• Journal of Korean Society of Water and Wastewater
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• v.26 no.5
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• pp.649-658
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• 2012

In this study, the influencing factors for efficient anaerobic digestion of high strength ammonia-nitrogen wastewater removal were investigated by testing biochemical methane potential test. In the influencing factors, the trace metals which could increase activity of anaerobic microorganisms, microbial concentration and types were evaluated. In the results, trace metals supplementation showed gas production amount higher than those without addition of trace metals. Among the tested trace metals, B, Ni, and Se were preferable to gas production. In the result of gas production according to the microbial concentration, the amount of gas production was proportional to the microbial concentration. In addition, the shortest lag time and the fastest gas production rate were achieved when the highest microbial concentration was tested. granule-type microorganism produced more gas than suspended-type microorganism. In conclusion, the efficient anaerobic digestion for high strength ammonia-nitrogen wastewater removal could be achieved by applying necessary trace metals injection and high concentration granule type microorganism.

• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.503-516
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• 2019

We have estimated the vertical column density (VCD) of formaldehyde (HCHO) on a global scale using a multiple linear regression method (MRM) with Ozone Monitoring Instrument (OMI) and Moderate-Resolution Imaging Spectroradiometer (MODIS) data. HCHO VCDs were estimated in regions of biogenic, pyrogenic, and anthropogenic emissions using independent variables, including $NO_2$ VCD, land surface temperature (LST), an enhanced vegetation index (EVI), and the mean fire radiative power (MFRP), which are strongly correlated with HCHO. To evaluate the HCHO estimates obtained using the MRM, we compared estimates of HCHO VCD data measured by OMI ($HCHO_{OMI}$) with those estimated by multiple linear regression equations (MRE) ($HCHO_{MRE}$). Good MRM performances were found, having the average statistical values (R = 0.91, slope = 1.03, mean bias = $-0.12{\times}10^{15}molecules\;cm^{-2}$, percent difference = 11.27%) between $HCHO_{MRE}$ and $HCHO_{OMI}$ in our study regions where high HCHO levels are present. Our results demonstrate that the MRM can be a useful tool for estimating atmospheric HCHO levels.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2461-2476
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• 2013

To assess environmental contamination with carcinogens, carbonaceous compounds, water-soluble ionic species and trace gaseous species were identified and quantified every three hours for three days st three different atmospheric layer at the heart of chiang-Mai, bangkok and hat-Yai from December 2006 to February 2007. A DRI model 2001 Themal/Optical Carbon Analyzer with the IMPROVE thermal/optical reflectance (TOR) protocol was used to quantify the organic carbon(OC) and elemental carbon content in $PM_{10}$. Diurnal and vertical variability was also carefully investigated. In general, OC and EC contenttration shoeed the highest values at the monitoring period o 21.00-00.00 as consequences of human activities at night bazaar coupled with reduction of mixing layer, decreased wind speed and termination of photolysis nighttime. Morning peaks of carboaceous compounds were observed during the sampling period of 06:00 -09:00, emphasizing the main contribution of traffic emission in the three cities. The estimation of incremental lifetime partculate matter exposure (ILPE) raises concern of high risk of carbonaceous accumulation over workers and residents living close to the observatory sites. The average values of incremental lifrtime particulate matter exposure (ILPE) of total carbon at Baiyoke Suit Hotel and Baiyoke Sky Hotel are approsimately ten time shigher then those air sample collected at prince of songkla University Hat-Yai campus corpse incinerator and fish-can maufacturing factory but only slightly higher than those of rice straw burnig in Songkla province. This indicates a high risk of developing lung cancer and other respiratory diseases across workers and residents living in high buildings located in Pratunam area. Using knowledge of carbonaceous fractions in $PM_{10}$, one can estimate the gas-particle partitioning of polycyclic aromatic hydrocarbons (PAHs). Dachs-Eisenreich model highlights the crucial role of adsorption in gas-particle partitioning of low molecular weight PAHs, whereas both absorption and adsorption tend to account for gas-particle partitioning of high molecular weight PAHs in urban residential zones of Thailand. Interestingly, the absorption mode alone plays a minor role in gas-partcle partitiining of PAHs in Chiang-Mai, Bangkok and hat-Yai.

• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1465-1474
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• 2013

In this paper, air pollutant tracing models using perceptron neural network(PNN) and non-negative least square(NNLS) are proposed. When the measured values of the air pollution and the contribution concentration of each source by chemical transport modeling are given, they estimate and trace the amount of the air pollutants emission from each source. Two kinds of emissions data are used in the experiments : CH4 and N2O of Geumgo-dong landfill greenhouse gas, and PM10 of 17 areas in Northeast Asia and eight regions of the Korean Peninsula. Emission values were calculated using pseudo inverse method, PNN and NNLS. Pseudo inverse method could be used for the model, but it may have negative emission values. In order to deal with the problem, we used the PNN and NNLS methods. As a result, the estimation using the NNLS is closer to the measured values than that using PNN. The proposed tracing models have better utilization and generalization than those of conventional pseudo inverse model. It could be used more efficiently for air quality management and air pollution reduction.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.148-153
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• 2009

This paper considers the age of air in a ventilated space with multiple supply inlets. The local mean age of air at a point from one supply inlet is different from those from the other supply inlets. It is the purpose of the present paper to investigate theoretically the relations between the LMA's from each supply and overall combined LMA whether or not to trace the origins of supply air. Transient concentration distributions are calculated with a step-up injection of tracer gas at each supply inlet, and at both inlets simultaneously. The steady state concentration with a continuous tracer injection at a supply inlet works as a weighting factor for the corresponding LMA in calculating the average overall LMA from multiple inlets.

• Journal of Korean Society of Transportation
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• v.31 no.6
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• pp.90-105
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• 2013

There are lots of variations on speed, acceleration and engine power during vehicle driving. It is well known that Green House Gas emissions by these dynamic driving properties are not precisely estimated by the average speed based emission estimation model which has been currently used in Korea. MOVES are selected as an appropriate transferable model among Micro-level emission estimation models. Based on MOVES, a novel emission estimation model can be used in Korea is developed. In this model, MOVES concept of emission estimation method and the MOVES method of estimating the Micro-level emission rate map is adopted. The results from the proposed model were compared with those from the average speed based emission model. The comparison results show the estimated base emission maps are good to be applied in Korea, but needed to be adjusted to consider the vehicle size differences between the two countries. Therefore, the factors for calibrating vehicle size difference were calculated and applied to acquired the micro-level emission maps for the Korean standard vehicle types.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.523-530
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• 2015

A Multiple Regression Method (MRM) is used for the first time with Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) data to estimate formaldehyde (HCHO) Vertical Column Density (VCD). For a 3.5-year period from January 2005 through July 2008, HCHO VCD estimation is investigated in cities over Asia in two categorized areas: (1) Major cities in Northeast Asia (Beijing, Seoul, and Tokyo), (2) Major cities in Southeast Asia (New Delhi, Dhaka, and Bangkok). In the Major cities in Northeast Asia, there are good agreements between HCHO estimated by the multiple linear regression method ($HCHO_{MRM}$) and HCHO measured by OMI ($HCHO_{OMI}$) (0.78 < $R^2$ < 0.82). However, in Major cities in Southeast Asia, there were poor agreements between $HCHO_{OMI}$ and $HCHO_{MRM}$ (0.24 < $R^2$ < 0.39). In addition, an unbiased assessment of the MRM performance using modeling and validation groups shows that the performance of the MRM based on separate modeling and validation groups is comparable to that using all the data for deriving Multiple Regression Equations (MREs). This study demonstrates that MRM can be an alternative tool for HCHO estimation in certain areas over Asia.

