• Korean Journal of Food Science and Technology
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• v.30 no.1
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• pp.206-212
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• 1998

This study was undertaken to explore the applicability of glutathione S-transferase (GST) activity as a predictable indicator to monitor chemical pollution in shells and fishes utilized for food. There were some variations in the basal level of GST activity depending on species tested. Ark shells, Anadara satowi, showed the highest normal enzyme activity, followed by catfish and marine mussels, Mytilus coruscus. White clams, Meretrix lusoria, Israeli carp and catfish had lower activity. When A. satowi was exposed to 3-methyl-cholanthrene (3-MC), a prototypic polycyclic aromatic hydrocarbon for 1 week, GST activity decreased by about 30%. This reduction in GST activity induced by 3-MC did not recover until two weeks after the cessation of exposure. GST activity increased in response to 3-MC in most of the other species studied. The GST elevation in M. coruscus attained its maxinum of about 200% at the termination of 3-MC exposure maintaining this level up to 2 weeks, and declined gradually thereafter. 3-MC also induced GST activity in lsraeli carp in a similar fashion to M. coruscus. Phenobarbital induced GST activity both in M. coruscus and lsraeil carp. Other chemicals. such as clofibrate, butylated hydroxyanisole. hexachlorobenzene, and oxolinic acid did not change the enzyme activity significantly in most speciel. Phenol depressed GST activity only in lsraeli carp. These results suggest that the basal level of GST activity is somewhat variable and that the direction of change in response to chemicals seems to be related to its normal activity. The change in enzyme activity can be a preditable indicator of some environmental chemicals such as PAHs and phenol.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.6
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• pp.373-381
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• 2012

An automatic flow and water quality monitoring system was applied to estimate pollutant loads to an urban stream during storm events in DTV (Daeduk Techno Valley), Daejeon, Korea. The monitoring system consists of rainfall gage, ultrasonic water level meter, water quality sensors for DO, temperature, pH, conductivity, turbidity and automatic water sampler for further laboratory analysis. All data are transmitted through on-line system and the monitoring system is designed to be controlled manually in the field and remotely from laboratory computer. Flow rates were verified with field measurements during storm events and showed good agreements. Automatic sampler was used to collect real time samples and analyzed for BOD, COD, TN, TP, SS and other pollutant concentrations in the laboratory. SWMM (Storm Water Management Model) urban watershed model was applied and calibrated using the observed flow and water quality data for the study area. While flow modeling results showed good agreement for all events, water quality modeling results showed variable levels of agreement. These results indicate that current options in the SWMM model to predict pollutant build up and wash-off effects are not sufficient to satisfy modeling of all the rainfall events under study and thus need further modification. This study showed the automatic monitoring system can be used to provide data to assist further refinement of modeling accuracy. This automatic stormwater monitoring and modeling system can be used to develop basin scale water quality management strategies of urban streams in storm events.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.177-191
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• 2021

One of the major causes of serious air pollution worldwide is emissions from road transportation. A number of countries are working to reduce vehicle emissions, and the Seoul Metropolitan Government is also implementing active policies to reduce emissions by setting a target of 40% by 2030. Implementing these policies requires the introduction of practical indicators. Most of the domestic emissions are calculated by the emission coefficient, a function of speed at the National Institute of Environmental Research under the Ministry of Environment, but the dynamic variable speed is limited to being used as an indicator of the number of eco-friendly vehicles. Therefore, this study calculated the emission rates in Seoul using the vehicle registration data of Seoul and the vehicle inspection data from the Korea Transportation Safety Authority. The tendency of emissions was determined according to key variables such as vehicle type, fuel and mileage. Emissions were based on carbon monoxide, hydrocarbons, nitrogen oxides and particulate matter measured by vehicle inspection from the Korea Transportation Safety Authority. As a result, the emission rates showed a significant trend according to the model year and mileage. This can be used as a policy indicator to preferentially switch commercial vehicles with old model years and long mileage when switching eco-friendly vehicles in Seoul.

