본 연구에서는 오징어류에 해당하는 대왕오징어, 오징어, 문어, 한치 및 이를 이용한 가공식품에 대해서 분자생물 학적 기법을 활용한 시험법을 검토하였다. 시료 중 원료 성분 확인을 위하여 오징어류 4종에 대해 최적의 종 특이 프라이머를 디자인하였으며, 시료로부터 직접 genomic DNA를 추출하여 PCR을 실시하였다. PCR 수행과정에서 반응을 저해하는 염 성분을 제거하기 위하여 증류수를 이용하여 3~4회 세척 후 PCR을 실시한 결과, Single PCR의 경우 대왕오징어(552 bp), 오징어(463 bp), 문어(247 bp), 한치(354 bp)에 해당하는 종 특이적인 증폭산물을 확인하였으며, Multiplex PCR 의 경우 서로 다른 종 사이의 교차반응없이 동시다발적으로 증폭이 일어남을 확인할 수 있었다. 또한 이들 4종에 대해 PCR 민감도를 조사한 결과, 모두 약 0.1 ng/μl의 농도까지 검출이 가능함을 확인하였으며 multiplex PCR의 경우 약 0.25 ng/μl의 농도까지 검출이 가능함을 확인하였다. 이를 이용하여 오징어류가 함유된 수산물 가공식품 8건에 대해 적용성을 검토한 결과, 모든 시료에서 유효한 결과를 확인할 수 있었다. 따라서 본 연구에서 제작된 오징어류 4종에 대한 종 특이적 프라이머는 생물 상태뿐만 아니라 수산물 가공식품에 대해서도 이를 판별할 수 있어 식품안전관리에 활용할 수 있을 것으로 기대된다.

Temporal and spatial variations in surface ozone concentrations in Busan were investigated by using observation data from urban air quality sites during 2001-2016. The annual ozone concentrations showed a significant increasing trend of +0.40 ppb yr-1 in this period, with a more rapid increase of +0.81 ppb yr-1 since 2010. For the monthly analysis, the increase in ozone concentration was the greatest in August (+0.68 ppb yr-1). These ozone trends were due mainly to rising temperature (+0.05℃ yr-1) and weak decreasing precipitation (－6.42 mm yr-1). However, the extreme weather events (heat wave, localized heavy rain, etc.) lead to an increase in short-term variability of ozone since 2010. The relatively low ozone concentrations in the downtown area were caused by high NOx emissions from mobile sources. The increases in ozone concentrations were observed at most of the air quality monitoring sites due to the reductions in anthropogenic emissions of NOx during 2001-2015. However, in the southern coastal area, lower rates of increase in ozone concentrations were observed by –0.10~0.25 ppb yr-1 due to the significant NOx emitted by ships in the Busan port and Busan new port.

Both the propagation velocity and the direction of atmospheric waves are important factors for analyzing and forecasting meteo-tsunami. In this study, a total of 14 events of meteo-tsunami over 11 years (2006-2016) are selected through analyzing sea-level data observed from tidal stations along the west coast of the Korean peninsula. The propagation velocity and direction are calculated by tracing the atmospheric disturbance of each meteo-tsunami event predicted by the WRF model. Then, the Froude number is calculated using the propagation velocity of atmospheric waves and oceanic long waves from bathymetry data. To derive the critical condition for the occurrence of meteo-tsunami, supervised learning using a logistic regression algorithm is conducted. It is concluded that the threshold distance of meteo-tsunami occurrence, from a propagation direction, can be calculated by the amplitude of air-pressure tendency and the resonance factor, which are found using the Froude number. According to the critical condition, the distance increases logarithmically with the ratio of the amplitude of air-pressure tendency and the square of the resonance factor, and meteo-tsunami do not occur when the ratio is less than 5.11 hPa/10 min.

Provider-oriented weather information has been rapidly changing to become more customer-oriented and personalized. Given the increasing interest in wellness and health topics, the demand for health weather information, and biometeorology, also increased. However, research on changes in the human body according to weather conditions is still insufficient due to various constraints, and interdisciplinary research is also lacking. As part of an effort to change that, this study surveyed medical practitioners at an actual treatment site, using questionnaires, to investigate what kind of weather information they could utilize. Although there was a limit to the empirical awareness that medical staff had about weather information, most respondents noted that there is a correlation between disease and weather, with cardiovascular diseases (coronary artery disease (98.5%) and hypertension (95.9% ), skin diseases (atopic dermatitis (100%), sunburn (93.8%)) being the most common weather-sensitive ailments. Although there are subject-specific differences, most weather-sensitive diseases tend to be affected by temperature and humidity in general. Respiratory and skin diseases are affected by wind and solar radiation, respectively.

