• Journal of Wetlands Research
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• v.24 no.2
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• pp.83-92
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• 2022

The amount of the plastic waste has been increasing according to global demand for plastic. Microplastics are the most hazardous among all plastic pollutants due to their toxicity and unknown physicochemical properties. This study investigates the optimal methodology that can be applied to sewage samples for detecting microplastics before discussing reducing microplastics in MWTPs. In this study, the effect of different pretreatment methods while detecting microplastic analysis of MWTP influent samples was investigated; the samples were collected from the J sewage treatment plant. There are many pretreatment methods but two of them are widely used: Fenton digestion and hydrogen peroxide oxidation. Although there are many pretreatment methods that can be applied to investigate microplastics, the most widely used methods for sewage treatment plant samples are Fenton digestion and H₂O₂ oxidation. For each pretreatment method, there were factors that could cause an error in the measurement. To overcome this, in the case of the Fenton digestion pretreatment, it is recommended to proceed with the analysis by filtration instead of the density separation method. In the case of the H₂O₂ oxidation method, the process of washing with distilled water after the reaction is recommended. As a result of the analysis, the concentration of microplastics was measured to be 2.75ea/L for the sample using the H₂O₂ oxidation method and 3.2ea/L for the sample using the Fenton oxidation method, and most of them were present in the form of fibers. In addition, it is difficult to guarantee the reliability of measurement results from quantitative analysis performed via microscope with eyes. A calibration curve was created for prove the reliability. A total of three calibration curves were drawn, and as a result of analysis of the calibration curves, all R² values were more than 0.9. This ensures high reliability for quantitative analysis. The qualitative analysis could determine the series of microplastics flowing into the MWTP, but could not confirm the chemical composition of each microplastic. This study can be used to confirm the chemical composition of microplastics introduced into MWTP in the future research.

• Clean Technology
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• v.28 no.2
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• pp.131-137
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• 2022

The semiconductor process currently emits various by-products and unused gases. Emissions containing pollutants are generally classified into categories such as organic, acid, alkali, thermal, and cabinet exhaust. They are discharged after treatment in an atmospheric prevention facility suitable for each exhaust type. The main components of organic exhaust are volatile organic compounds (VOC), which is a generic term for oxygen-containing hydrocarbons, sulfur-containing hydrocarbons, and volatile hydrocarbons, while the main components of alkali exhaust include ammonia and tetramethylammonium hydroxide. The purpose of this study was to determine the combustion characteristics and analyze the NO_X reduction rate by maintaining a direct combustion and temperature to process organic and alkaline exhaust gases simultaneously. Acetone, isopropyl alcohol (IPA), and propylene glycol methyl ether acetate (PGMEA) were used as VOCs and ammonia was used as an alkali exhaust material. Independent and VOC-ammonia mixture combustion tests were conducted for each material. The combustion tests for the VOCs confirmed that complete combustion occurred at an equivalence ratio of 1.4. In the ammonia combustion test, the NO_X concentration decreased at a lower equivalence ratio. In the co-combustion of VOC and ammonia, NO was dominant in the NO_X emission while NO₂ was detected at approximately 10 ppm. Overall, the concentration of nitrogen oxide decreased due to the activation of the oxidation reaction as the reaction temperature increased. On the other hand, the concentration of carbon dioxide increased. Flameless combustion with an electric heat source achieved successful combustion of VOC and ammonia. This technology is expected to have advantages in cost and compactness compared to existing organic and alkaline treatment systems applied separately.

