본 연구에서는 PMF 모델을 이용하여 PM2.5에 대한 오염원 확인 및 오염원별 기여도를 분석하였다. A시의 배출원별 기여도 순위는 Secondary Sulfate가 19.8%로 가장 기여도가 높고, 그 다음으로는 Mobile 19.5%, Industry 16.0%, Biomass Buring 14.1%, Secondary Nitrate 14.1%, Oil Combustion 11.6%, Aged Sea Salt 2.6%, Soil 2.5% 등으로 분석되었다. Sulfate와 Ammonium 농도가 배출원별 프로 파일에서 기여도가 가장 높은 오염원으로 분석되었는데, 이는 대기 중에서 가스상 전구물질(SOx와 암모니아 가스)이 광화학 반응하여 생성된 2차 에어로졸인 것으로 분석되었다.

본 연구에서는 신안 장산도 남부해역 육상오염원의 위생상태와 영향 반경을 분석하였다. 배수 유역에 대한 해안선 조사를 실시해 오염원 종류를 구분하고, 해역으로 방출되는 오염원 유량과 위생실태를 분석하였으며 오염원의 영향 반경을 산정하였다. 육상오염원은 생활하수 21개소, 농 업용수 1개소, 육상양식장 11개소로 총 33개소(St. 65~97)이었고 이 중 농업용수 1개소, 육상양 식장 8개소의 오염원이 해역으로 배출되었다. 방출오염원의 유량은 72,857~281,250 l/min이었 고, 분변계대장균은 St. 72(농업용수)에서 490 MPN/100 ml, St. 74(육상양식장)에서 49 MPN/ 100 ml으로 비교적 높았다. 이들 영향 반경은 각각 4,389 m와 1.900 m로 나타났고, 해역의 안 전한 위생을 확보하기 위해서는 이들 오염원들에 대한 관리 및 해수 위생조사가 필요할 것으 로 판단된다.

Urban areas (residential, commercial, transportation), each of the points during the same rainfall in the same area, this study was evaluated by a survey to find out the basic data and the characteristics of non-point pollution on local characteristics was performed. To evaluate and compare a non-point source pollution concentrations. The conclusion of this study was to know the influence of non-point pollutants in initial rainfall. There was a difference during the same point was compared. The pollution levels were differences in the point-specific characteristics, the same point compared by rainfall when rainfall is low, the contaminant concentrations were high. Finally, when compared to the number of rainy days. The shorter the number of rainy days, the non-point pollutants were high.

Atmospheric stability is an important parameter which effects pollutant dispersion in the atmospheric boundary layer.The objective of this paper was to verify the effect of stability conditions on odor dispersion downwind from anarea source using computational fluid dynamic (CFD) modeling. The FLUENT Realizable k-ε model was used tosimulate odor dispersion as released by an odor source. A total of 3 simulations demonstrated the effects of unstable,neutral, and stable atmospheric conditions. Unstable atmospheric stability conditions produced a shorter odor plumelength compared with neutral and stable conditions because of stronger convective effects. Like other studies,unstable atmospheric condition produced higher plume height compared with neutral and stable conditions.

The Ministry of Environment (MOE) has made more effort in managing point source pollution rather than in nonpoint source pollution in order to improve water quality of the four major rivers. However, it would be difficult to meet water quality targets solely by managing the point source pollution. As a result of the comprehensive measures established in 2004 under the leadership of the Prime Minister’s Office, a variety of policies such as the designation of control areas to manage nonpoint source pollution are now in place. Various action plans to manage nonpoint source pollution have been implemented in the Soyang-dam watershed as one of the control areas designed in 2007. However, there are no tools to comprehensively assess the effectiveness of the action plans. Therefore, this study would assess the action plans (especially, BMPs) designed to manage Soyang-dam watershed with the WinHSPF and the CE-QUAL-W2. To this end, we simulated the rainfall-runoff and the water quality (SS) of the watershed and the reservoir after conducting model calibration and the model validation. As the results of the calibration for the WinHSPF, the determination coefficient (R2) for the flow (Q, m3/s) was 0.87 and the R2 for the SS was 0.78. As the results of the validation, the former was 0.78 and the latter was 0.67. The results seem to be acceptable. Similarly, the calibration results of the CE-QUAL-W2 showed that the RMSE for the water level was 1.08 and the RMSE for the SS was 1.11. The validation results(RMSE) of the water level was 1.86 and the SS was 1.86. Based on the daily simulation results, the water quality target (turbidity 50 NTU) was not exceeded for 2009∼2011, as results of maximum turbidity in '09, '10, and '11 were 3.1, 2.5, 5.6 NTU, respectively. The maximum turbidity in the years with the maximum, the minimum, and the average of yearly precipitation (1982∼2011) were 15.5, 7.8, and 9.0, respectively, and therefore the water quality target was satisfied. It was discharged high turbidity at Inbuk, Gaa, Naerin, Gwidun, Woogak, Jeongja watershed resulting of the maximum turbidity by sub-basins in 3years(2009∼2011). The results indicated that the water quality target for the nonpoint source pollution management should be changed and management area should be adjusted and reduced.