Meteo-tsunamis are tsunamis that are typically caused by strong atmospheric instability (e.g., pressure jumps) in low pressure systems, but some meteo-tsunamis in winter can be caused by local atmospheric instability in high pressure systems (e.g., the Siberian High). In this study, we investigated a meteo-tsunami event related to a high pressure system that occurred during winter on the Yellow Sea in 2005. Sea level data from tidal stations were analyed with a high-pass filter, and we also performed synoptic weather analyses by using various synoptic weather data (e.g., surface weather charts) collected during the winter season(DJF) of 2005. A numerical weather model (WRF) was used to analyze the atmospheric instability on the day of the selected event (21 Dec. 2005). On the basis of the results, we suggest that the meteo-tsunami triggered by the high pressure system occurred because of dynamic atmospheric instability induced by the expansion and contraction of the Siberian High.

The effect of weather on disease was investigated based on results reported in academic papers. Weather-sensitive disease was selected by analyzing the frequency distributions of diseases and correlations between diseases and meteorological factors (e.g., temperature, humidity, pressure, and wind speed). Correlations between disease and meteorological factors were most frequently reported for myocardial infarction (MI) (28%) followed by chronic ischemic heart disease (CHR) (12%), stroke (STR) (10%), and angina pectoris (ANG) (5%). These four diseases had significant correlations with temperature (meaningful correlation for MI and negative correlations for CHR, STR, and ANG). Selecting MI, as a representative weather-sensitive disease, and summarizing the quantitative correlations with meteorological factors revealed that, daily hospital admissions for MI increased approximately 1.7%-2.2% with each 1℃ decrease in physiologically equivalent temperature. On the days when MI occurred in three or more patients larger daily temperature ranges (2.3℃ increase) were reported compared with the days when MI occurred in fewer than three patients. In addition, variations in pressure (10 mbar, 1016 mbar standard) and relative humidity (10%) contributed to an 11%-12% increase in deaths from MI and an approximately 10% increase in the incidence of MI, respectively.

In this study, the regional climate (WRF) and air quality (CMAQ) models were used to simulate the effects of future urban growth on surface ozone concentrations in the Seoul metropolitan region (SMR). These analyses were performed based on changes in ozone concentrations during ozone seasons (May–June) for the year 2050 (future) relative to 2012 (present) by urban growth. The results were compared with the impacts of RCP scenarios on ozone concentrations in the SMR. The fractions of urban in the SMR (25.8 %) for the 2050 were much higher than those (13.9 %) for the 2012 and the future emissions (e.g., CO, NO, NO2, SO2, VOC) were increased from 121 % (NO) to 161.3 % (NO2) depending on emission material. The mean and daily maximum 1-h ozone in the SMR increased about 3 - 7 ppb by the effect the RCP scenarios. However, the effect of urban growth reduced the mean ozone by 3 ppb in the SMR and increased the daily maximum 1-h ozone by 2 - 5 ppb over the northeastern SMR and around the coastline. In particular, the ozone pollution days exceeding the 1-h regulatory standard (100 ppb) were far more affected by urban growth than mean values. As a result, the average number of days exceeding the 1-h regulatory standard increased up to 10 times.

A meteo-tsunami occurred along the coastline of South Korea on 31 March 2007, with an estimated maximum amplitude of 240 cm in Yeonggwang (YG). In this study, we investigated the synoptic weather systems around the Yellow sea including the Bohai Bay and Shandong Peninsula using a weather research and forecast model and weather charts of the surface pressure level, upper pressure level and auxiliary analysis. We found that 4-lows passed through the Yellow sea from the Shandung Peninsula to Korea during 5 days. Moreover, the passage of the cold front and the locally heavy rain with a sudden pressure change may make the resonance response in the near-shore and ocean with a regular time-lag. The sea-level pressure disturbance and absolute vorticity in 500 hPa projected over the Yellow sea was propagated with a similar velocity to the coastline of South Korea at the time that meteo-tsunami occurred.