• Journal of Wetlands Research
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• v.25 no.2
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• pp.145-158
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• 2023

Constructed wetlands (CWs) are effective technologies for urban wastewater management, utilizing natural physico-chemical and biological processes to remove pollutants. This study employed a bibliometric analysis approach to investigate the progress and future research trends in the field of CWs. A comprehensive review of 100 most-recently published and open-access articles was performed to analyze the performance of CWs in treating wastewater. Spain, China, Italy, and the United States were among the most productive countries in terms of the number of published papers. The most frequently used keywords in publications include water quality (n=19), phytoremediation (n=13), stormwater (n=11), and phosphorus (n=11), suggesting that the efficiency of CWs in improving water quality and removal of nutrients were widely investigated. Among the different types of CWs reviewed, hybrid CWs exhibited the highest removal efficiencies for BOD (88.67%) and TSS (95.67%), whereas VSSF, and HSSF systems also showed high TSS removal efficiencies (83.25%, and 78.83% respectively). VSSF wetland displayed the highest COD removal efficiency (71.82%). Generally, physical processes (e.g., sedimentation, filtration, adsorption) and biological mechanisms (i.e., biodegradation) contributed to the high removal efficiency of TSS, BOD, and COD in CW systems. The hybrid CW system demonstrated highest TN removal efficiency (60.78%) by integrating multiple treatment processes, including aerobic and anaerobic conditions, various vegetation types, and different media configurations, which enhanced microbial activity and allowed for comprehensive nitrogen compound removal. The FWS system showed the highest TP removal efficiency (54.50%) due to combined process of settling sediment-bound phosphorus and plant uptake. Phragmites, Cyperus, Iris, and Typha were commonly used in CWs due to their superior phytoremediation capabilities. The study emphasized the potential of CWs as sustainable alternatives for wastewater management, particularly in urban areas.

• Journal of the Korea Organic Resources Recycling Association
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• v.31 no.1
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• pp.69-84
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• 2023

Despite the continuous installation and regular inspection of waste treatment facilities, complaints about excessive incineration and illegal dumping stench continue to occur at on-site treatment facilities. In addition, field surveys were conducted on the waste treatment facilities currently in operation (6 type) to understand the waste treatment process for each field, to grasp the main operating factors applied to the inspection. In addition, we calculated the material·energy balance for each main process and confirmed the proper operation of the waste disposal facility. As a result of the site survey, in the case of heat treatment facilities such as incineration, cement kilns, and incineration heat recovery facilities, the main factors are maintenance of the temperature of the incinerator required for incineration and treatment of the generated air pollutants, and in the case of landfill facilities Retaining wall stability, closed landfill leachate and emission control emerged as major factors. In the case of sterilization and crushing facilities, the most important factor is whether or not sterilization is possible (apobacterium inspection).In the case of food distribution waste treatment facilities, retention time and odor control during fermentation (digestion, decomposed) are major factors. Calculation results of material balance and energy resin for each waste treatment facility In the case of incineration facilities, it was confirmed that the amount of flooring materials generated is about 14 % and the amount of scattering materials is about 3 % of the amount of waste input, and that the facility is being operated properly. In addition, among foodwaste facilities, in the case of an anaerobic digestion facility, the amount of biogas generated relative to the amount of inflow is about 17 %, and the biogas conversion efficiency is about 81 %, in the case of composting facility, about 11 % composting of the inflow waste was produced, and it was comfirmend that all were properly operated. As a result, in order to improve the inspection method for waste treatment facilities, it is necessary not only to accumulate quantitative standards for detailed inspection methods, but also to collect operational data for one year at the time of regular inspections of each facility, Grasping the flow and judging whether or not the treatment facility is properly operated. It is then determined that the operation and management efficiency of the treatment facility will increase.

• Korean Journal of Environment and Ecology
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• v.36 no.6
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• pp.566-574
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• 2022

