• Journal of Korean Society for Atmospheric Environment
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• v.19 no.E2
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• pp.51-61
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• 2003

The material exposure tests have been carried out since 1993 to evaluate the relationship between air pollution and material corrosion with the cooperation of the researchers in Japan, China, and Korea. The test pieces such as bronze, copper, marble, and carbon steel have been exposed under both unsheltered and rain-sheltered outdoor condition separately at 18 sampling sites in East Asia. At the same time, the concentration of SO$_2$ and NO$_2$ has been measured simultaneously with passive sampler. The meteorological data were collected from the AWS (Auto-mated weather station) In each country and chemical compositions of wet deposition were also analyzed by the bulk sampling of rainfall every month. As the results, it was found that the corrosion rates of test pieces in the ambient air were appeared to be in the order of carbon steel > marble > bronze copper. The corrosion rates of test pieces in the unsheltered outdoor condition were 2.34 to 5.88 times larger than those in rain-sheltered condition. It was also found that the corrosion rate in the heavy polluted area in China was the highest, and the corrosion rates of the metal pieces were generally proportional to SO$_2$ concentration. Between two sites in Korea, the test pieces at Daegu site showed higher corrosion rates that would be due to the higher SO$_2$ concentration.

• Journal of Environmental Science International
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• v.11 no.6
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• pp.489-496
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• 2002

The purpose of this study was to investigate spatial distributions of total deposition. A total number 79 samples were collected at 17 sampling sites from September 1999 to January 2000. Total (=wet+dry) atmospheric depositions were collected by filtered deposition sampler at sampling site (the Western Part of Kyongsangnam Province). In addition, the deposition of soluble and insoluble fraction was also investigated to find a suitable simplified collection method for a long-term monitoring of total deposition. The total depositions were measured soluble amount(mm/month), insoluble amount(kg/km$^2$/month), pH, conductivity(E.C.) and eight ionic components. The spatial distribution of deposition flux was to estimated by using a kringing analysis. The 17 sites mean fluxes of water soluble ionic components; SO$_4$$\^$2-/, Cl$\^$-/, NO$_3$$\^$-/, Na$\^$+/, NH$_4$$\^$+/, K$\^$+/, Mg$\^$2+/, Ca$\^$2+/ were 100.7∼315.6kg/km$^2$/month, 30.1∼234.3kg/km$^2$/month, 64.4∼ 139.4kg/km$^2$/month, 7.5∼68.3kg/km$^2$/month, 10.7∼48.7kg/km$^2$/month, 5.6∼27.9kg/km$^2$/month, 4.5∼17.5kg/km$^2$/month, 27.6∼81.7kg/km$^2$/month, respectively.

• Journal of environmental and Sanitary engineering
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• v.10 no.3
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• pp.85-98
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• 1995

In order to ensure that all major cations and anions were accurately measured, the quality assurance checks of chemical analysis data by considering ion and conductivity balance of each precipitation sample were performed. To check the quality assurance of chemical analysis data, precipitation samples were collected by wet- only precipitation sampler at Seoul site and their chemical components were analyzed. By checking the problems for the screening methods of chemical analysis data used until recently, the f value expressed as the ratio of the sum of cations and anions equivalent concentration( $\Sigma $C/$\Sigma $A ) was found to be not ap priorate for data screening. Also, the scattering plot between cation and anion equivalent concentrations in each sample was found to show the general tendency of ion balance but was proved to not quantitate the standard of data screening at a set of samples of various concentration levels.4 more appropriate value was therefore required, h value is defined as (A-C)/C for C≥A and ( A-C)/A for C<4. This value was showed to check the ion balance in a viewpoint of quantitative as well as qualitative and to be useful in applying this expression to a measurement data set. However, the standard o( data screening must vary in response to the ion concentration of sample. In this study, the quality assurance of chemical analysis data was checked by considering both the ion balance evaluating by h value and the electrical conductivity. As these quality assurance checks were applied to Seoul data serf 67 valid samples were obtained. The result of statistical summary in the analytical parameter of precipitation samples collected for a certain period was found to be computed in the precipitation volume- weighted mean( VWM) rather than the arithmetic mean( AM), but PH In the VWM of hydrogen ion concentration. The annual VWM of pH values was 5.0(4.9 ∼ 5.1).

