• Journal of Environmental Health Sciences
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• v.38 no.3
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• pp.184-194
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• 2012

Objectives: We investigated the effects of air pollution on allergic diseases (allergic rhinitis, asthma, atopic dermatitis) in metropolitan cities in Korea, adjusting for meteorological factors. Methods: Data on daily hospital visits and hospital admissions for 2003-2010 was obtained from the National Health Insurance Cooperation. Meteorological data was obtained from the Korea Meteorological Administration. We then calculated daily mean temperature, daily mean humidity, daily mean air pressure at sea level, and diurnal temperature range. We used data on air pollution provided by the National Institute of Environmental Research. Maximum daily eight-hour average ozone concentrations and the daily mean $PM_{10}$ were used. We estimated excess risk and 95% confidence interval for the increasing interquatile range (IQR) of each air pollutant using Generalized Additive Models (GAM) that appropriate for time series analysis. Results: In this study, we observed an association between ozone and hospital visits for allergic rhinitis, asthma, and atopic dermatitis in all metropolitan cities, adjusting for temperature, humidity, air pressure at sea level, diurnal temperature range, and day of the week. Ozone was associated with hospital visits for allergic rhinitis, asthma, and atopic dermatitis across all metropolitan cities. However $PM_{10}$ was associated with allergic-related diseases in only select cities. Also, ozone and $PM_{10}$ were associated with hospital admission for asthma in all cities except Gwangju. Hospitalization for the other diseases failed to show consistent association with air pollutants. Conclusion: In the findings of this study, there was a significant association between air pollutants and allergic-related diseases. More detailed research subdivided age group or conducting meta-analyses combining data of all cities is required.

• Ocean Science Journal
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• v.42 no.4
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• pp.211-222
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• 2007

We compare insolation results calculated from two well-known empirical formulas (Socket and Beaudry's SB73 formula and the original Smithsonian (SMS) formula) and a radiative transfer model using input data predicted from meteorological weather-forecast models, and review the accuracy of each method. Comparison of annual mean daily irradiance values for clear-sky conditions between the two formulas shows that, relative to the SMS, the SB73 underestimates spring values by 9 W $m^{-2}$ in the northern Adriatic Sea, although overall there is a good agreement between the annual results calculated with the two formulas. We also elucidate the effect on SMS of changing the 'Sun-Earth distance factor (f)', a parameter which is commonly assumed to be constant in the oceanographic context. Results show that the mean daily solar radiation for clear-sky conditions in the northern Adriatic Sea can be reduced as much as 12 W $m^{-2}$ during summer due to a decrease in the f value. Lastly, surface irradiance values calculated from a simple radiative transfer model (GM02) for clear-sky conditions are compared to those from SB73 and SMS. Comparison with iu situ data in the northern Adriatic Sea shows that the GM02 estimate gives more realistic surface irradiance values than SMS, particularly during summer. Additionally, irradiance values calculated by GM02 using the buoy meteorological fields and ECMWF (The European Centre for Medium Range Weather Forecasts) meteorological data show the suitability of the ECMWF data usage. Through tests of GM02 sensitivity to key regional meteorological factors, we explore the main factors contributing significantly to a reduction in summertime solar irradiance in the Adriatic Sea.

• Journal of Environmental Science International
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• v.22 no.12
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• pp.1633-1641
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• 2013

The objective of this study was to analyze correlation between phenological characteristics of Salix spp. and meteorological factors in the Upo wetlands. Phenology of Salix subfragilis Andersson and Salix chaenomeloides Kimura was monitored from 2007 to 2012. Meteorological variables were monitored by Korea Meteorological Administration (Hap-chon). Average date of flowering, fruiting, seed dispersion was 86, 113, 136 days for S. subfragilis and 112, 140, 164 days for S. chaenomeloides as Julian days. Flowering of S. subfragilis and S. chaenomeloides were correlated with daily mean air temp. in March (r=-0.92, r=-0.85, p<0.05). Fruiting of S. subfragilis was correlated with total precipitation between Jan and March of previous year (r=-0.90, p<0.01), however, the fruiting of S. chaenomeloides was highly correlated with max. temp. in Jan of previous year (r=0.99, p<0.01). Seed dispersion of both species is correlated with min. temp. in Feb. Phenology monitoring will contribute to understanding Salix spp. response against climate change.

• Journal of Environmental Science International
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• v.14 no.1
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• pp.91-96
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• 2005

Several samplers using gravimetric methods such as high-volume air sampler, MiniVol portable sampler, personal environmental monitor(PEM) and cyclone were applied to determine the concentrations of fine particles in atmospheric condition. Comparative evaluation between high-volume air sampler and Minivol portable sampler for $PM_{10}$, and between Minivol portable sampler and PEM was undertaken from June, 2003 to January 2004. Simultaneously, meteorological conditions such as wind speed, wind direction, relative humidity and temperature was measured to check the factors affecting the concentrations of fine particles. In addition, particle concen­trations by cyclone with an aerodynamic diameter of $4{\mu}m$ were measured. Correlation coefficient between high­volume air sampler and portable air sampler for $PM_{10}$ was 0.79 (p<0.001). However, the mean concentration for $PM_{10}$ by high-volume air sampler was significantly higher than that by Minivol portable sampler (p=0.018). Correlation coefficient between Minivol portable sampler and PEM for $PM_{2.5}$ as 0.74 (p<0.001), and the measured mean concentrations for $PM_{2.5}$ did not show significant difference. Difference of the measured con­centrations of fine particle might be explained by wind speed and humidity among meteorological conditions. Particle concentration differences by measurement samplers were proportional to the wind speed, but inversely proportional to the relative humidity, though it was not a significant correlation.

