• Journal of Environmental Impact Assessment
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• v.26 no.6
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• pp.418-430
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• 2017

The quality of surface water is a very important issue to use various demands like as drinking water, industrial, agricultural and recreational usages. There has been an increasing demand for monitoring water quality of many rivers by regular measurements of various water quality variables. However precise and effective monitoring is not enough, if the acquired dataset is not analyzed thoroughly. Therefore, the aim of this study was to estimate differences of seasonal and regional water quality using multivariate data analysis for each investing tributaries in Han River. Statistical analysis was applied to the data concerning 11 mainly parameters (flow, water temperature, pH, EC, DO, BOD, COD, SS, TN, TP and TOC) for the time period 2012~2016 from 12 sampling sites. The seasonal water quality variations showed that each of BOD, TN, TP and TOC average concentration in spring and winter was higher than that of summer and fall, respectively. In summer each flow rate and average concentration of SS was higher than any other seasons, respectively. The correlation analysis were explained that EC had a strong relationship with BOD (r=0.857), COD (r=0.854), TN (r=0.899) and TOC (r=0.910). According to principal component analysis, five principal components (Eigenvalue > 1) are controlled 98.0% of variations in water quality. The first component included TP, DO, pH. The second component included EC, TN. The third component included SS. The fourth component included flow. The last component included Temp. Cluster analysis classified that spring is similar to fall and winter with water quality parameters. AnyA, WangsA, JungrA and TancA were identified as affected by organic pollution. Cluster analysis derived seasonal differences with investigating sites and better explained the principal component analysis results.

• Journal of Food Hygiene and Safety
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• v.37 no.6
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• pp.385-393
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• 2022

The contamination level of inorganic arsenic, a human carcinogen, was investigated in 87 grains and 66 processed grain foods. Two inorganic arsenic species arsenite (As(III)) and arsenate (As(V)) and four organic arsenic monomethylarsonic acid, dimethylarsinic acid, arsenobetaine, arsenocholine were analyzed using HPLC-ICP/MS with high separation and sensitivity and ICP/MS was used to quantify total arsenic. Inorganic arsenic was detected in all grains. And the total arsenic in grains consists of about 70-85% inorganic arsenic and about 10-20% DMA. The concentration of inorganic arsenic was high in rice and black rice cultivated in paddy soil with irrigated water, while the miscellaneous grain in field was low. Mean concentration of inorganic arsenic in rice germ, brown rice and polished rice was 0.160 mg/kg, 0.135 mg/kg, 0.083 mg/kg, respectively, indicating that rice bran contains more arsenic. In processed grain foods, inorganic arsenic concentration varied according to the kind of ingredients and content, and the detection amount was high in processed food with brown rice and germ. The arsenic content of all samples did not exceed each standard, but the intake frequency is high and it is considered that continuous monitoring is necessary for food safety.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.5 no.3
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• pp.195-207
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• 2000

Organic and inorganic characteristics including bacterial cell number, enzyme activity, nutrients, and heavy metals have been monitored in twelve acrylic experimental tanks for two weeks to estimate and compare self-purification capacities in two Korean wet-land environments, tidal flat and rice field, which are possibly different with the environments in other countries because of their own climatic conditions. FW tanks, filled with rice field soils and fresh water, consist of FW1&2 (with paddy), FW3&4 (without paddy), and FW5&6 (newly reclaimed, without paddy). SW tanks, filled with tidal flat sediments and salt water, are SW1&2 (with anoxic silty mud), SW3&4 (anoxic mud), and SW5&6 (suboxic mud). Contaminated solution, which is formulated with the salts of Cu, Cd, As, Cr, Pb, Hg, and glucose+glutamic acid, was spiked into the supernatent waters in the tanks. Nitrate concentrations in supernatent waters as well as bacterial cell numbers and enzyme activities of soils in the FW tanks (except FW5&6) are clearly higher than those in the SW tanks. Phosphate concentrations in the SW1 tank increase highly with time compared to those in the other SW tanks. Removal rates of Cu, Cd, and As in supematent waters of the FW5&6 tanks are most slow in the FW tanks, while the rates in SW1&2 are most fast in the SW tanks. The rate for Pb in the SW1&2 tanks is most fast in the SW tanks, and the rate for Hg in the FW5&6 tanks is most slow in the FW tanks. Cr concentrations decrease generally with time in the FW tanks. In the SW tanks, however, the Cr concentrations decrease rapidly at first, then increase, and then remain nearly constant. These results imply that labile organic materials are depleted in the FW5&6 tanks compared to the FW1&2 and FW3&4 tanks. Removal of Cu, Cd, As from the supernatent waters as well as slow removal rates of the elements (including Hg) are likely due to the combining of the elements with organic ligands on the suspended particles and subsequent removal to the bottom sediments. Fast removal rates of the metal ions (Cu, Cd, As) and rapid increase of phosphate concentrations in the SW1&2 tanks are possibly due to the relatively porous anoxic sediments in the SW1&2 tanks compared to those in the SW3&4 tanks, efficient supply of phosphate and hydrogen sulfide ions in pore wates to the upper water body, complexing of the metal ions with the sulfide ions, and subsequent removal to the bottom sediments. Organic materials on the particles and sulfide ions from the pore waters are the major factors constraining the behaviors of organic/inorganic elements in the supernatent waters of the experimental tanks. This study needs more consideration on more diverse organic and inorganic elements and experimental conditions such as tidal action, temperature variation, activities of benthic animals, etc.

• Solar Energy
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• v.13 no.2_3
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• pp.65-78
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• 1993

An overdose of fossil fuel for greenhouse heating causes not only the high cost and low quality of agricultural products, but also the environmental pollution of farm village. To solve these problems it is desirable to maximize the solar energy utilization for the heating of greenhouse in winter season. In this study phase change materials were selected to store solar energy concentratively for heating the greenhouse and their characteristics of thermal energy storage were analyzed. The results were summarized as follows. The organic $C_{28}H_{58}$, and the inorganic $CH_3COONa{\cdot}3H_2O\;and\;Na_2SO_4{\cdot}10H_2O$ were selected as low temperature latent heat storage materials. The equation of critical radius was derived to define the generating mechanism of the maximum latent heat of phase change materials. The melting point of $C_{28}H_{58}$ was $62^{\circ}C$, and the latent heat was $50.0{\sim}52.0kcal/kg$. The specific heat of liquid and solid phase was $0.54{\sim}0.69kcal/kg^{\circ}C$ and $0.57{\sim}0.75kcal/kg^{\circ}C$ respectively. The melting point of $CH_3COONa{\cdot}3H_2O$ was $61{\sim}62^{\circ}C$, the latent heat was $64.9{\sim}65.8$ kcal/kg and the specific heat of liquid and solid phase was respectively $0.83kcal/kg^{\circ}C$ and $0.51{\sim}0.52kcal/kg^{\circ}C$. The melting point of $Na_2SO_4{\cdot}10H_2O$ was $30{\sim}30.9^{\circ}C$, the latent heat was 53.0 kcal/kg and the specific heat of liquid and solid phase was respectively $0.78{\sim}0.89kcal/kg^{\circ}C$ and $0.50{\sim}0.7kcal/kg^{\circ}C$ When the urea of 21.85% was added to control the melting point of $Na_2SO_4{\cdot}10H_2O$ and the phase change cycles were repeated from 0 to 600, the melting point was $16.7{\sim}16.0^{\circ}C$ and the latent heat was $36.0{\sim}28.0kcal/kg^{\circ}C$.