The MFFn(Mass first flush), EMCs(Event mean concentrations) and runoff loads were analyzed for various rainy events(monitoring data from 2011 to 2012) in transportation area(rail road in station). The pollutant EMCs by volume of stormwater runoff showed the BOD5 9.6 ㎎/L, COD 29.9 ㎎/L, SS 16.7 ㎎/L, T-N 3.271 ㎎/L, T-P 0.269 ㎎/L in the transportation areas(Railroad in station). The average pollutant loading by unit area of stormwater runoff showed the BOD5 27.26 kg/㎢, COD 92.55 kg/㎢, SS 50.35 kg/㎢, T-N 10.13 kg/㎢ and T-P 10.13 kg/㎢ in the transportation areas. Estimated NCL-curve(Normalized cumulated-curve) was evaluated by comparison with observed MFFn. MFFn was estimated by varying n-value from 10% to 90% on the rainy events. The n-value increases, MFFn is closed to '1'. As time passed, the rainfall runoff was getting similar to ratio of pollutants accumulation. The result of a measure of the strength of the linear relationship between observed data and expected data under model was good.

지형자료를 활용하여 지표수의 흐름 경로를 탐색하고 하천 네트워크를 추출하는 것은 수문 해석의 주요한 과정이다. 오늘날, DEM (digital elevation model)을 활용하여 유역 내 각 지점의 흐름 방향을 탐색하고 추가적인 특성인자를 산정하는 작업이 보편화되었다. DEM을 바탕으로 한 하천망의 추출에서 어려운 문제의 하나는 하천의 시점을 결정하는 것이다. 하천시점을 결정하는 정량적인 방법에는 하천이 생성되기 위한 최소한의 유역면적(upslope area)을 의미하는 유원면적(source area)을 가정하여, 각 지점의 유역면적이 유원면적보다 크면 해당 지점을 하천의 유로로 선택하는 방법이 있다. 보통 유역 전체에 일정한 값의 유원면적을 적용하여 하천의 시발점을 선택하지만, 유원면적은 실제로 유역 내 각 지점의 지형적 특성에 따른 하나의 변수로 다루는 것이 더 합리적이다. Montgomery and Dietrich (1988)는 유원면적이 다양한 지형학적, 기상학적, 지질학적 요소들의 관계에 따른 변수라는 관점을 제시하였으며, 특히 각 지점의 경사에 의존적이라는 것을 주장하였다. 유역 내의 모든 지점에 대하여 유역면적과 경사를 도시화하면, 일반 경사면에서는 두 가지 요소의 관계가 명확히 드러나지 않는 것에 반해 하천의 유로 구간에서는 유원면적과 경사의 함수 관계가 비교적 뚜렷하게 나타나고, 해당 면적을 각 지점의 유원면적으로 설정할 수 있다. 본 연구에서는 이렇게 상이한 하천시점 결정방법을 국내 유역에 적용하고 비교해 보았다. 가공되지 않은 DEM에 존재하는 웅덩이(depression cell)를 제거하고, 경사가 없는 평탄 지역에 대해 흐름 방향을 결정하기 위한 가상의 경사를 부여하는 전처리 과정으로는 Jenson and Domingue (1988)의 depression filling 기법과 Garbrecht and Martz (1997)의 imposed gradient 기법을 적용하였다. 가공된 지형자료를 바탕으로 각 지점에서의 흐름 방향을 결정하는 과정에는 기존 흐름 방향 탐색 모형의 단점을 합리적으로 보완한 GD8 (Paik, 2008) 모형을 적용하였다. 본 연구에서 두 가지 하천시점 탐색법을 비교한 결과, 유원면적-경사의 관계를 고려한 하천시점 탐색법이 고정된 값의 유원면적을 전 유역에 적용한 결과에 비해 실제 자연 하천망의 특성을 잘 반영한 결과를 나타내는 것을 확인할 수 있었다. 향후 지점의 경사와 함께 토양의 특성과 유역의 기후 특성 등 다양한 인자를 추가 고려한다면 실제 하천 발달의 물리적 과정에 보다 근사한 하천망 추출 결과 도출이 가능할 것으로 기대된다.

