• Journal of environmental and Sanitary engineering
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• v.18 no.3 s.49
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• pp.1-10
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• 2003

This study was aimed to investigate the influence on the vicinity by air pollutant generated from facility of the district heating located in local small town. We selected the seven areas arround the surroundings of facility of the district heating, compared the air quality evaluated before and after operations of the facility, and estimated the diffusion of air pollutant exhausted from the facility using a ISC model. The result was that the concentration of TSP before and after operations of the facility was 89${\sim}$94${\mu}$g/m$^3$,and 72${\sim}$81${\mu}$g/m$^3$, respectively and the latter showed a decline in concentration. Also, there was no relationship between straight distance from the facility of the district heating and the concentration of TSP. This result was applicable to cases of PM-10 and SO$_2$. We also investigated the influence on the air around the neighbored area by air pollutant produced from facility of the district heating using ISCLT3 model. The adding-concentrations of TSP, SO$_2$,NO$_2$, and CO were 0.0019${\sim}$0.00183${\mu}$g/m$^3$, 0.0029${\sim}$0.5648ppb, 0.2924${\sim}$l.9837ppb,and 0.0087${\sim}$0.0590ppb, respectively. It is predicted that each concentration is added to pollutant exhausted from facility of the district heating and is about 1/100${\sim}$1/180,000 of present air quality. This has a tiny influence on general air quality. According to this analysis, the concentration of air pollutant is less effected to pollutants expected by the facility of the district heating than other pollutants emitted from mobil source or industrial complex, and etc.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2D
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• pp.335-340
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• 2006

Geology and terrain of Imha basin has a very weak characteristics to soil erosion, so much soil particles flow into Imha reservoir and bring about high density turbid water when it rains a lot. Especially, since the agricultural area of Imha basin is mainly located in river boundary, Imha reservoir has suffered from turbid water by soil erosion. Therefore, it is important to estimate the influence of soil erosion to establish efficient management of water-pollutant buffering zone for the reduction of turbid water. By applying GIS-based RUSLE model, this study can acquire 12.23% that is the ratio of soil erosion in water-pollutant buffering zone and is higher than area-ratio (9.95%) of water-pollutant buffering zone. This is why the area-ratio of agricultural district (27.24%) in water-pollutant buffering zone is higher than the area-ratio of agricultural district (14.96%) in Imha basin. Also as the result of soil erosion in sub-basin, Daegok basin shows highest soil erosion in water-pollutant buffering zone, second is Banbyeon_10 basin and last is Seosi basin.

• KIEAE Journal
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• v.5 no.3
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• pp.41-48
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• 2005

Before occupation of an apartment housing, the builders are required to inform the test result of IAQ to the public. However, there is no simplified method to predict IAQ before measurement of pollutant concentration. In this study, a simplified way of predicting IAQ based on the distribution of indoor pollutant concentration is proposed. 7 different cases of air change rate have been simulated through CFD analysis to get the distribution ratio of each pollutant material and then simplified functions were used with CRIAQ1 values derived from CFD simulation to evaluate by comparing the influence of each material in the indoor pollutant concentration. Again, a lot of efforts which can improve the indoor air quality have been performed. Materials used in indoor space are labeled with their pollutant emission level. Installation of ventilation system in residential buildings will be regulated by a building codes sooner or later. But it is important to understand the fact that layout of walls, location or size of openings will influence the indoor air flow and pollutant concentration. And location of emitting material influences to indoor air pollutants distribution. But until now there is few recognition and consideration of these factors. Therefore, in this paper the effects of these factors is proved and some kind of guideline is made for designers after a comparison of typical apartment floor plan and a new type plan with their average pollutant concentration and its distribution of each room. CFD(Computational Fluid Dynamics) program was used to show the indoor air flow and pollutant concentration distribution. For this purpose, a typical $100m^2$ apartment floor plan was chosen as a case study model and several alternatives were reviewed to improve the IAQ performance. The simulation took place in the condition of natural ventilation through windows.

