Hyungsuk Kim, Jeongin Kim, Sunghong Lee, Jae-won Choi, Y. Kim
In this study, according to determination of nitrogen (δN) and oxygen (δO) from nitrate (NO 3 ) in water for 2 years, 2016-2017, Gunwi, Korea, the origin of pollutants in supply water could be found. The sampling sites are including 6 points, Donggok, Yonga, Janggok1 and 2, reservoir of dam and Ingak temple around Gunwi Dam, Korea. The water samples were determined NO 3 -N using Ion Chromatography and Nitrogen (δN) and Oxygen (δO) stable isotope ratio in nitrate and isotope ratio mass spectrometry, respectively. The standard deviation of determined standard materials is less than 0.2‰ for δN AIR and 0.2‰ for δO VSMOW in water. The origin of the supply water pollution was analyzed through the correlation between the values of δN and δO in nitrate. The values indicated that these sources were originated sewage and livestock manure in the Dam. The dominant contribution of water pollutants was calculated about 50% from Donggok location in this study. In addition, the location of Yonga where has the small inflow rate also constantly contributed to the Dam.
{"title":"Identification of Pollutants Sources of Water Supply using Nitrogen (δ15N) and Oxygen (δ18O) Stable Isotope Ratio in Nitrate","authors":"Hyungsuk Kim, Jeongin Kim, Sunghong Lee, Jae-won Choi, Y. Kim","doi":"10.36278/jeaht.22.3.145","DOIUrl":"https://doi.org/10.36278/jeaht.22.3.145","url":null,"abstract":"In this study, according to determination of nitrogen (δN) and oxygen (δO) from nitrate (NO 3 ) in water for 2 years, 2016-2017, Gunwi, Korea, the origin of pollutants in supply water could be found. The sampling sites are including 6 points, Donggok, Yonga, Janggok1 and 2, reservoir of dam and Ingak temple around Gunwi Dam, Korea. The water samples were determined NO 3 -N using Ion Chromatography and Nitrogen (δN) and Oxygen (δO) stable isotope ratio in nitrate and isotope ratio mass spectrometry, respectively. The standard deviation of determined standard materials is less than 0.2‰ for δN AIR and 0.2‰ for δO VSMOW in water. The origin of the supply water pollution was analyzed through the correlation between the values of δN and δO in nitrate. The values indicated that these sources were originated sewage and livestock manure in the Dam. The dominant contribution of water pollutants was calculated about 50% from Donggok location in this study. In addition, the location of Yonga where has the small inflow rate also constantly contributed to the Dam.","PeriodicalId":15758,"journal":{"name":"Journal of Environmental Analysis, Health and Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84225221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
H. Seo, In-sook Kang, K. Son, Yang Eun, Won-Sam Jeong, Seong-Jun Kim
In this study, multivariate statistical analysis was applied to analyze the trend of water quality and water quality in the Fourth reservoir over the last 10 years. Correlation analysis between water quality variables showed that, the correlation coefficient between COD and TOC, which is an indirect indicator of organic matter, showed a high correlation of 0.608, while water temperature showed a positive correlation with pH of 0.515 and a negative correlation with DO of -0.716. Principal component and factor analyses showed that the four major components were extracted from the total water quality and contributed 72.9% of the total variance. When analyzed for cyanobacteria occurrence, three major components were extracted and contributed 67.2% of the total variance. Factor loadings analysis of water quality variables on the factors identified the first factors as COD and TOC. Water quality of the Fourth reservoir was found to be influenced by seasonal effects such as rainfall and organic matter, in addition to the effects of phytoplankton proliferation and nutrient influx.
{"title":"Evaluation of Water Quality Characteristics Using Multivariate Statistical Analysis in the Fourth Reservoir","authors":"H. Seo, In-sook Kang, K. Son, Yang Eun, Won-Sam Jeong, Seong-Jun Kim","doi":"10.36278/jeaht.22.3.117","DOIUrl":"https://doi.org/10.36278/jeaht.22.3.117","url":null,"abstract":"In this study, multivariate statistical analysis was applied to analyze the trend of water quality and water quality in the Fourth reservoir over the last 10 years. Correlation analysis between water quality variables showed that, the correlation coefficient between COD and TOC, which is an indirect indicator of organic matter, showed a high correlation of 0.608, while water temperature showed a positive correlation with pH of 0.515 and a negative correlation with DO of -0.716. Principal component and factor analyses showed that the four major components were extracted from the total water quality and contributed 72.9% of the total variance. When analyzed for cyanobacteria occurrence, three major components were extracted and contributed 67.2% of the total variance. Factor loadings analysis of water quality variables on the factors identified the first factors as COD and TOC. Water quality of the Fourth reservoir was found to be influenced by seasonal effects such as rainfall and organic matter, in addition to the effects of phytoplankton proliferation and nutrient influx.","PeriodicalId":15758,"journal":{"name":"Journal of Environmental Analysis, Health and Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74015980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An applicability evaluation was performed for an automatic sampling strategy to respond to chemical accidents and the method was compared with manual grab sampling. The auto sampling includes a deep-well pump and an auto reverse filtration system, which resulted in up to a maximum of 6h of running time. Sampling was carried out at three locations on May 22 and June 20, 2019 and pH, dissolved oxygen (DO), and temperature were measured on site. In addition, samples collected via the two methods were analyzed for BTEX (benzene, toluene, ethylbenzene and xylene), three elements (Fe, Mn and Zn) and microorganic pollutants. BTEX was not detected at all at the sites and the concentration ranges were 5.0 to16.0 μg/L for Fe, 0.9 to 65.0 μg/L for Mn, and N.D. to 24.0 μg/L for Zn. Target screening was performed for 15 micro organic pollutants including pharmaceuticals and pesticides and for the 12 compounds that were quantitatively analyzed, the concentration range was N.D. to 55.0 ng/L. We measured the concentrations and the values for the two sampling methods were compared, resulting in 14 out of 17 samples showing good agreement between the two methods. As a result, this automatic sampling method is expected to be applied in various fields (e.g., mobile analysis system).
