• Journal of Environmental Impact Assessment
• /
• v.28 no.2
• /
• pp.101-112
• /
• 2019

Over the last few years, air pollution ($PM_{10}$, $PM_{2.5}$) in the Seoul metropolitan area (SMA) has emerged as one of the most concerned and threatening environmental issues among the residents. It brings about various harmful effects on human health, as well as ecosystem and industrial activities. Governments and individuals pay various costs to mitigate the level of air pollutants. This study aims to empirically find the willingness to pays (WTP) among the parents from different socio-cultural groups - international and domestic groups to mitigate air pollution ($PM_{10}$, $PM_{2.5}$) in their residential area. Contingent Valuation Methods (CVM) is used with employing single-bounded dichotomous choice technique to elicit the respondent's WTP. Using tobit (censored regression) and probit models, the monthly mean WTP of the pooled sample for green electricity which contributes to improve air quality in the region was estimated as 3,993 KRW (3.58 USD). However, the mean WTP between the international group and domestic group through a sub-sample analysis shows broad distinction as 3,325KRW (2.98 USD) and 4,449 KRW (3.98 USD) respectively. This is because that socio-cultural characteristics of each group such as socio-economic status, personal experience, trust in institutions and worldview are differently associated with the WTP. Based on the results, the society needs to raise awareness of lay people to find a strong linkage between the current PM issue and green electricity. Also, it needs to improve trust in the government's pollution abatement policy to mobilize more assertive participation of the people from different socio-cultural background.

• ANNALS OF ANIMAL RESOURCE SCIENCES
• /
• v.29 no.4
• /
• pp.150-157
• /
• 2018

The Zygote arrest 1 (ZAR1) gene is known to affect early embryonic development in various vertebrates. In this study, we performed the association analysis to check whether there is any significant relationship between semen kinematic characteristics and the ZAR1 gene. To determine semen kinematic characteristics, we measured motility (MOT), straight-line velocity (VSL), curvilinear velocity (VCL), average path velocity (VAP), linearity (LIN), straightness (STR), amplitude of lateral head displacement (ALH), and beat cross frequency (BCF) of spermatozoa in boars. In order to detect single nucleotide polymorphisms (SNPs), we extracted genomic DNA from multiple Duroc boars, and then subsequently used them in sequencing reactions. As a result, three SNPs were detected in the intronic region of ZAR1 gene (g.2435T>C in intron 2, g.2605G>A and g.4633A>C in intron 3 ). SNPs g.2435T>C and g.2605G>A were significantly associated with MOT (p<0.01) and VSL (p<0.05), and g.4633A

• Journal of Food Hygiene and Safety
• /
• v.34 no.2
• /
• pp.140-147
• /
• 2019

An analytical method was developed for the determination of quinoxyfen in agricultural products using the QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) method by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The samples were extracted with 1% acetic acid in acetonitrile and water was removed by liquid-liquid partitioning with $MgSO_4$ (anhydrous magnesium sulfate) and sodium acetate. Dispersive solid-phase extraction (d-SPE) cleanup was carried out using $MgSO_4$, PSA (primary secondary amine), $C_{18}$ (octadecyl) and GCB (graphitized carbon black). The analytes were quantified and confirmed by using LC-MS/MS in positive mode with MRM (multiple reaction monitoring). The matrix-matched calibration curves were constructed using six levels ($0.001-0.25{\mu}g/mL$) and the coefficient of determination ($R^2$) was above 0.99. Recovery results at three concentrations (LOQ, 10 LOQ, and 50 LOQ, n=5) were in the range of 73.5-86.7% with RSDs (relative standard deviations) of less than 8.9%. For inter-laboratory validation, the average recovery was 77.2-95.4% and the CV (coefficient of variation) was below 14.5%. All results were consistent with the criteria ranges requested in the Codex guidelines (CAC/GL 40-1993, 2003) and Food Safety Evaluation Department guidelines (2016). The proposed analytical method was accurate, effective and sensitive for quinoxyfen determination in agricultural commodities. This study could be useful for the safe management of quinoxyfen residues in agricultural products.

