conditions, seven clusters were identified. Yearly GDD based on daily mean temperature data of each county were calculated for each of the cluster to predict the change of potential distribution. Temperature effect indices were estimated to predict the effect of GDD on the growth patterns. In addition, RCP 4.5 and RCP 8.5 of climate change scenarios were adopted to estimate yearly GDD and temperature effect indices from 2011 to 2100. The results indicate that the areas with low latitude and elevation exceed the upper threshold of GDD for the species due to the increase of mean temperature with climate change. It was also predicted that the steep increase of temperature will have negative influences on tree-ring growth, and will move the potential distribution of the species to areas with higher latitude or higher elevation, especially after the year of 2050. The results of this study are expected to provide valuable information necessary for estimating local growth characteristics and for predicting changes in the potential distribution of Q. mongolica caused by climate change.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.60 no.3
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• pp.273-281
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• 2015

Relationship between grain quality-related traits and daily mean temperature/sunshine hours during grain filling stage was analyzed using eleven high quality rice varieties at 24 experimental sites through eight provinces of Korea in 2013~2014. In the data set pooled across varieties, experimental sites and years, grain quality-related traits such as percentage of head rice (PHR), head rice yield (HRY), protein in milled rice (PRO) and Toyo Mido Meter glossiness value (TGV) were higher at the temperature lower than $22.6^{\circ}C$ for 40 days after flowering (DAF), which was optimum for percentage of grain filling in this study. Optimum sunshine hours for 40 DAF were $6.0{\sim}6.1\;hr\;d^{-1}$when considered PHR, HRY and TGV. PRO was associated with daily mean temperature and sunshine hours for 40 DAF in more varieties than the other traits. PRO was closely correlated with daily mean temperature during early filling stage and sunshine hours during early to mid filling stage, compared to other stages during grain filling. It is concluded that general trend in the variation of grain quality-related traits could be explained by the changes in daily mean temperature and sunshine hours during grain filling. In addition, climate conditions during early grain filling stage played important roles to enhance grain quality.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.183-185
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• 2015

Recently, big data analysis based on machine learning has gained popularity and many machine learning techniques have been applied to the field of agriculture. By using machine learning technique to analyze huge number of samples of biological and environmental data, new observations can be found. In this research, we consider the estimation of proportional daily weight increase (PDWI) based on measurement data from experimental swine farm. In order to derive the exact formulation for PDWI estimation, we have used measured value of mean, daily maximum, daily minimum of temperature, humidity, CO2, wind speed and measured PDWI values. Based on collected data, we have derived equation for PDWI estimation using tree-based algorithm. In the derived formulation, we have found that the daily average temperature is the most dominant factor that affects PDWI. Our results can be applied to pig farms to estimate the PDWI of swine.

• Journal of Environmental Health Sciences
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• v.30 no.2
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• pp.140-148
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• 2004

To evaluate the acute effects of fine particles on pulmonary function, a longitudinal study was conducted. This study was carried out for the schoolchildren (3rd and 6th grades) living in Beijing, China. Each child was provided with a mini-Wright peak flow meter and a preformatted health symptom diary for 40 days, and was trained on their proper use. Participants were instructed to perform the peak flow test three times in standing position, three times a day (9 am, 12 pm, and 8 pm), and to record all the readings along with the symptoms (cold, cough, and asthmatic symptoms) experienced on that day. Daily measurement of fine particles (PM$_{10}$ and PM$_{2.5}$) was obtained in the comer of the playground of the participating elementary school for the same period of this longitudinal study. The relationship between daily peak expiratory flow rate (PEFR) and fine particle levels was analyzed using a mixed linear regression models including gender, height, the presence of respiratory symptoms, and daily average temperature and relative humidity as extraneous variables. The total number of students participating in this longitudinal study was 87. The range of daily measured PEFR was 253-501$\ell$/min. In general, the PEFR measured in the morning was lower than the PEFR measured in the evening (or afternoon) on the same day. The daily mean concentrations of PM$_{10}$ and PM$_{2.5}$ over the study period were 180.2$\mu\textrm{g}$/㎥ and 103.2$\mu\textrm{g}$/㎥, respectively. The IQR (inter-quartile range) of PM$_{10}$ and PM$_{2.5}$ were 91.8$\mu\textrm{g}$/㎥ and 58.0$\mu\textrm{g}$/㎥. During the study period, the national ambient air quality standard of 150$\mu\textrm{g}$/㎥ (for PM$_{10}$) was exceeded in 23 days (57.5%). The analysis showed that an increase of 1$\mu\textrm{g}$/㎥ of PM$_{10}$ corresponded to 0.59$\mu\textrm{g}$/㎥ increment of PM$_{2.5}$. Daily mean PEFR was regressed with the 24-hour average PM$_{10}$ (or PM$_{2.5}$) levels, weather information such as air temperature and relative humidity, and individual characteristics including gender, height, and respiratory symptoms. The analysis showed that the increase of fine particle concentrations was negatively associated with the variability in PEFR. The IQR increments of PM$_{10}$ or PM$_{2.5}$ (at 1-day time lag) were also shown to be related with 1.54 $\ell$/min (95% Confidence intervals: 0.94-2.14) and 1.56$\ell$/min (95% CI: 0.95-2.16) decline in PEFR.R.ine in PEFR.ine in PEFR.