• Journal of Preventive Medicine and Public Health
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• v.32 no.1
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• pp.60-64
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• 1999

Objectives. Changes in lung function are frequently used as biological markers to assess the health effects of criteria air pollutants. We tried to formulate the prediction models of pulmonary functions based on height, weight, age and gender, especially for children aged 12 years who are commonly selected for the study of health effects of the air pollution. Methods. The target pulmonary function parameters were forced vital capacity(FVC) and forced expiratory volume in one second(FEV1). Two hundreds and fifity-eight male and 301 female 12-year old children were included in the analysis after excluding unsatisfactory tests to the criteria recommended by American Thoracic Sosiety and excluding more or less than 20% predicted value by previous prediction equations. The weight prediction equation using height as a independent variable was calculated, and then the difference of observed weight and predicted weight (i.e. residual) was used as the independent variable of pulmonary function prediction equations with height. Results. The prediction equations of FVC and FEV1 for male are FVC(ml) = $50.84{\times}height(cm)+7.06{\times}weight$ residual 4838.86, FEV1(ml) = $43.57{\times}height(cm)+3.16{\times}weight$ residual - 4156.66, respectively. The prediction equations of FVC and FEV1 for female are FVC(ml) = $42.57{\times}height(cm)+12.50{\times}weight$ residual - 3862.39, FEV1(ml) = $36.29{\times}height(cm)+7.74{\times}weight$ residual - 3200.94, respectively.

• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.341-349
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• 2020

The present study aims to investigate the sequential mediation model in the relationships between optimistic bias, subjective perception, risk perception, and the future time perspective in terms of a particulate matter and depression, using the sequential mediation model. An online self-reported survey was conducted on 545 participants who agreed to participate in the current study. We considered depression as a dependent variable, optimistic bias as an independent variable, and subjective perception of particulate matter, the risk perception of particulate matter, future-time-perspective as mediators. The sequential mediation analysis was conducted using the SPSS Macro. The results show that optimistic bias was not directly related to depression, but was related to indirect paths through the subjective perception of particulate matter, the risk perception of particulate matter, and future time perspective. More specifically, the lack of optimistic bias was related to a tendency to subjectively perceive the quality of air pollution more seriously and a limited future time perspective, which subsequently related to depression. Future studies should pay more attention to the effects of particulate matter on the quality of life and mental health.

• Journal of Korea Water Resources Association
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• v.54 no.2
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• pp.121-133
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• 2021

Suspended Solids (SS) generated in rivers are mainly introduced from non-point pollutants or appear naturally in the water body, and are an important water quality factor that may cause long-term water pollution by being deposited. However, the conventional method of measuring the concentration of suspended solids is labor-intensive, and it is difficult to obtain a vast amount of data via point measurement. Therefore, in this study, a model for measuring the concentration of suspended solids based on remote sensing in the Nakdong River was developed using Sentinel-2 data that provides high-resolution multi-spectral satellite images. The proposed model considers the spectral bands and band ratios of various wavelength bands using a machine learning model, Support Vector Regression (SVR), to overcome the limitation of the existing remote sensing-based regression equations. The optimal combination of variables was derived using the Recursive Feature Elimination (RFE) and weight coefficients for each variable of SVR. The results show that the 705nm band belonging to the red-edge wavelength band was estimated as the most important spectral band, and the proposed SVR model produced the most accurate measurement compared with the previous regression equations. By using the RFE, the SVR model developed in this study reduces the variable dependence compared to the existing regression equations based on the single spectral band or band ratio and provides more accurate prediction of spatial distribution of suspended solids concentration.

• Journal of Environmental Health Sciences
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• v.29 no.1
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• pp.51-61
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• 2003

Pollution purification using titanium dioxide (TiO$_2$) photocatalyst has attracted a great deal of attention with increasing number of relent environmental problems. Currently, the application of TiO$_2$ photocatalyst has been focused on purification and treatment of waste water. However. the use of conventional TiO$_2$ powder photocatalyst results in disadvantage of stirring during the reaction and of separation after the reaction. And the usage of artificial UV lamp has made the cost of photocatalyst treatment system high. Consequently, we herein studied the pilot-scale design to aid in optimization of the energy-saving process for more through development and reactor design by solar light/UV lamp/ TiO$_2$system. In this study, we manufactured the TiO$_2$sol by sol-gel method. According to analysis by XRD, SEM and TEM, characterization of TiO$_2$ sol were nano-size (5-6 nm) and anatase type. Inorganic binder (SiO$_2$) was added to TiO$_2$ lot to be coated for support strongly, and support of ceramic bead was used to lower separation rate that of glass bead The influences were studied of various experimental parameters such as TiO$_2$ quantity, pH, flow rate. additives, pollutants concentration, climate condition and reflection plate by means of reaction time of the main chararteristics of the obtained materials. In water treatment system, variable realtor as solar light/ or UV lamp according to climate condition such as sunny and cloudy days treated the phenol and E-coli(Escherichia coli) effectively.

