• Journal of Environmental Science International
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• v.5 no.1
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• pp.15-23
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• 1996

During the last two decades, many industrial complexes for heavy and chemical industries have been established along the Korean coastline, thereby increasing the pollution materials burden on the coastal environment of seawater. Masan Bay is one of the most polluted coastal areas in Korea and the main soures of pollutants are domestic and industrial wastewater from Masan, Changwon. This study was aimed to evaluate relationships among the physicochemical parameters in the bottom water of Masan bay and to examine environmental factors affecting to pollutions of seawater by factor analysis. 'rife factor loading, 1 is showed higher increasing inclination after 1989 year in station 1. The variance of pollutant materials is showed 43.7% in which the coastal inflow water is indicated external loadings(factor 1 : NO3--N, TN, factor 4 : SiO2-Si) corresponded to domestic sewage, industrial wastewater, and earth-sands in the bottom water of Masan bay And the internal loadings(factor 2 : SS, salinity, factor 3 . W.T., DO) are explained 33.8%'corresponded the phenomena of sedimentary layer and oxygen concentration. Therefore, The external loadings are explained by the higher factor pollutantal variance in Masan bay.

• Journal of Korean Society on Water Environment
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• v.28 no.1
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• pp.84-93
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• 2012

The study was conducted to analyze the spatio-temporal changes in water quality of the major 36 sampling stations of Nakdong River, depending on each station, season using the 17 water quality variables from 2000 to 2010. The result was verified to interpret the characteristics of water quality variables in a more accurate manners. According to the Principal component analysis (PCA) and Exploratory factor analysis (EFA) results; the results of these analyses were identified 4 factors, Factor 1 (nutrients) included the concentrations of T-N, T-P, $NO_{3}-N$, $PO_{4}-P$, DTN, DTP for sampling station and season, Factor 2 (organic pollutants) included the concentrations of BOD, COD, Chl-a, Factor 3 (microbes) included the concentrations of F.Coli, T.Coli, and Factor 4 (others) included the concentrations of pH, DO. The results of a Cluster analysis indicated that Geumhogang 6 was the most contaminated site, while tributaries and most of the down stream sites of Nakdong River were mainly affected by each nutrients (Factor 1) and organic pollutants (Factor 2). The verification consequence of Confirmatory factor analysis (CFA) from Exploratory factor analysis (EFA) result can be summarized as follows: we could find additional relations between variables besides the structure from EFA, which we obtained through the second-order final modeling adopted in CFA. Nutrients had the biggest impact on water pollution for each sampling station and season. In particular, It was analyzed that P-series pollutant should be controlled during spring and winter and N-series pollutant should be controlled during summer and fall.

• Journal of environmental and Sanitary engineering
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• v.18 no.4
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• pp.6-14
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• 2003

A spring water quality was depend on the aquifer soil status. However, water quality was rapidly contaminated by artificial affects. In the contaminate components, the heavy metals were significantly important because the heavy metals influence the plants and the animals. But, it is difficult to find out how the heavy metal can affect in the water quality. According to the group analysis and the factor analysis, water quality management was advanced. The experimental area was divided into three region and six factor. The six factor could not define the overall water quality, however this method were one of the useful methods.

• 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.

• Journal of Environmental Science International
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• v.25 no.6
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• pp.767-787
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• 2016

In this study, we analyzed on-site monitoring data for 15 tributaries in Geumho watersheds for 3 years (2011-2013) in order to sort out priorities on water quality characteristics and improvement. As a result of estimating contribution to contamination of the tributary rivers, Dalseocheon showed the highest load densities, despite the smallest watershed area, with 22.7% $BOD_5$, 30.7% $COD_{Mn}$, 31.3% TOC and 47.6% TP. After conducting PCA (principal component analysis) and FA (factor analysis) to analyze water quality characteristics of the tributary rivers, the first factor was classified as $COD_{Mn}$, TOC, EC, TP and $BOD_5$, the second factor as pH, Chl-a and DO, the third factor as water temperature and TN, and the fourth factor as SS and surface flow. In addition, arithmetical sum of each factor's scores based on grading criteria revealed that Dalseocheon and Namcheon were classified into Group A for their highest scores - 96 and 93, respectively -, and selected as rivers that require water environmental management measures the most. Also, water environmental contamination inspection showed that Palgeocheon had the most number of aquatic factors to be controlled: $BOD_5$, $COD_{Mn}$, SS, TOC, T-P, Chl-a, etc.