• Journal of the Korea Organic Resources Recycling Association
• /
• v.30 no.4
• /
• pp.109-122
• /
• 2022

Currently, most of the pig manure generated from pig farms in Korea is in the form of a slurry with a moisture content of about 97%. Pig manure slurry is a mixture of pig manure and cleaning water in the pig house. In this study, changes in properties of pig manure liquid fertilizer according to whether air was supplied or not and with the passage of storage period were analyzed for 120 days. During the experimental period, the degree of maturity of the pig manure liquid fertilizer was higher in the experimental closed batch reactors supplied with air than in the same type reactors not supplied with air. As the liquid fertilizer storage period elapsed, there was a tendency that liquid fertilizer was converted to a state of complete maturity. In the batch reactor in which air was supplied, the moisture content of pig manure slurry, which had a moisture content of 97.90%, was reduced to 96.82% at the end of the experiment. On the other hand, the moisture content in the reactor without air was reduced to 97.33%. The pH of the liquid fertilizer, which was 8.82 at the start of the experiment, changed to 7.57 in the reactor with air supplied and 8.75 in the reactor without air at the completion of the experiment. The nitrogen content in the liquid fertilizer was 0.198 mg/L on average at the start of the experiment and it was lowered to 0.076 mg/L in the air supplied reactor at the end of the experiment. On the other hand, the nitrogen content of the liquid fertilizer was lowered to 0.121 mg/L in the reactor to which air was not supplied. The phosphoric acid (P₂O₅) concentration in the liquid decreased higher in the liquid fertilizer filled in the reactor without air than the liquid fertilizer filled in the reactor with air supplied as the storage period elapsed. Considering the experimental results, it is considered that the quality of pig manure liquid fertilizer is improved when air is supplied to pig manure slurry and the storage period of pig manure slurry is longer.

• Journal of Korea Water Resources Association
• /
• v.53 no.12
• /
• pp.1159-1172
• /
• 2020

This study applied deep convolution neural network based on U-Net and SegNet using long period weather radar data to very short-term rainfall prediction. And the results were compared and evaluated with the translation model. For training and validation of deep neural network, Mt. Gwanak and Mt. Gwangdeoksan radar data were collected from 2010 to 2016 and converted to a gray-scale image file in an HDF5 format with a 1km spatial resolution. The deep neural network model was trained to predict precipitation after 10 minutes by using the four consecutive radar image data, and the recursive method of repeating forecasts was applied to carry out lead time 60 minutes with the pretrained deep neural network model. To evaluate the performance of deep neural network prediction model, 24 rain cases in 2017 were forecast for rainfall up to 60 minutes in advance. As a result of evaluating the predicted performance by calculating the mean absolute error (MAE) and critical success index (CSI) at the threshold of 0.1, 1, and 5 mm/hr, the deep neural network model showed better performance in the case of rainfall threshold of 0.1, 1 mm/hr in terms of MAE, and showed better performance than the translation model for lead time 50 minutes in terms of CSI. In particular, although the deep neural network prediction model performed generally better than the translation model for weak rainfall of 5 mm/hr or less, the deep neural network prediction model had limitations in predicting distinct precipitation characteristics of high intensity as a result of the evaluation of threshold of 5 mm/hr. The longer lead time, the spatial smoothness increase with lead time thereby reducing the accuracy of rainfall prediction The translation model turned out to be superior in predicting the exceedance of higher intensity thresholds (> 5 mm/hr) because it preserves distinct precipitation characteristics, but the rainfall position tends to shift incorrectly. This study are expected to be helpful for the improvement of radar rainfall prediction model using deep neural networks in the future. In addition, the massive weather radar data established in this study will be provided through open repositories for future use in subsequent studies.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.12
• /
• pp.510-523
• /
• 2020