• Journal of Environmental Health Sciences
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• v.41 no.2
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• pp.90-101
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• 2015

Objective: This study was conducted to develop a chemical oxygen demand (COD) regression model using water quality monitoring data (January, 2014) obtained from the Han River auto-monitoring stations. Methods: Surface water quality data at 198 sampling stations along the six major areas were assembled and analyzed to determine the spatial distribution and clustering of monitoring stations based on 18 WQPs and regression modeling using selected parameters. Statistical techniques, including combined genetic algorithm-multiple linear regression (GA-MLR), cluster analysis (CA) and principal component analysis (PCA) were used to build a COD model using water quality data. Results: A best GA-MLR model facilitated computing the WQPs for a 5-descriptor COD model with satisfactory statistical results ($r^2=92.64$,$Q{^2}_{LOO}=91.45$,$Q{^2}_{Ext}=88.17$). This approach includes variable selection of the WQPs in order to find the most important factors affecting water quality. Additionally, ordination techniques like PCA and CA were used to classify monitoring stations. The biplot based on the first two principal components (PCs) of the PCA model identified three distinct groups of stations, but also differs with respect to the correlation with WQPs, which enables better interpretation of the water quality characteristics at particular stations as of January 2014. Conclusion: This data analysis procedure appears to provide an efficient means of modelling water quality by interpreting and defining its most essential variables, such as TOC and BOD. The water parameters selected in a COD model as most important in contributing to environmental health and water pollution can be utilized for the application of water quality management strategies. At present, the river is under threat of anthropogenic disturbances during festival periods, especially at upstream areas.

• Journal of Korea Water Resources Association
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• v.42 no.4
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• pp.297-307
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• 2009

For reliable water quality simulation by semi distributed model, accurate daily runoff simulation should have preceded. In this study, newly developed channel routing method which is nonlinear storage method is combination of Muskingum routing method and variable storage routing method and temporally weighted average curve number method were applied for effect analysis of water quality simulation. Developed modules, which are added in SWAT models and simulation, were conducted for the Chungju dam watershed. The simulation result by each module applied effect. As a result of analysis contribute water quality modeling, nonlinear storage method is more effective than temporally weighted average curve number method. Nutrient loading discharge was affected by development of runoff delaying from improvement of channel routing, because of characteristics of nonpoint source pollution.

• Atmosphere
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• v.26 no.4
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• pp.673-686
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• 2016

Understanding limitation of simulation for Planetary Boundary Layer (PBL) height in mesoscale meteorological model is important for accurate meteorological variable and diffusion of air pollution. This study examined the accuracy for simulated PBL heights using two different PBL schemes (MYJ, YSU) in Weather Research and Forecasting (WRF) model during the radiosonde observation period. The simulated PBL height were verified using atmospheric sounding data obtained from radiosonde observations that were conducted during 5 months from August to December 2014 over the Gumi weir in Nakdong river. Four Dimensional Data Assimilation (FDDA) using radiosonde observation data were conducted to reduce error of PBL height in WRF model. The assessment result of PBL height showed that RMSE with YSU scheme were lower than that with MYJ scheme in the day and night time, respectively. Especially, the WRF model with YSU scheme produced lower PBL height than with the MYJ scheme during night time. The YSU scheme showed lower RMSE than the MYJ scheme on sunny, cloudy and rainy day, too. The experiment result of FDDA showed that PBL height error were reduced by FDDA and PBL height at the nudging coefficient of $3.0{\times}10^{-1}$ (YSU_FDDA_2) were similar to observation compared to the nudging coefficient of $3.0{\times}10^{-4}$ (YSU_FDDA_1).