• Earthquakes and Structures
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• v.12 no.3
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• pp.321-332
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• 2017

The reverse fault is a dangerous geological hazard faced by buried steel pipelines. Permanent ground deformation along the fault trace will induce large compressive strain leading to buckling failure of the pipe. A hybrid pipe-shell element based numerical model programed by INP code supported by ABAQUS solver was proposed in this study to explore the strain performance of buried X80 steel pipeline under reverse fault displacement. Accuracy of the numerical model was validated by previous full scale experimental results. Based on this model, parametric analysis was conducted to study the effects of four main kinds of parameters, e.g., pipe parameters, fault parameters, load parameter and soil property parameters, on the strain demand. Based on 2340 peak strain results of various combinations of design parameters, a semi-empirical model for strain demand prediction of X80 pipeline at reverse fault crossings was proposed. In general, reverse faults encountered by pipelines are involved in 3D oblique reverse faults, which can be considered as a combination of reverse fault and strike-slip fault. So a compressive strain demand estimation procedure for X80 pipeline crossing oblique-reverse faults was proposed by combining the presented semi-empirical model and the previous one for compression strike-slip fault (Liu 2016). Accuracy and efficiency of this proposed method was validated by fifteen design cases faced by the Second West to East Gas pipeline. The proposed method can be directly applied to the strain based design of X80 steel pipeline crossing oblique-reverse faults, with much higher efficiency than common numerical models.

• Geophysics and Geophysical Exploration
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• v.21 no.1
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• pp.54-60
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• 2018

The data acquired from seismic exploration can be used to detect the existence of oil and gas resources through appropriate processing and interpretation. The seismic attributes indicating the existence of resources are extracted from amplitude information, where the Q-factor representing intrinsic attenuation plays an useful role of hydrocarbon indicator. So, the accuracy of Q-factor estimation is very important to investigate the existence of resources. In this study, we calculated the Q-factor and analyzed the error rate through a numerical example. To mimic real data, random noise was added to the synthetic data. With the noise-added data, the Q-factor was estimated and the error rate was analyzed by using the spectral ratio method (SRM) and peak frequency shift method (PFSM). Both methods provided a relatively accurate Q-factor when the signal-to-noise ratio was 90 dB. However, the peak frequency shift method (PFSM) produced better results than the spectral ratio method (SRM) as the level of random noise increased.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.135-147
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• 2017

We, for the first time, estimated daily and monthly surface nitrogen dioxide ($NO_2$) volume mixing ratio (VMR) using three regression models with $NO_2$ tropospheric vertical column density (OMIT-rop $NO_2$ VCD) data obtained from Ozone Monitoring Instrument (OMI) in Seoul in South Korea at OMI overpass time (13:45 local time). First linear regression model (M1) is a linear regression equation between OMI-Trop $NO_2$ VCD and in situ $NO_2$ VMR, whereas second linear regression model (M2) incorporates boundary layer height (BLH), temperature, and pressure obtained from Atmospheric Infrared Sounder (AIRS) and OMI-Trop $NO_2$ VCD. Last models (M3M & M3D) are a multiple linear regression equations which include OMI-Trop $NO_2$ VCD, BLH and various meteorological data. In this study, we determined three types of regression models for the training period between 2009 and 2011, and the performance of those regression models was evaluated via comparison with the surface $NO_2$ VMR data obtained from in situ measurements (in situ $NO_2$ VMR) in 2012. The monthly mean surface $NO_2$ VMRs estimated by M3M showed good agreements with those of in situ measurements(avg. R = 0.77). In terms of the daily (13:45LT) $NO_2$ estimation, the highest correlations were found between the daily surface $NO_2$ VMRs estimated by M3D and in-situ $NO_2$ VMRs (avg. R = 0.55). The estimated surface $NO_2$ VMRs by three modelstend to be underestimated. We also discussed the performance of these empirical modelsfor surface $NO_2$ VMR estimation with respect to otherstatistical data such asroot mean square error (RMSE), mean bias, mean absolute error (MAE), and percent difference. This present study shows a possibility of estimating surface $NO_2$ VMR using the satellite measurement.