This study analyzed groundwater quality in hydroponic cultivation facilities. Through this study, the possibility of groundwater use was evaluated according to the quality of the groundwater for hydroponic cultivation facilities. Good groundwater quality, on average, is pH 6.61, EC 0.27 dS/m, NO3-N 7.64 mg/L, NH4+-N 0.80 mg/L, PO4-P 0.09 mg/L, K+ 6.26 mg/L, Ca2+ 18.57 mg/L, Mg2+ 4.38 mg/L, Na+ 20.85 mg/L, etc. All of these satisfy the water quality standard for raw water in nutrient cultivation. But in the case of farmers experiencing problems with groundwater quality, most of the items exceeded the water quality standard. As a result of the analysis, it was judged that purifying groundwater of unsuitable quality for crop cultivation, and using it as raw water, was effective in terms of water quality and soil purification. If an agricultural water purification system is constructed based on the results of this study, it is judged that the design will be easy because the items to be treated can be estimated. If a purification system is established, it can use groundwater directly in the facility and for horticulture. These study results will be available for use in sustainable agriculture and environments.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.49 no.4
• /
• pp.41-54
• /
• 2021

This study targets the urban park corresponding to the core areas (Hubs) of Green Infrastructure and estimates their value utilizing the Contingent Valuation Method (CVM) and determines the planning factors which affect them. The research aims to provide basic data for supporting the value improvement in the planning stage for urban parks representing green infrastructure. The primary purpose of this research is to derive variables that affect economic value and planning factors to improve the use-value of urban parks, one of the Hubs of the green infrastructure. In this study, Sejong Lake Park, located in Sejong City, is the target site. This study collected the responses of 105 people by conducting a survey on the intention to pay for the use-value and the planning factors that affect it, targeting visitors to Sejong Lake Park. The study conducts Contingent Valuation Method (CVM) on this survey responses. The results are as follows: first, as a result of analyzing the variables which affect willingness to pay for use-value, residence and age influence the willingness to pay significantly among socioeconomic characteristics. Next, the survey responses of Double-bounded dichotomous choices (DB-DC) CVM are converted into variables through statistic techniques. Furthermore, the variables are used for a Logit model to draw coefficients. The average willingness to pay per person for the use-value of Sejong Lake Park using the derived coefficients was approximately found to be 8,597 won. Therefore, as of 2019, Sejong Lake Park, with a total of 430,000 visitors, is estimated to have an annual economic value of 3.7 billion won. Third, the average Likert scale of the planning factor affecting the decision to pay for the economic value of Sejong Lake Park was the highest along the waterfront landscape, and the convenience facilities and waterfront landscape showed the highest willingness to pay, 10,000 won. In the range between 2,500 won and 5,000 won, the waterfront area ranks highest. Therefore, it can be said that visitors to Sejong Lake Park take account of the economic value of using the waterfront landscape the most. This study is meaningful as a thesis on use-value and the planning factors that affected value evaluation results of urban parks, and the analysis of the correlation between the planning factors of urban parks as hubs located in urban areas.

• Korean Journal of Environment and Ecology
• /
• v.36 no.3
• /
• pp.303-317
• /
• 2022

Climate change caused by increased greenhouse gas emissions can alter the natural ecosystem, including the pollination ecosystem and agricultural ecology, which are ecological interactions between potted insects and plants. Many studies have reported that populations of wild bees, including bees and wasps (BW), which are the key pollinators, have gradually declined due to climate change, leading to adverse impacts on overall biodiversity, ultimately with agribusinesses and the life cycle of flowering plants. Therefore, we could infer that the rising temperature in Korean Peninsula (South Korea) due to global warming has led to climate change and influenced the wild bee's ecosystem. In this study, we surveyed the distributional pattern of BW (Superfamily: Apoidea, Vespoidea, and Chrysidoidea) at 51 sites from 2017 (37 sites) to 2018 (14 sites) to examine the effects of climatic factors on the nationwide distribution of BW in South Korea. Previous literature has confirmed that their distribution according to forest climate zones is significantly correlated with mean and accumulative temperatures. Based on the result, we predicted the effects of future climate changes on the BW distribution that appeared throughout South Korea and the species that appeared in specific climate zones using Shared Socioeconomic Pathways (SSPs). The distributions of wild BW predicted by the SSP scenarios 2-4.5 and 5-8.5 according to the BIOMOD species distribution model revealed that common and endemic species will shift northward from the current habitat distribution by 2050 and 2100, respectively. Our study implies that climate change and its detrimental effect on the ecosystem is ongoing as the BW distribution in South Korea can change, causing the change in the ecosystem in the Korean Peninsula. Therefore, immediate efforts to mitigate greenhouse gas emissions are warranted. We hope the findings of this study can inspire further research on the effects of climate change on pollination services and serve as the reference for making agricultural policy and BW conservation strategy