• Journal of Korean Society on Water Environment
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• v.33 no.6
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• pp.650-660
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• 2017

In this study, pollutant emission characteristics by water damage period analyzed 11 items (water temperature, pH, DO, EC, BOD, COD, TOC, SS, T-N, T-P and flow) with load duration curve, time series load curve and factor analysis for three years (2014-2016). Load duration curve is applied to judge the level of impaired waterbody and estimate impaired level by pollutants such as BOD and T-P in this study depending on variation of stream flow. Water quality standard exceeded the flow of mid-range and low-range by flow condition evaluation using load duration curve. This watershed was influenced by point source more than non-point source. Cumulative excess rate of BOD and T-P kept water quality standard for all seasons (spring, summer, autumn and winter) except BOD 59% in spring. Water quality changes were influenced by pollutants of basic environmental treatment facilities and agricultural areas during spring and summer. Results of factor analysis were classified commonly first factor (BOD, COD, and TOC) and second factor (flow, water temperature and SS). Therefore, effects of artificial pollutants and maintenance water must be controlled seasonally and reduced relative to water damage caused by point pollution sources with effluent standard strengthened in the target watershed.

• Journal of Environmental Science International
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• v.7 no.2
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• pp.171-176
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• 1998

This study was conducted to evaluate water quality utilizing principal component analysis in the Nakdong River Estuary. From the results of analysis, water quality in the Nakdong River Estuary could be explained up to 65.3 Percente by three factors which were Included In river loadlnwastes from the Nakdong River and rainfalls : 39.1%1, sediment resuspension(13.7BS) and metabolism(12.5%). In the eastern part of estuary In flowing the Nakdong River, river loading factor score(factor 1 Pas higher than that In western part. Sediment resuspension factor score(factor 2) was high in shallow water, while metabolism factor score(factor 3) was high in deeper water. For seasonal variations of factors score, factor 1 was h19h- 1y related to rainfall season.

• Journal of Korean Society on Water Environment
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• v.30 no.3
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• pp.351-360
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• 2014

The allocation of margin of safety (MOS) at a uniform rate to all areas of the unit watershed makes it very difficult to keep the load allotment stable in the area for lack of reduction measures like forest land. This study developed an equation to calculate margin of safety differentially according to the regional characteristics. The equation was formulated on the basis of the regional characteristic factors such as a load contribution factor for land use type and a site conversion factor for the unit watershed. The load contribution factor represents a contribution of loads from a particular land use. The site conversion factor was derived from the site conversion ratio of a unit watershed. Margin of safety for the non-point pollution load in the land use sector decreased by 20~25% in three river basins. The margin of safety in the unit watersheds with low site occupation ratios decreased in high rate, while in the unit watersheds with large urban area decreased in low rate. With the application of the differential margin of safety considering regional characteristics, not only the reduction of pollution loads can become lighter but also it can be easier to develop plans for Total Maximum Daily Loads (TMDLs) even where the reduction measures are not available.

• Journal of Environmental Science International
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• v.8 no.3
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• pp.331-336
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• 1999

The monthly water quality data measured at 14 stations located in the Geum-River watershed were clustered into 2 to 7 clusters. Furthermore, factor analyses were conducted on Gabcheon and Yugucheon to characterize the water qualtiy, based on the information obtained from the results of culster analysis. The results of cluster analysis show that the water quality charactersitic of main stream of the Geum-River is somewhat different from that of substream of the Geum-River. Furthermore, the water quality characteristic of Gabcheon which is expected to have the most serious water quality problems in the Geum-River watershed shows the most different water quality characteristic from Yugucheon. Based ont he factor loadings in each factor, Gabcheon and Yugucheon have their own water quality characteristics. This is mainly because of composite factors such as different population density, industrial activities, and land use conditions in Gabcheon and Yugucheon subwatersheds.

• Korean Journal of Environmental Biology
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• v.17 no.4
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• pp.521-527
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• 1999

To investigate the variations of environmental and microbial populations in six stations at water region of Gangjin Bay, nutritive salts, water temperature, COD, DO, pH, heterotrophic bacteria, fungi and facal coliform bacteria were analysed four imes from February to November, 1998. These data were subjected to simple statistics, correlation analysis and principal factor analysis. Ecosystem of Gangiin Bay was regulated by 2∼4 factors during four seasons. We estimated that it was mainly influenced by inflow of fresh water, nutrient salts, suspended solids, salinity and variation of water temperature. These results suggested that influences of environmental factor of Gangiin Bay was relatively less than those of other bays.