• Journal of Korean Society of Water and Wastewater
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• v.26 no.1
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• pp.47-54
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• 2012

This study analyzed influence factors and the correlation among pollutants which affect occurrence of leaked pollution based on the long-term runoff flow and water quality investigation results to understand the characteristics of highway rainfall runoff pollution load. According to the result of correlation analysis on TSS (Total Suspended Solid) concentration, anteceded dry days, rainfall intensity, traffic volume and etc. as major influence factors of highway rainfall runoff pollution loads, the correlations were weak or scarce in most items. These results might be attributed that runoff pollutant concentration changes vary severely on changes of rainfall intensity and rainfall duration within rainfall and it is affected by disturbances of vehicles and street cleaning and etc. as characteristics of the highway. While Cu, Fe and Zn which are discharged with high concentrations out of heavy metals showed high correlation with particulate matter, organic matter(COD), nutrient(TN, TP), Ni and Pb showed relatively low correlation in a correlation evaluation by pollutant. Significant correlation with traffic volumes was not shown and TSS concentration even decreased in accordance with increase of the traffic volume. In the comparison with precedent studies, it was considered necessary additional analysis of the effects of rainfall section analysis, road type, disturbances of surface contaminants by vehicles, rainfall and climate conditions, surrounding terrains etc.

• Journal of Korean Society on Water Environment
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• v.23 no.1
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• pp.161-168
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• 2007

The main aim of this work is focus on the Geum river water quality evaluation of pollution data obtained by monitoring measurement during the period 2001-2005. The complex data matrix 19 (entire monitoring stations)*13 (parameters), 60 (month)*13 (parameters) and 20 (season)*13 (parameters) were treated with different multivariate techniques such as factor analysis/principal component analysis (FA/PCA). FA/PCA identified two factor (19*13) classified pollutant Loading factor (BOD, COD, pH, Cond, T-N, T-P, $NH_3$-N, $NO_3$-N, $PO_4$-P, Chl-a), seasonal factor (water temp, SS) and three Factor (60*13, 20*13) classified pollutant Loading factor (BOD, COD, Cond, T-N, T-P, $NH_3$-N, $NO_3$-N, $PO_4$-P), seasonal factor (water temp, SS) and metabolic factor (Chl-a, pH). Loadings of pollutant factor is potent influence main factor in the Geum river which is explained by loadings of pollutant factor at whole sampling stations (71.16%), month (52.75%) and season (56.57%) of main water quality stations. Result of this study is that pollutant loading factor is affected at Gongju 1, 2, Buyeo 1, 2, Gangkyeong, Yeongi stations by entire stations and entire month (Gongju 1, Cheongwon stations), April, May, July and August (buyeo 1) by month. Also the pollutant Loading factor is season gives an influence in winter (Gongju 1, buyeo 1) from main sampling stations, but Cheongwon characteristic is non-seasonal influenced. This study presents necessity and usefulness of multivariate statistic techniques for evaluation and interpretation of large complex data set with a view to get better information data effective management of water sources.

• KCID journal
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• v.18 no.2
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• pp.54-65
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• 2011

This study was performed to analyze the influence of pollutant loads characteristics on the point and non-point sources in Saemangeum watershed area using Hydrological Simulation Program, Fortran (HSPF). The simulation items were flow, BOD, T-N, and T-P(2007~2010). The pollutant loads trend reflects the precipitation. Specifically, the point source loads were almost constant, but the non-point source loads were influenced in the precipitation. It was found that the effect of non-point source is larger than point source. The water quality had a clear trend by the season. However, pollutant loads did not show distinct seasonal changes. The reason is that the pollutant concentration is diluted by the increased flow at summer season. Therefore, it is important to control the non-point source in order to manage water quality in the region. For the management of Saemangeum lake, it is need to control of supplied pollutant loads from Saemangeum watershed.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.12 no.3
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• pp.149-155
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• 2000