Heavy metals are one of the dangerous pollutants that threaten urban biodiversity due to their accumulation over a long period without being decomposed in vivo. Accordingly, there is a need for biological monitoring to compare accumulation concentrations in living organisms according to the degree of heavy metal exposure to evaluate heavy metal contamination in the air in urban areas. This study aims to examine the possibility of using nesting materials as heavy metal monitoring samples and determine the effects of heavy metals on Paridae. We installed 54 artificial nest boxes in the research areas that included campus green spaces (14), urban forests (11), and urban parks (29) on a university campus in Cheonan City, Chungcheongnam Province. The birds' use rate of artificial nest boxes was 11/14 (78.57%) in campus green spaces, 8/11 (72.72%) in urban forests, and 6/29 (20.68%) in urban parks. Moss materials were collected from collected nests, and the heavy metal accumulation characteristics of each type of urban green space and the effects of heavy metals on the success of fledging of Paridae were compared through heavy metal analysis. The analysis showed that the average concentrations of zinc and lead were 228.08±209.62 ㎍/dry g and 17.67 ± 6.72 ㎍/dry g, respectively. There was no significant difference in zinc concentration for each type of urban green space (Kruskal-Wallis test, p-value=0.28), but lead concentration showed a significant difference (Kruskal-Wallis test, p<0.05^*). Of the 21 Paridae, nests analyzed for heavy metals, fledging of birds was observed in 11 nests (52.38%). Fledging of birds observed in each urban green space type was 7 campus green spaces (77.78%), 6 in urban forests (85.71%), and 1 in urban park (20%), mainly in urban forests and green spaces on campus. Heavy metal concentrations were compared to check the effect of heavy metal accumulation on the successful fledging of Paridae, but there was no statistically significant difference (Zn: W=44, p-value=0.74, Pb: t=0.64676, df =7.2422, p-value=0.54). This study is a basic study using the nesting materials of Paridae as heavy metal monitoring samples, and it is determined that it can be used as basic data for non-invasive biological monitoring.

• Analytical Science and Technology
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• v.20 no.5
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• pp.383-392
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• 2007

The water soluble components were analyzed in the $PM_{2.5}$ fine particles collected at the 1100 site of Mt. Halla for the spring seasons between 1998 and 2004. The $PM_{2.5}$ mass concentrations were within $13.4{\pm}9.6{\sim}21.7{\pm}20.0{\mu}g/m^3$, and the concentrations of ionic components were in the order of nss-$SO{_4}^{2-}$ > $NH{_4}{^+}$ > $NO{_3}{^-}$ > $Ca^{2+}$ > $K^+$ > $Na^+$ > $Cl^-$ > $Mg^{2+}$, in which the concentration of nss-$SO{_4}^{2-}$($3.41{\pm}2.42{\mu}g/m^3$) was the highest. The concentrations of $NH{_4}{^+}$, $SO{_4}^{2-}$, and $NO{_3}{^-}$, the secondary pollutants, were respectively 0.60~1.50, 2.86~4.42, and $0.24{\sim}1.57{\mu}g/m^3$, which had occupied 88 % of the total ionic components, on the other hand, the concentrations of marine species were less than 5 %. The nss-$SO{_4}^{2-}$ showed the high correlation with $NH{_4}{^+}$, $K^+$, so that $NH{_4}{^+}$ and nss-$SO{_4}^{2-}$ might exist in the form of $(NH_4)_3H(SO_4)_2$ and $(NH_4)_2SO_4$ in fine particles. From the backward trajectory analysis, in case of high concentrations of $NH{_4}{^+}$ and nss-$SO{_4}^{2-}$ simultaneously, the air masses were originated and stagnated at the east region of China for a while, then moved into the atmosphere of Jeju. However, in case of $NO{_3}{^-}$ and nss-$Ca^{2+}$, the air masses originated at China and Siberia were moved into Jeju via the eastern China.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.

• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.12-23
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• 2023

