• Proceedings of the Korean Environmental Sciences Society Conference
• /
• 2020.10a
• /
• pp.157-157
• /
• 2020

• Industrial Engineering and Management Systems
• /
• v.10 no.2
• /
• pp.128-133
• /
• 2011

This paper presents a study on product design optimization to reduce the environmental impact of machining. The objective is to analyze the effect of changing the product design parameters such as its dimensions, and basic features on the environmental impact of machining process in terms of its energy consumption, waste produced and the chemicals and other consumables used up during the process. To realize this objective, we used a CAD model of a product with different design scenarios, and analyze their energy consumption using an environmental impact calculator method developed. The waste produced, and the consumables used up, such as lubricants and coolants were analyzed using environmental emission factors. Optimization methods using Genetic Algorithm and Goal Programming are applied to the product design parameters in order to get the best possible product dimensions with the least environmental impact of the machining process.

• Environmental Engineering Research
• /
• v.16 no.2
• /
• pp.97-102
• /
• 2011

This study investigates the treatment of pigment wastewater using a sequential batch reactor (SBR) followed by dissolved ozone flotation-pressurized ozone oxidation treatement (DOF-$PO_2$). The process efficiency has been evaluated at the lab scale on the basis of water quality parameters. In addition, the effect of pure oxygen and air was investigated on the removal of COD, BOD, and TN in the SBR process. It was observed that under comparable conditions the removal efficiencies of these water quality parameters using pure oxygen and air were similar. The effect of the recycle rate was also investigated for its impact on the water quality parameters using different ozone dissolving pressures in a DOF process in order to optimise conditions. The results conclude that the use of an SBR and ozone contact by DOF-$PO_2$ is a highly effective treatment for pigment wastewater and aids in the achievement of effluent discharge criteria.

• Applied Chemistry for Engineering
• /
• v.30 no.6
• /
• pp.742-748
• /
• 2019

Influence of several experimental parameters (e.g., initial dye concentration, pH, distance between electrodes, applied voltage, electrical conductivity, current density, and reaction time) on the performance of electrocoagulation (EC) process for the removal of acid blue 25 (AB25) was studied. A bipolar batch reactor was used to test the impact of the parameters. The removal efficiency (RE) of AB25 dye was promoted by increasing the contact time, voltage, electrical conductivity, and applied current density. In contrast, RE of AB25 decreased with higher level of AB25 and the longer distance between electrodes. The removal efficiency increased consistently until pH 7, but decreased above pH 7. The maximum efficiency of AB25 removal above 90% was obtained at a voltage of 60 V, reaction time of 90 min, distance between electrodes of 0.5 cm, initial concentration of 25 mg/L, conductivity of 3,000 μS/cm and pH of 7. These results imply that the high RE of AB25 dye from the aqueous solution can be achieved by EC process.

• Journal of Environmental Science International
• /
• v.25 no.10
• /
• pp.1417-1426
• /
• 2016

Despite the low removal efficiencies reported by previous studies, electro-flotation still stands out among other microalgae removal methods for its economical and environmental benefits. To enhance removal efficiency, the important factors that limit the performance of this method must be investigated. In this study, the possible ways of increasing the removal efficiency of microalgae have been explored by investigating the effects of several important variables in electro-flotation. Eight parameters, namely flotation time, rising time, current density, pH, conductivity, electrode distance, temperature and initial concentration were evaluated using a one-parameter-at-a-time approach. Results revealed that the operational parameters that greatly affected the removal efficiency of microalgae were electro-flotation time, current density, pH, and initial concentration. The effect of conductivity, electrode distance, and temperature on removal efficiency were insignificant. However, they exhibited positive an indirect positive effect on power demand, which is nowadays considered an equally important aspect in the running of a feasible and economically efficient electro-flotation process.

• Korean Journal of Soil Science and Fertilizer
• /
• v.50 no.6
• /
• pp.684-696
• /
• 2017

An investigation of grain size, organic compounds and metal distribution in lakes from Geum river basin (Republic of Korea) was conducted in two years (2014 and 2015). The samples of sediment were collected from the 3 lakes (12 sites). The samples were analyzed the concentration of metals (Pb, Zn, Cu, Cr, Ni, As, Cd, Hg, Al, and Li) and general indices including grain size. Spearman correlation coefficients were determined using general indices and metal concentrations respectively. The organic qualities of sediments were improved in 2015 compared with 2014. The concentrations of metals were lower than Sediment Criteria of Lakes in Korea. The significant Spearman correlation coefficients were presented only sand-clay, clay-water content, COD-TOC, Cu-Ni, Cd-Li, Zn-Li, and Cr-Ni of general and metal parameters in 2014, 2015 and both of two years.