{"title":"Verification of Automatic Water Sampling System for Chemical Spill Events","authors":"Daeho Kang, Junho Jeon, M. Song, Jin-Sung Ra","doi":"10.36278/jeaht.22.3.126","DOIUrl":"https://doi.org/10.36278/jeaht.22.3.126","url":null,"abstract":"An applicability evaluation was performed for an automatic sampling strategy to respond to chemical accidents and the method was compared with manual grab sampling. The auto sampling includes a deep-well pump and an auto reverse filtration system, which resulted in up to a maximum of 6h of running time. Sampling was carried out at three locations on May 22 and June 20, 2019 and pH, dissolved oxygen (DO), and temperature were measured on site. In addition, samples collected via the two methods were analyzed for BTEX (benzene, toluene, ethylbenzene and xylene), three elements (Fe, Mn and Zn) and microorganic pollutants. BTEX was not detected at all at the sites and the concentration ranges were 5.0 to16.0 μg/L for Fe, 0.9 to 65.0 μg/L for Mn, and N.D. to 24.0 μg/L for Zn. Target screening was performed for 15 micro organic pollutants including pharmaceuticals and pesticides and for the 12 compounds that were quantitatively analyzed, the concentration range was N.D. to 55.0 ng/L. We measured the concentrations and the values for the two sampling methods were compared, resulting in 14 out of 17 samples showing good agreement between the two methods. As a result, this automatic sampling method is expected to be applied in various fields (e.g., mobile analysis system).","PeriodicalId":15758,"journal":{"name":"Journal of Environmental Analysis, Health and Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89277274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jong-Yeon Hwang, Sin-Woo Lee, Kum-hee Kim, Y. Huh, E. Yoo, Bokyoung Kim, Hee Jung Kim, Hyeri Lee, S. Ko, Jeehye Kim, Sooa Jeon, J. Lee, Kyung Ro Lee, Suk-Young Hong, Hyun Mi Chung, Jongwoo Choi
One of the most important purposes of a validation method is to verify whether a test method is suitable for the purpose of the test. In this study, validation parameters that are used by national and international institutes for test and inspection bodies are classified. As a result of classifying these general factors, method validation parameters were performed, including the following cases: 1 the confirmation of a new test method, 2 comparison between a non-standardized test method and standardized method, 3confirmation of a test method needing such extensions as a test method verification, verification of the test method applied between other test institutes or analysts, 4 verification of the required similarity between test methods, and 5 revalidation of the previously verified test methods. The general parameters applied in the validation processes were classified as follows; specificity, selectivity, linearity, sensitivity, accuracy, precision, detection limit uncertainty, quantitative limit, and range. By a comparison of the validation guidelines or guideline parameters applied by the test and inspection bodies, the survey results were considered to be useful in preparing validation guidelines for environmental testing and inspection methods.
{"title":"Comparison of Method Validation for Test and Inspections","authors":"Jong-Yeon Hwang, Sin-Woo Lee, Kum-hee Kim, Y. Huh, E. Yoo, Bokyoung Kim, Hee Jung Kim, Hyeri Lee, S. Ko, Jeehye Kim, Sooa Jeon, J. Lee, Kyung Ro Lee, Suk-Young Hong, Hyun Mi Chung, Jongwoo Choi","doi":"10.36278/jeaht.22.3.104","DOIUrl":"https://doi.org/10.36278/jeaht.22.3.104","url":null,"abstract":"One of the most important purposes of a validation method is to verify whether a test method is suitable for the purpose of the test. In this study, validation parameters that are used by national and international institutes for test and inspection bodies are classified. As a result of classifying these general factors, method validation parameters were performed, including the following cases: 1 the confirmation of a new test method, 2 comparison between a non-standardized test method and standardized method, 3confirmation of a test method needing such extensions as a test method verification, verification of the test method applied between other test institutes or analysts, 4 verification of the required similarity between test methods, and 5 revalidation of the previously verified test methods. The general parameters applied in the validation processes were classified as follows; specificity, selectivity, linearity, sensitivity, accuracy, precision, detection limit uncertainty, quantitative limit, and range. By a comparison of the validation guidelines or guideline parameters applied by the test and inspection bodies, the survey results were considered to be useful in preparing validation guidelines for environmental testing and inspection methods.","PeriodicalId":15758,"journal":{"name":"Journal of Environmental Analysis, Health and Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80058176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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