The correlation among gaseous air pollutants (odorous compounds, greenhouse gases) and meteorological parameters was analyzed in-depth using measurement data at a barn and ambient in a naturally ventilated dairy farm. Both concentration and emission data (loading rate and emission rate), which more accurately express the actual pollutant emissions, were used in the correlation analysis. Gaseous air pollutants (ammonia, hydrogen sulfide, carbon dioxide, nitrous oxide, methane) and meteorological factors (relative humidity, temperature, wind speed, solar strength) were measured for one week in July 2013. The upper and lower outliers of measured data by inducing 1.5 times the interquartile range (IQR) were eliminated. After eliminating the outliers and grouping according to data magnitude, the correlation analysis among gaseous compounds and meteorological factors was conducted using the average values of each group. In the correlation analysis, data for the emission rate (barn) and the loading rate (ambient) showed a better correlation than concentration data. Gaseous air pollutants except for hydrogen sulfide in the barn showed a good correlation. Hydrogen sulfide might not be produced from manure or animal origin. Rather, the compound may be produced by flushing water, which was flushed at periodical times (every six hours). Ammonia emissions increased with increasing temperature, and this increase can be affected from greater exertion of feces by frequent water drinking in a high-temperature condition. In the ambient, the correlation for all gaseous air pollutants was better than that in the barn, because those air pollutants from manure, animals, and flushing water origins were sufficiently mixed in the atmosphere. Wind speed also showed a good correlation with all gaseous air pollutants.

This study investigated the weather conditions, fine particle concentration, and ion components in PM2.5 when two cold fronts passed through Busan in succession on February 1 and 2, 2021. A analysis of the surface weather chart, AWS, and backward trajectory revealed that the first cold front passed through the Busan at 0900 LST on February 1, 2021, with the second cold front arriving at 0100 LST on February 2, 2021. According to the PM10 concentration of the KMA, the timing of the cold front passage had a close relationship with the occurrence of the highest concentration of fine particles. The transport time of the cold front from Baengnyeongdo to Mt. Gudeok was approximately 11 hours . The PM10 and PM2.5 concentrations in Busan started to increase after the first cold front had passed, and the maximum concentration occurred two hours after the second cold front passed. The SO4 2-, NO3 -, and NH4 + concentration in PM2.5 started to increase from 1100 to 1200 LST on February 1, after the first cold front passed, and peaked at 0100 LST to 0300 LST on February 2. However, the highest Ca2+ concentration was recorded 2-3 hours after the second cold front had passed.

This study investigated characteristics of meteorological parameters and ionic components of PM2.5 during Asian dust events on November 28 and 30, 2018 at Busan, Korea. The seasonal occurrence frequencies of Asian dust during 1960∼2019 (60 years) were 81.7% in spring, 12.2% in winter, and 6.1% in autumn. Recently, autumn Asian dust occurrence in Busan has shown an increasing trend. The result of AWS (automatic weather station), surface weather chart, and backward trajectory analyses showed that the first Asian dust of Nov. 28, 2018, in Busan came with rapid speed through inner China and Bohai Bay from Mongolia. The second Asian dust of Nov. 30, 2018, in Busan seems to have resulted from advection and deposition of proximal residual materials. These results indicated that understanding the characteristics of meteorological parameters and ionic components of PM2.5 during Asian dust events could provide insights into establishing a control strategy for urban air quality.

기후변화에 따른 다양한 자연 재해들이 발생함에 따라 수자원 분야에서도 이에 대한 관심이 증가하고 있다. 특히 수자원 분야는 인류의 생존과 직결되어 있는 물 관련 이슈인 홍수, 가뭄, 물 부족 등의 문제점이 나타나고 있으며, 크게는 물 순환에 영향을 받게 되어 그에 따른 연구가 필수적이다. 따라서 본 연구에서는 수자원 분야 연구의 일환으로 수문·기상학적 인자들을 산출하기 위하여 지면 모형 중 하나인 Common Land Model (CLM)을 사용하였다. 모형의 구동을 위한 자료는 한반도지표자료동화체계(Korea Land Data Assimilation System; KLDAS)의 자료를 사용하였다. 한반도지표자료동화체계는 다양한 자료를 사용하여 지면 모형에 강제시켜 신뢰할 만한 결과를 산출해낸다. 모형의 결과는 국내 KoFlux 관측 지점 중 하나인 해남의 자료와 비교한다. 이를 통하여 아직 미흡한 CLM 모형에 대한 국내 및 동북아시아 지역에 대한 사용 가능성을 확인하고, 추후 더 많은 관측 자료와 비교·검증할 예정이다.

본 연구에서는 Clark 합성단위도의 매개변수 추정치에 대한 신뢰구간을 좁힐 수 있는 방안으로, 이들을 강우, 기상, 및 유역 특성인자로 다변량 회귀분석한 후 이를 Monte Carlo 모의기법을 통하여 분석하였다. 아울러 이렇게 얻은 결과는 Bootstrap 기법으로 분석한 결과 및 기존에 많이 사용되어 왔던 경험식과도 비교 검토하였다. 이상과 같은 과정을 통해 얻은 결과는 다음과 같다. (1) 관측된 호우사상의 수가 제한적인 경우, 유출특성에 미치는