• Asian-Australasian Journal of Animal Sciences
• /
• v.20 no.2
• /
• pp.160-165
• /
• 2007

Dispersion parameters for the number of piglets born alive were estimated using a repeatability and random regression model. Six sow breeds/lines were included in the analysis: Swedish Landrace, Large White and both crossbred lines between them, German Landrace and their cross with Large White. Fixed part of the model included sow genotype, mating season as month-year interaction, parity and weaning to conception interval as class effects. The age at farrowing was modelled as a quadratic regression nested within parity. The previous lactation length was fitted as a linear regression. Random regressions for parity on Legendre polynomials were included for direct additive genetic, permanent environmental, and common litter environmental effects. Orthogonal Legendre polynomials from the linear to the cubic power were fitted. In the repeatability model estimate of heritability was 0.07, permanent environmental effect as ratio was 0.04, and common litter environmental effect as ratio was 0.01. Estimates of genetic parameters with the random regression model were generally higher than in the repeatability model, except for the common litter environmental effect. Estimates of heritability ranged from 0.06 to 0.10. Permanent environmental effect as a ratio increased along a trajectory from 0.03 to 0.11. Magnitudes of common litter effect were small (around 0.01). The eigenvalues of covariance functions showed that between 7 and 8 % of genetic variability was explained by individual genetic curves of sows. This proportion was mainly covered by linear and quadratic coefficients. Results suggest that the random regression model could be used for genetic analysis of litter size.

• Journal of Korean Society on Water Environment
• /
• v.36 no.5
• /
• pp.353-363
• /
• 2020

Hydrologic models can be classified into two types: those for understanding physical processes and those for predicting hydrologic quantities. This study deals with how to use the model to predict today's stream flow based on the system's knowledge of yesterday's state and the model parameters. In this regard, for the model to generate accurate predictions, the uncertainty of the parameters and appropriate estimates of the state variables are required. In this study, a relatively simple hydrologic partitioning model is proposed that can explicitly implement the hydrologic partitioning process, and the posterior distribution of the parameters of the proposed model is estimated using the Markov chain Monte Carlo approach. Further, the application method of the ensemble Kalman filter is proposed for updating the normalized soil moisture, which is the state variable of the model, by linking the information on the posterior distribution of the parameters and by assimilating the observed steam flow data. The stochastically and recursively estimated stream flows using the data assimilation technique revealed better representation of the observed data than the stream flows predicted using the deterministic model. Therefore, the ensemble Kalman filter in conjunction with the Markov chain Monte Carlo approach could be a reliable and effective method for forecasting daily stream flow, and it could also be a suitable method for routinely updating and monitoring the watershed-averaged soil moisture.

• Journal of Environmental Science International
• /
• v.14 no.2
• /
• pp.251-258
• /
• 2005

Statistical analysis between operating parameters and effluent quality on advanced wastewater treatment plant was performed. Through factor analysis four factors derived varimax rotation were selected each plant. Four components explained $80\%,\;82\%$ of the total variance of the process, respectively. The components on MLE plant were identified in the following order: 1) HRT increase and BOD load decrease by influent decrease, 2) Biomass, 3) SVI increase by internal return increase, 4) Microbial diversity by SRT increase. On $A_2O$ plant, we defined them as follows: factor 1, high MLSS by return rate increase, HRT increase by influent decrease; factor 2, biomass; factor 3, BOD of influent; factor 4 was relate to DO.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.25 no.8
• /
• pp.1046-1052
• /
• 2001

This study has been performed experimentally to measure the frost properties over a cold flat plate in order to obtain the correlations of the frost properties with various environmental parameters. Correlations of the frost surface temperature, thickness, density, and thermal conductivity are presented along with the experimental results as a function of environmental parameters, distance from the leading edge of test plate, and time. These correlations can be used to predict the frost properties with a maximum error of 8% in the following ranges : air temperature 15∼25$\^{C}$, relative humidity 60∼80%, air velocity 1∼3m/s and cooling plate temperature -15∼-25$\^{C}$.