Now a days, frequency of abnormally high temperatures like heat wave by global warming and climate change is increasing constantly and the number of patient with heat related illness are jumping rapidly. In this study, we chose the case day for the heat wave in Busan area(Busan and Yangsan), 2013 which it was the most hottest year during 21th century. And then, we analysed the weather condition using automatic synoptic observing system(ASOS) data. Also, four indices, heat index(HI), wet bulb globe temperature(WBGT), Man-ENvironment heat EXchange model(MENEX)’s results like Physiological subjective temperature(PST), Physiological strain(PhS), were calculated to evaluate the thermal comfort and stress quantitatively. However, thermal comfort was different as the each station and thermal comfort index during same time. Busan’s thermal indices (HI: hot, WBGT: sweltering, PST: very hot, PhS: very hot) indicated relatively higher than Yansan’s (HI: very hot, WBGT: sweltering, PST: very hot, PhS: sweltering). It shows that Busan near coast is relatively more comfortable than Yangsan located in inland.

The spatial and temporal changes of the annual mean urban heat island(UHI) intensity were investigated using near surface temperature data measured at 16 automatic weather systems(AWS) in Busan metropolitan area(BMA) during the 11-yr period, from 2000 to 2010. For nighttime, the annual mean UHI intensity at Dongnae(U1) in 2000 was weaker than it in 2010. However the change of the annual mean UHI intensity at Daeyeon(U2) during 11 years was different from it at U1. The annual frequency of the UHI intensity over 5℃ considerably increased at U2 and decreased at U1 during 11 years. The center of the UHI also spatially shifted southward with Daeyeon and Haeundae in BMA. It would be caused by the increase of urban area, population-density and transportation near U2 and by the decrease of them near U1. We found that the spatial and temporal differences of the UHI intensity have coincided with changes of land-use, population density and transportation in BMA.

In this study, the characteristics in the simulation of high-resolution coastal weather, i.e. sea surface wind (SSW) and significant wave height (SWH), were studied in a southeastern coastal region of Korea using the WRF and SWAN models. This analyses was performed based on the effects of various input factors in the WRF and SWAN model during M-Case (moderate days with average 1.8 m SWH and 8.4 ms-1 SSW) and R-Case (rough days with average 3.4 m SWH and 13.0 ms-1 SSW) according to the strength of SSW and SWH. The effects of topography (TP), land cover (LC), and sea surface temperature (SST) for the simulation of SSW with the WRF model were somewhat high on v-component winds along the coastline and the adjacent sea of a more detailed grid simulation (333 m) during R-Case. The LC effect was apparent in all grid simulations during both cases regardless of the strength of SSW, whereas the TP effect had shown a difference (decrease or increase) of wind speed according to the strength of SSW (M-Case or R-Case). In addition, the effects of monthly mean currents (CR) and deepwater design waves (DW) for the simulation of SWH with the SWAN model predicted good agreement with observed SWH during R-Case compared to the M-Case. For example, the effects of CR and DW contributed to the increase of SWH during R-Case regardless of grid resolution, whereas the differences (decrease or increase) of SWH occurred according to each effect (CR or DW) during M-Case.

In this study, the use survey of domestic and international weather information on coastal regions and the demand survey (e.g. general and in-depth surveys) for customer needs with coastal industries were carried out to design customized coastal weather contents. The general demand survey showed that most of the customers working in the coastal industries were interested in a short-term forecast, such as a general weather outlook (approximately 29% of the total respondents) and typhoon information (19%), and they preferred to be given the forecast information from new media such as the internet web-pages (36%) and mobile utilities (23%) rather than old media such as TV (16%) and radio (11%). In addition, only 31% of the total respondents were found to be satisfied with the use of the current coastal weather service. This low percentage might mainly be a result of lack of information accuracy (about 64%) and diversity (28%). From in-depth survey with site visiting, the need of coastal weather contents, such as weather elements, data form, a tool of communication, and forecast interval, differed with the working stages in three coastal industries (e.g. shipbuilding, maritime trade, and passenger transport industries).

The relationship between air temperatures and the fraction of urban areas (FUA) and their linear regression equation were estimated using land-use data provided by the water management information system (WAMIS) and air temperatures by the Korea Meteorology Administration (KMA) in the Seoul metropolitan area (SMA) during 1975 through 2000. The future FUA in the SMA (from 2000 to 2030) was also predicted by the urban growth model (i.e., SLEUTH) in conjunction with several dataset (e.g., urban, roads, etc.) in the WAMIS. The estimated future FUA was then used as input data for the linear regression equation to estimate an annual mean minimum air temperature in the future (e.g., 2025 and 2030). The FUA in the SMA in 2000 simulated by the SLEUTH showed good agreement with the observations (a high accuracy (73%) between them). The urban growth in the SMA was predicted to increase by 16% of the total areas in 2025 and by 24% in 2030. From the linear regression equation, the annual mean minimum air temperature in the SMA increased about 0.02℃/yr and it was expected to increase up to 8.3℃ in 2025 and 8.7℃ in 2030.