This study was conducted to investigate runoff characteristics of non-point pollutants source at the urban area in boeun area, Chungbuk Province. The monitoring site covering the watershed of 2.11 km 2 contains about 40.3 % of total watershed with the urban area. The monitoring was conducted with six events for five months and Event Mean Concentration(EMC) and Site Mean Concentration(SMC) of SS, BOD, CODMn, T-N, T-P were calculated on the result of the water quality parameters. As a result of the comparion between Arithmetic Mean Concentration and Event Mean Concentration, it showed that over all Event Mean Concentration was higher than Arithmetic Mean Concentration. And it showed that SS, BOD, T-P featured the first-flushing effect, showing relatively high concentration in early-stage storm event.

This study were to simulate major criteria air pollutants and estimate regional source-receptor relationship using air quality prediction model (TAPM ; The Air Pollution Model) in the Seoul Metropolitan area. Source-receptor relationship was estimated by contribution of each region to other regions and region itself through dividing the Seoul metropolitan area into five regions. According to administrative boundary, region Ⅰ and region Ⅱ were Seoul and Incheon in order. Gyeonggi was divided into three regions by directions like southern(region Ⅲ), northern(Ⅳ) and eastern(Ⅴ) area. Gridded emissions (1km×1km) by Clean Air Pollicy Support System (CAPSS) of National Institute of Environmental Research (NIER) was prepared for TAPM simulation. The operational weather prediction system, Regional Data Assimilation and Prediction System (RDAPS) operated by the Korean Meteorology Administration (KMA) was used for the regional weather forecasting with 30km grid resolution. Modeling period was 5 continuous days for each season with non-precipitation . The results showed that region Ⅰ was the most air-polluted area and it was 3～4 times more polluted region than other regions for NO2, SO2 and PM10. Contributions of SO2 NO2 and PM10 to region Ⅰ, Ⅱ and Ⅲ were more than 50 percent for their own sources. However region Ⅳ and Ⅴ were mostly affected by sources of region Ⅰ, Ⅱ and Ⅲ. When emissions of all regions were assumed to reduce 10 and 20 percent separately, air pollution of each region was reduced linearly and the contributions of reduction scenario were similar to those of base case. As input emissions were reduced according to different ratio - region Ⅰ 40 percent, region Ⅱ and Ⅲ 20 percent, region Ⅳ and Ⅴ 10 percent, air pollutions of region Ⅰ and Ⅲ were decreased remarkably. The contributions to regionⅠ, Ⅱ, Ⅲ were also reduced for their own sources. However, region Ⅰ, Ⅱ and Ⅲ affected more regions Ⅳ and Ⅴ. Shortly, graded reduction of emission could be more effective to control air pollution in emission imbalanced area.

The air pollutant emission is mainly caused by line sources in urban area. For example, the annually totaled air pollutant emission is known to consist of about 80% of line sources in Daegu. Hence, the appropriate assessment on the air pollutants of line sources is very important for the atmospheric environmental management in urban area. In this study, we made a comparative study to evaluate suitable dispersion model for estimating the air pollution from line sources. Two air pollution dispersion models, ISCST3 and CALINE4 were the subject of this study. The results were as follows; In the assessment of air pollution model, ISCST3 was found to have 4 times higher concentration than CALINE4. In addition, actual data obtained by measurement and estimated values by CALINE4 were generally identical. The air pollution assessment based on ISC3 model produced significantly lower values than actual data. The air pollution levels estimated by ISCST3 were very low in comparison with the observational values.

The runoff characteristics of non-point source pollutions in the municipal area of Jeonju were investigated and analyzed by using the SWMM (Storm Water Management Model). The flow rates and water qualities of runoff from two types of drainage conduits were measured respectively. One was a conventional combined sewer system and the other was a separated sewer system constructed recently. From August to November in 2004, investigations on two rainfall events were performed and flow rate, pH, BOD, COD, SS, T-N and T-P were measured. These data were also used for model calibration. On the basis of the measured data and the simulation results by SWMM, it is reported that 80-90% of pollution load is discharged in the early-stage storm runoff. Therefore, initial 10-30 mm of rainfall should be controlled effectively for the optimal treatment of non-point source pollution in urban area. Also, it was shown that the SWMM model was suitable for the management of non-point source pollution in the urban area and for the analysis of runoff characteristics of pollutant loads.