The goal of international development projects is to assist sustainable development in recipient countries through foreign aid from donor countries. However, despite the need for both countries to negotiate and work together from the initial stages to maintain sustainability after the project, clear guidelines or standards have not been established. Additionally, despite the need for donor countries, which are relatively advanced, to understand the situation of recipient countries, many projects are donor-centric and fail to prioritize the value of sustainability. Therefore, this study extracted economic, social, and environmental risks that threaten sustainability through literature review and proposed a sustainability framework based on these criteria. To validate framework, actual international development cases conducted by advanced donor countries such as Australia, the United States, and Japan, in collaboration with South Korea, were analyzed by applying content analysis with the reports, which covers the overall contents from the planning stage to the operation stage. Analysis of sustainability perspectives focused on economy, society and the environment, advanced donor countries emphasized (1) the importance of pre-assessment, (2) the need for coordination with the local population and communities despite the existence of donor-specific values, and (3) addressing economic considerations such as pre-operational and maintenance costs, social communication with the local population, and environmental considerations starting from the initial stages of construction regarding the treatment of pollutants as values to be improved. Compared to other advanced donor countries, the Republic of Korea should also focus on consultation with local residents to achieve social integration, and improve sustainability by deployment the managers in local sites for better negotiation.The proposed framework in this study will serve as a tool to enhance communication among the countries and the locals, with the expectation of increasing project efficiency and sustainability.

• Journal of Marine Life Science
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• v.8 no.2
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• pp.104-114
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• 2023

As plastic usage increases globally, the amount of plastic waste entering the marine environment is steadily rising. Microplastics, in particular, can be ingested by marine organisms and accumulated in their digestive tracts, causing harmful effects on their growth and reproduction. Cytochrome P450 (CYP) enzymes are known to metabolize various environmental pollutants as detoxification enzymes, but their role in crustaceans is not well understood. In this study, sequences of nine CYP genes (CYP370A4, CYP370C5 from clan 2; CYP350A1, CYP350C5, CYP361A1 from clan 3; CYP4AN-like, CYP4AP2, CYP4AP3, CYP4C33-like1 from clan 4) were analyzed using conserved domains in the brackish water flea Diaphanosoma celebensis. Additionally, after exposure to three different sizes of polystyrene beads (0.05-, 0.5-, 6-㎛ PS beads; 0.1, 1, and 10 mg/L) for 48 hours, the expression of these nine CYP genes were investigated using real-time reverse transcription polymerase chain reaction (RT-PCR). The results showed that all CYP genes possessed conserved motifs, indicating that D. celebensis CYP has evolutionarily conserved functions. Among these CYP genes, the expression of CYP370C5, CYP360A1, and CYP4C122 showed a significant increase after exposure to 0.05-㎛ PS beads, suggesting their involvement in PS metabolism. This research will contribute to understanding the molecular mode of actions of microplastics on marine invertebrates.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.523-541
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• 2023

As accessibility to 3D printers increases, there is a growing frequency of exposure to chemicals associated with 3D printing. However, research on the toxicity and harmfulness of chemicals generated by 3D printing is insufficient, and the performance of toxicity prediction using in silico techniques is limited due to missing molecular structure data. In this study, quantitative structure-activity relationship (QSAR) model based on data-centric AI approach was developed to predict the toxicity of new 3D printing materials by imputing missing values in molecular descriptors. First, MissForest algorithm was utilized to impute missing values in molecular descriptors of hazardous 3D printing materials. Then, based on four different machine learning models (decision tree, random forest, XGBoost, SVM), a machine learning (ML)-based QSAR model was developed to predict the bioconcentration factor (Log BCF), octanol-air partition coefficient (Log Koa), and partition coefficient (Log P). Furthermore, the reliability of the data-centric QSAR model was validated through the Tree-SHAP (SHapley Additive exPlanations) method, which is one of explainable artificial intelligence (XAI) techniques. The proposed imputation method based on the MissForest enlarged approximately 2.5 times more molecular structure data compared to the existing data. Based on the imputed dataset of molecular descriptor, the developed data-centric QSAR model achieved approximately 73%, 76% and 92% of prediction performance for Log BCF, Log Koa, and Log P, respectively. Lastly, Tree-SHAP analysis demonstrated that the data-centric-based QSAR model achieved high prediction performance for toxicity information by identifying key molecular descriptors highly correlated with toxicity indices. Therefore, the proposed QSAR model based on the data-centric XAI approach can be extended to predict the toxicity of potential pollutants in emerging printing chemicals, chemical process, semiconductor or display process.