• Journal of Preventive Medicine and Public Health
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• v.52 no.2
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• pp.82-91
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• 2019

Objectives: Many studies have explored the relationship between short-term weather and its health effects (including pneumonia) based on mortality, although both morbidity and mortality pose a substantial burden. In this study, the authors aimed to describe the influence of meteorological factors on the number of emergency room (ER) visits due to pneumonia in Seoul, Korea. Methods: Daily records of ER visits for pneumonia over a 6-year period (2009-2014) were collected from the National Emergency Department Information System. Corresponding meteorological data were obtained from the National Climate Data Service System. A generalized additive model was used to analyze the effects. The percent change in the relative risk of certain meteorological variables, including pneumonia temperature (defined as the change in average temperature from one day to the next), were estimated for specific age groups. Results: A total of 217 776 ER visits for pneumonia were identified. The additional risk associated with a $1^{\circ}C$ increase in pneumonia temperature above the threshold of $6^{\circ}C$ was 1.89 (95% confidence interval [CI], 1.37 to 2.61). Average temperature and diurnal temperature range, representing within-day temperature variance, showed protective effects of 0.07 (95% CI, 0.92 to 0.93) and 0.04 (95% CI, 0.94 to 0.98), respectively. However, in the elderly (65+ years), the effect of pneumonia temperature was inconclusive, and the directionality of the effects of average temperature and diurnal temperature range differed. Conclusions: The term 'pneumonia temperature' is valid. Pneumonia temperature was associated with an increased risk of ER visits for pneumonia, while warm average temperatures and large diurnal temperature ranges showed protective effects.

• Journal of Climate Change Research
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• v.6 no.4
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• pp.277-281
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• 2015

A Chinese cabbage is one of important vegetables which accounts for more than 60 percent of leaf vegetable. However, cultivation area and yield of Chinese cabbage are steadily decreasing recently. Because meteorological changes destabilize the balance of Chinese cabbage, we need to study on meteorological factors affecting estimation of Chinese cabbage yield. So we conducted a panel analysis using mean temperature, maximum temperature, minimum temperature, precipitation and sunshine's duration from August to November for estimation of Chinese cabbage yield. As the results, we found that if the mean temperature of September increase by $1^{\circ}C$ the amount of production of Chinese cabbage per unit area was increased by 348.6 kg/10a. We also found that the mean temperature of October increased by 174.8 kg/10a, that of November 148 kg/10a, the difference between the maxium temperature and the minimum temperature of October equals 443.3 kg/10a. However, we found that the difference between the maximum temperature and the minimum temperature of November decreased 274.1 kg/10a.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.181-187
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• 2021

Recently, various air pollution factors have been measured and analyzed to reduce damages caused by it. In this process, many missing values occur due to various causes. To compensate for this, basically a vast amount of training data is required. This paper proposes a statistical techniques that effectively compensates for missing values generated in the process of measuring ozone, carbon dioxide, and ultra-fine dust using a small amount of learning data. The proposed algorithm first extracts a group of meteorological data that is expected to have positive effects on the correction of missing values through statistical information analysis such as the correlation between meteorological data and air pollution level factors, p-value, etc. It is a technique that efficiently and effectively compensates for missing values by analyzing them. In order to confirm the performance of the proposed algorithm, we analyze its characteristics through various experiments and compare the performance of the well-known representative algorithms with ours.

• Journal of Integrative Natural Science
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• v.17 no.2
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• pp.33-41
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• 2024

Abnormal climate is a phenomenon in which meteorological factors such as temperature and precipitation are significantly higher or lower than normal, and is defined by the World Meteorological Organization as a 30-year period. However, over the past 30 years, abnormal climate phenomena have occurred more frequently around the world than in the past. In Korea, abnormal climate phenomena such as abnormally high temperatures on the Korean Peninsula, drought, heatwave and heavy rain in summer are occurring in March 2023. Among them, heatwaves are expected to increase in frequency compared to other abnormal climates. This suggests that heatwave should be recognised as a disaster rather than just another extreme weather event. According to several previous studies, greenhouse gases and meteorological factors are expected to affect heatwaves, so this paper uses logistic regression and discriminant analysis on meteorological element data and greenhouse gas data in Gwangju from 2008 to 2022. We analyzed the impact of heatwaves. As a result of the analysis, greenhouse gases were selected as effective variables for heatwaves compared to the past, and among them, chlorofluorocarbons were judged to have a stronger effect on heatwaves than other greenhouse gases. Since greenhouse gases have a significant impact on heatwaves, in order to overcome heatwaves and abnormal climates, greenhouse gases must be minimized to overcome heatwaves and abnormal climates.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.656-656
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• 2002

It is studied on the relationship between the occurrence of red tide(Chlorophyll-a concentration by the in-situ and satellite data) and the meteorological factors (precipitation, air temperature, sunshine and winds) in the coastal areas in the South Sea of Korea. In summer and early-fall which frequently occurred the red tide, the precipitation above 213mm had directly influence on the occurrence of red tide because it carried the nutritive substance which originated from the land into the coastal areas. Then air temperature kept up generally high values as 23~26$^{\circ}C$, and sunshine with 187~198hours and wind velocity with 3.1~7.9m/s showed not directly the relationship on the occurrence of red tide.

• Journal of Environmental Science International
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• v.7 no.6
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• pp.827-831
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• 1998

Statistical $SO_2$ forecasting technique by multiple regression analysis was designed and developed to predict $SO_2$ concentration in Wonju City. $SO_2$ concentration data measured from air pollution monitoring system and meteorological factors data such as : wind speed, atmospheric stability, surface temperature, relative humidity and precipitation were used in Wonju City during the 1996~1997. As the results, correlation model for forecasting was well fitted with some parameters including minimum temperature, wind speed and the $SO_2$ concentration of the previous day.