The present study investigated runoff characteristics of non-point pollutants and discharge load amount according to the land utilization in Yeinam river basin. The land utilization of target basin was divided into paddy field, dry field, forest, residential area and composition area. The study on the runoff characteristics of non-point pollutants by rainfall-runoff process showed that COD, SS and T-P had the first-flushing effect with relatively high concentration in early-stage of the rainfall-runoff process, but the T-P revealed similar runoff characteristics. Event Mean Concentration(EMC) of BOD and COD according to the land utilization revealed the range of 3.11～15.50mg/L and 3.37～33.42mg/L, and the highest concentration of EMC corresponding to BOD and COD was detected in the paddy field. The EMC of SS showed 1.7～305.02mg/L and it's highest concentration was found in the dry field. The EMC of T-N and T-P represented the highest concentration in the paddy field and dry field with range of 0.91～8.76mg/L and 0.02～0.44mg/L.

강우에 따른 토사유실은 호소내 저수용량 감소 및 탁수 등의 수질오염을 유발하기 때문에 유역관리 측면에서 중요한 인자가 된다. 최근 GIS를 활용한 토사유실평가 연구가 진행되고 있으나, 토사유실 원인지역에 대한 검토는 고려하지 않고 있다. 본 연구에서는 GIS 기반 토사유실모델을 활용하여 임하호 유역의 토사유실량을 산정하였으며, SPOT 5 고해상도 위성영상과 토지피복도 자료를 활용하여 토사유실원인지역을 검토하였다. 분석결과 토사유실이 높게 나타나는 지역

Samples of size-fractionated PM10 (airborne particulate matter with aerodynamic diameter less than 10㎛) were collected at an urban site in Jeju city from May to September 2002. The mass concentration and chemical composition of the samples were measured. The data sets were then applied to the CMB receptor model to estimate the source contribution of PM10 in Jeju area. The average PM10 mass concentration was 28.80㎍/㎥ (24.6~33.49㎍/㎥), and the FP (fine particle with aerodynamic diameter less than 2.1㎛) fraction in PM10 was approximately 8% higher than the CP (coarse particle with aerodynamic diameter greater than 2.1㎛ and less than 10㎛) fraction in PM10. The CP composition was obviously different from the FP composition, that is, the most abundant water soluble species was nitrate ion in the FP, but sulfate ion in the CP. Also sulfur was the most dominant element in the FP, however, sodium was that in the CP. From CMB receptor model results, it was found that road dust was the largest contributor to the CP mass concentration (45% of the CP) and ammonium nitrate, domestic boiler, and marine aerosol were major sources to the CP mass. However, the secondary aerosol was the most significant contributor to the FP mass concentration (45% of the FP). In this study, it was suggested that the contributions of soil dust and gasoline vehicle became very low due to collinearity with road dust and diesel vehicle, respectively.

In the present study, space allocation methods of pollutant emission from area and mobile sources are assessed by the actual application to air quality modeling of Pohang area. It is found that the TM-based modeling which allocates emission onto the 1km x 1km sized TM-grid system predicts almost the same mean ground-level concentration as that by the GIS-based modeling which uses geographical information of area and mobile sources directly, while maximum ground-level concentration by the TM-based modeling is predicted considerably lower than that by the GIS-based modeling. Moreover, the problem is found that the TM-based modeling causes deviation of mobile roads. In conclusion, it is anticipated to applying GIS-based modeling for a more accurate assessment of air quality in local scale.

To examine water pollution status of agricultural water source of greenhouse area in Gyeongnam, the ground water quality was investigated six times at five areas in Gyeongnam from October in 1995 to March in 1996. pH of ground water were generally in the range of 5.9∼7.6. But a site in Changnyeong area was out of the range in 6.0∼8.5 which is water quality standard for agriculture. COD of ground water was below 8.0㎎/ℓ which is water quality standard for agriculture in all areas and the average was below 2.8㎎/ℓ. NH_4^+ -N contents in ground water was very low in all areas and the average of NO_3^- -N contents in Changnyeong and Chinju area was high with 13.2 and 11.5㎎/ℓ, respectively. Hardness, SO_4^2- and EC of ground water in Haman were higher than any other area. Fe and Mn contents of ground water in Kimhae were higher than any other area with 7.17 and 0. 95㎎/ℓ, respectively. Heavy metals such as Cu, Cd, Pb and Zn of ground water were below water quality standard for agriculture but some sites were over. Between COD and SS in ground water were not correlated with r=0.328, but between COD and NH_4^+ -N were positively correlated. And EC was positively correlated with Ca^2+, Mg^2+ and SO_4^2-. Ground water pollution status of agricultural water source of greenhouse area in Gyeongnam was generally high in order of Sacheon < Chinju < Haman < Kimhae < Changnyeong.