• Economic and Environmental Geology
• /
• v.55 no.5
• /
• pp.551-561
• /
• 2022

Geophysical exploration methods are very useful for generating high-resolution images of underground structures, and such methods can be applied to investigation of buried cultural properties and for determining their exact locations. In this study, image feature extraction and image segmentation methods were applied to automatically distinguish the structures of buried relics from the high-resolution ground-penetrating radar (GPR) images obtained at the center of Silla Kingdom, Gyeongju, South Korea. The major purpose for image feature extraction analyses is identifying the circular features from building remains and the linear features from ancient roads and fences. Feature extraction is implemented by applying the Canny edge detection and Hough transform algorithms. We applied the Hough transforms to the edge image resulted from the Canny algorithm in order to determine the locations the target features. However, the Hough transform requires different parameter settings for each survey sector. As for image segmentation, we applied the connected element labeling algorithm and object-based image analysis using Orfeo Toolbox (OTB) in QGIS. The connected components labeled image shows the signals associated with the target buried relics are effectively connected and labeled. However, we often find multiple labels are assigned to a single structure on the given GPR data. Object-based image analysis was conducted by using a Large-Scale Mean-Shift (LSMS) image segmentation. In this analysis, a vector layer containing pixel values for each segmented polygon was estimated first and then used to build a train-validation dataset by assigning the polygons to one class associated with the buried relics and another class for the background field. With the Random Forest Classifier, we find that the polygons on the LSMS image segmentation layer can be successfully classified into the polygons of the buried relics and those of the background. Thus, we propose that these automatic classification methods applied to the GPR images of buried cultural heritage in this study can be useful to obtain consistent analyses results for planning excavation processes.

• Journal of the Korean Geotechnical Society
• /
• v.38 no.7
• /
• pp.5-24
• /
• 2022

The current performance evaluation of slope anchors qualitatively determines the physical bonding between the anchor head and ground as well as cracks or breakage of the anchor head. However, such performance evaluation does not measure these primary factors quantitatively. Therefore, the time-dependent management of the anchors is almost impossible. This study is an evaluation of the 3D numerical model by SfM which combines UAS images with terrestrial LiDAR to collect numerical data on the damage factors. It also utilizes the data for the quantitative maintenance of the anchor system once it is installed on slopes. The UAS 3D model, which often shows relatively low precision in the z-coordinate for vertical objects such as slopes, is combined with terrestrial LiDAR scan data to improve the accuracy of the z-coordinate measurement. After validating the system, a field test is conducted with ten anchors installed on a slope with arbitrarily damaged heads. The damages (such as cracks, breakages, and rotational displacements) are detected and numerically evaluated through the orthogonal projection of the measurement system. The results show that the introduced system at the resolution of 8K can detect cracks less than 0.3 mm in any aperture with an error range of 0.05 mm. Also, the system can successfully detect the volume of the damaged part, showing that the maximum damage area of the anchor head was within 3% of the original design guideline. Originally, the ground adhesion to the anchor head, where the z-coordinate is highly relevant, was almost impossible to measure with the UAS 3D numerical model alone because of its blind spots. However, by applying the combined system, elevation differences between the anchor bottom and the irregular ground surface was identified so that the average value at 20 various locations was calculated for the ground adhesion. Additionally, rotation angle and displacement of the anchor head less than 1" were detected. From the observations, the validity of the 3D numerical model can obtain quantitative data on anchor damage. Such data collection can potentially create a database that could be used as a fundamental resource for quantitative anchor damage evaluation in the future.