• Journal of Environmental Science International
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• v.5 no.2
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• pp.141-152
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• 1996

This study is an attempt to investigate the chemical components of precipitation and its variation according to surface wind. Precipitation samples were collected by an wet-only precipitation sampler during the period of October 1994 to September 1995 at Kyungsan in Korea. The results obtained in t체s study are summerized as follows. The annual average of precipitation pH is 5.0, the highest month of pH is July of 5.5, and the lowest month of pH is December of 4.4. The most frequent appearance is in the range of pH 5.0 to 5.5 and its rate is 56.8%, The order of ion concentration In precipitation is SO42->NO3->Cl- in case of anion and $Ca^{2+}$>$NH_4^{+}$>$Na^+$>$Mg^{2+}$ in case of cation. It is found from our analysis that the correlation coefficient among the precipitation pH and ion components is below r=0.3, while the correlation coefficient between $SO_4^{2-}$ and NO_3^{-}$, $Na^+$ and $Cl^+$ is above r=0.8, respectively. The mean pH of precipitation is 4.8 under the westerly wind and 5.2 under the easterly wind. The concentrations of anion and cation under the westerly wind are more than the concentrations under the easterly wind. In autumn, the concentration of Na+ and $Cl^+$ under the easterly wind are higher than the concentration under the westerly wind. The correlation coefficients between wind speed and pH, ion components show very low correlation of -0.41 r 0.2. But the present study show that the correlation coefficient between wind speed and pH of precipitation is positive and the correlation coefficients between wind speed and ion concentration is negative.

• Journal of Korean Society for Atmospheric Environment
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• v.11 no.1
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• pp.57-68
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• 1995

Precipitation samples were collected by a wet-only automatic acid precipitation sampler at Kangwha island on the western coast in Korea, through January until December 1992. pH, electric conductivity and the concentrations of major water-soluble ion components such as N $H_{4}$$^{+}$, $Ca^{2+}$, $K^{+}$, $Mg^{2+}$, N $a^{+}$, N $O_{3}$$^{[-10]}$ , S $O_{4}$$^{2-}$ and C $l^{[-10]}$ were measured. From the result of checking the validity for assesment of pollution level of precipitation samples by pH using correlation analysis between pH and major components, and t-test of chemical composition between acid rain and non-acid rain, pH proved to be not satisfactory for its pillution level. A more comprehensive method is therefore required. In order to estimate the monthly analytical result of chemical composition of precipitation samples comprehensively, a cluster analysis was used among the various multivariate statistical analysis. As a result of making a cluster analysis for separating the monthly precipitation samples into homogeneous patterns by setting the concentrations of nine major water-soluble ion components as a variable, three homogeneous patterns were obtained. The first pattern was a group of months having average ion concentrations, the second a guoup of months having low ion concentration, and the third a group of months having high ion concentrations. Thus, it was indicated that the pollution level of precipitation was higher on February and lower on May, June, August and September than the other months. As a result, this analysis method could be estimated the chemical coposition of precipitation regionally as well as monthly.monthly.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.2
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• pp.89-100
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• 1999