The effects of the WfP construction are analysed quantitatively based on the pollutant budget change in Masan Bay. The reduction effects of the watershed pollutant loads are clearly shown, while the positive influence of the water quality (WQ) are not substantial because the pollutant load also increased continusly after WTP construction. The reduction effects of the COD, 55, TN and TP parameters are 17.6%, 68.9%,66.7%, and 38%, respectively in Masan Bay (zone I). The environmental condition of the northern part of Chinhae Bay (zone ll), however, is slowly degraded because of the direct and indirect effects - effluents discharge from the WTP and pollutants release from the sediment, respectively.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.908-912
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• 2006

Geology and terrain of Imha basin has a very weak characteristics to soil erosion, so much soil particles flow into Imha reservoir and bring about high density turbid water when it rains a lot. Especially, since the agricultural area of Imha basin is mainly located in river boundary, Imha reservoir has suffered from turbid water by soil erosion. Therefore, it is important to estimate the influence of soil erosion to establish efficient management of water-pollutant buffering zone for the reduction of turbid water. By applying GIS-based RUSLE model, this study can acquire 12.23% that is the ratio of soil erosion in water-pollutant buffering zone and is higher than area-ratio (9.95%) of water-pollutant buffering zone. This is why the area-ratio of agricultural district (27.24%) in water-pollutant buffering zone is higher than the area-ratio of agricultural district (14.96%) in Imha basin. Also as the result of soil erosion in sub-basin, Daegok basin shows highest soil erosion in water-pollutant buffering zone, second is Banbyeon_10 basin and last is Seosi basin.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.577-588
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• 2022

This study aims to identify the limiting nutrient for algal growth in the Geum River and the significant pollutant sources from the tributaries affecting the water quality and to provide a management alternative for an improvement of water quality. An eight-year of daily data (2013~2020) were collected from the Water Environment Information System (water.nier.go.kr) and Water Resources Management Information System (wamis.go.kr). 14 water quality variables were analyzed at five water quality monitoring stations in the Geum River (WQ1-WQ5). In the Geum River, the water quality variables, especially Chl-a vary greatly in downstream of the river. In the open weir gate operation, TP (total phosphorus) and water temperature greatly influence the growth of algae in downstream of the river. A correlation analysis was used to identify the relationship between variables and investigate the factor affecting algal growth in the Geum River. At the downstream station (WQ5), TP and Temp have shown a strong correlation with Chl-a, indicating they significantly influence the algal bloom. The principal component analysis (PCA) was applied to identify and prioritize the major pollutant sources of the two major tributaries of the river, Gab-cheon and Miho-cheon. PCA identifies three major pollutant sources for Gab-cheon and Miho-cheon, respectively. For Gab-cheon, wastewater treatment plant, urban, and agricultural pollutions pollution are identified as significant pollutant sources. For Miho-cheon, agricultural, urban, and forest land are identified as major pollutant sources. PCA seems to be effective in identifying water pollutant sources for the Geum River and its tributaries in detail and thus can be used to develop water quality management strategies.

• Journal of environmental and Sanitary engineering
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• v.24 no.3
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• pp.37-54
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• 2009

The study has analyzed impacts and intensity of weather that affect $PM_{10}$ concentration based on PM10 forecast conducted by the city of Seoul in order to identify ways to improve the accuracy of PM10 forecast. Variables that influence $PM_{10}$ concentration include not only velocity and direction of the wind and rainfalls, but also those including secondary particulate matter, which were identified to greatly influence the concentration in complicated manner as well. In addition, same variables were found to have different impacts depending on seasons and conditions of other variables. The study found out that improving accuracy of $PM_{10}$ concentration forecast face some limits as it is greatly influenced by the weather. As an estimation, this study assumed that basic research units and artificially estimated pollutant emissions, study on mechanisms of secondary particulate matter productions, observatory compliment, and enhanced forecaster's expertise are needed for better forecast.