The rain water samples were collected at Chunchon and Seoul by using wet only automatic sampler from January 1996 through 1997. The daily base rain water samples collected over than 95% rainy events components, $SO_4^{-2}$, $NO_3^-$, $CI^-$, NH_4^+$, $Ca^{2+}$, $Mg^{2+}$, $Na^+$, and $K^+$, by ion chromatography. In 1996, about 77% of sampled rain water showed below pH 5.6 and the 60% of rain water was lower than pH 5.0. The volume weighted average pH was 4.7 at all sites. In 1997, the volume weighted average pH was 4.6 and 4.9 at Seoul and Chunchon, respectively. Among the rain water samples,, 87% and 55% fo samples showed below than pH 5.6 and 5.0, respectively. The pH value of Chunchon was significantly (p＜0.05) lower than Seoul at the rain samples for less than 20mm rainfall. However conductivity of the rain samples were 20.9$\mu$S/cm for 1996 and 27.7$\mu$S/cm for 1997 at Seoul, and 19.1$\mu$S/cm for 1996 and 14.1$\mu$S/cm for 1997 at Chunchon. $H_2SO_4$ and $HNO_3$ contributed 65.9% and 29.6% of free acidity at Seoul, respectively. The ratio of [$NO_3^-$]/[nss-$SO_4^{-2}$] were 0.43 at Seoul and 0.51 at Chunchon for rain samples for less than 20mm rainfall. The annual wet deposition of $CI^-$, $NO_3^-$, $SO_4^{-2}$, $H^+$M, $Na^+$, NH_4^+$, $K^+$, $Mg^{2+}$, and $Ca^{2+}$, respectively, 568.8kg/$ extrm{km}^2$, 1489.3kg/$\textrm{km}^2$, 3184.8kg/$\textrm{km}^2$, 20.9kg/$\textrm{km}^2$, 249.4kg/$\textrm{km}^2$, 1091.2kg/$\textrm{km}^2$, 189.8kg/ $\textrm{km}^2$, 90.2kg/$\textrm{km}^2$ and 702.4kg/$\textrm{km}^2$ at Seoul for 1996; 656.4kg/$\textrm{km}^2$, 2029.7kg/$\textrm{km}^2$, 3280.7kg/$\textrm{km}^2$, 27.2kg /$\textrm{km}^2$, 229.4kg/$\textrm{km}^2$, 1063.9kg/$\textrm{km}^2$, 106.9kg/$\textrm{km}^2$, 78.2kg/$\textrm{km}^2$, 645.3kg/$\textrm{km}^2$ at Seoul for 1997; 116.9kg/ $\textrm{km}^2$, 983.3kg/$\textrm{km}^2$, 1797.0kg/$\textrm{km}^2$, 21.4kg/$\textrm{km}^2$, 83.2kg/$\textrm{km}^2$, 648.1kg/$\textrm{km}^2$, 78.0kg/$\textrm{km}^2$, 22.2kg/$\textrm{km}^2$, 368.8kg/$\textrm{km}^2$ at chunchon for 1996; 100.2kg/$\textrm{km}^2$, 1077.6kg/$\textrm{km}^2$, 1754.0kg/$\textrm{km}^2$, 13.4kg/$\textrm{km}^2$, 146.0kg/$\textrm{km}^2$, 602.3kg/$\textrm{km}^2$, 88.8kg/$\textrm{km}^2$, 16.2kg/$\textrm{km}^2$ and 206.8kg/$\textrm{km}^2$ at chunchon for 1997.

• Korean Journal of Environmental Biology
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• v.36 no.4
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• pp.626-637
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• 2018

In this study, a series of survey were conducted to identify the distribution patterns of macrobenthos at the Bongam sand tidal flat in Masan Bay. We collected macrobenthos at 9 sampling sites twice in June and September of every year from 2012 to 2017 using a box core sampler (collecting area, $0.025m^2$). There was a total of 50 species with a community density of $6,388ind.m^{-2}$ and a biomass of $313.9g\;wet\;m^{-2}$ during the study period. Polychaetes had the highest number of species and density among the macrofauna, but the mollusks had the largest biomass. The number of species ranged from 10 to 25 during study period but increased to over 20 species in 2014. The density which ranged from $1,508ind.m^{-2}$ to $12,008ind.m^{-2}$ rapidly increased in 2015. The dominant species were all polychaetes such as Heteromastus filiformis, Prionospio japonicus, Hediste diadroma, and Neanthes succinea. The mean diversity index ranged from 1.2 to 1.9, richness index from 1.2 to 2.4, and evenness index from 0.5 to 0.9. From the cluster analysis results, there was a spatial difference in the similarity of faunal composition of macrobenthos and this pattern was maintained throughout the study period, that is, the temporal similarities were higher than the spatial similarities. There was a change in community composition from June 2014 to June 2015 in most of the sampling sites. During this time, the dominant species also changed from H. filiformis and N. succinea to H. filiformis and H. diadroma. The density of opportunistic species such as Capitella capitata and Polydora ligni decreased compared to the early 2000s while the population of H. diadroma increased from 2015. There was little ecological information on H. diadroma such as when and where this species occurred.