• Journal of Wetlands Research
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• v.25 no.4
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• pp.353-365
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• 2023

The effects of climate change on green infrastructure and environmental media remain uncertain and context-specific despite numerous climate projections globally. In this study, the extreme weather conditions in seven major cities in South Korea were characterized through statistical analysis of 20-year daily meteorological data extracted fro m the Korea Meteorological Administration (KMA). Additionally, the impacts of extreme weather on Nature-based Solutions (NbS) were determined through a comprehensive review. The results of the statistical analysis and comprehensive review revealed the studied cities are potentially vulnerable to varying extreme weather conditions, depending on geographic location, surface imperviousness, and local weather patterns. Temperature extremes were seen as potential threats to the resilience of NbS in Seoul, as both the highest maximum and lowest minimum temperatures were observed in the mentioned city. Moreover, extreme values for precipitation and maximum wind speed were observed in cities from the southern part of South Korea, particularly Busan, Ulsan, and Jeju. It was also found that extremely low temperatures induce the most impact on the resilience of NbS and environmental media. Extremely cold conditions were identified to reduce the pollutant removal efficiency of biochar, sand, gravel, and woodchip, as well as the nutrient uptake capabilities of constructed wetlands (CWs). In response to the negative impacts of extreme weather on the effectiveness of NbS, several adaptation strategies, such as the addition of shading and insulation systems, were also identified in this study. The results of this study are seen as beneficial to improving the resilience of NbS in South Korea and other locations with similar climate characteristics.

• 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.

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.4
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• pp.216-224
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• 2023

Since maize (Zea mays L.) originated in central and south America, it requires warm climate conditions throughout its growing season. Growth halts when night-time temperatures drop below 10℃, and the plant may die if temperature reach -1.7℃. Thus, temperature should be maintained between 10 and 30℃ from seeding to maturity. The germination temperature for maize should be at least 8-11℃, whit an optimal range 32-34℃. Since temperature significantly affects the germination rate and period, it plays a crucial role in maize growth. In this study, we evaluated the quantity and feed value of 11 major varieties to determine those best suited for maize cultivation as feed in higher latitude, specifically in Democratic People's of Republic of Korea, below 38 degrees north. A cultivation test was also conducted in Suwon in Republic of Korea, to assess adaptability in areas south of Mt. Suyang. Among the varieties tested, Shinhwangok2 reached silking the fastest, in 65 days, while Gwangpyeongok took the longest at 75 days. The stem length of all varieties exceeded 230 cm. Gwangpyeongok had the tallest stems, while Daanok and Shinhwangok2ho displayed the highest ear ratios. Dacheongok presented the highest values in both dry matter and TDN quantity, with 31,420 kg/ha and 21,66 kg/ha respectively. Pyeonggangok had the highest crude protein content at 8.0%. TDN (%) ranged from 57-68%, with Hwangdaok reaching up to 68%. Based on these findings, Dacheongok and Pyeonggangok appear to be the most suitable varieties for cultivation in terms of both quantity and feed value.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.427-435
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• 2023

Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R². The models with applied correction coefficients achieve R² values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.779-793
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• 2023

Intensive and long-term aquaculture activities in Korea have generated considerable amounts of organic matter, deteriorating the sedimentary environment and ecosystem. The Korean government enacted the Fishery Management Act to preserve and manage the environment of fish farms. Based on this, a fisheries environment assessment has been conducted on fish cage farms since 2014, necessitating the development of a scientific and objective evaluation method suitable for the domestic environment. Therefore, a benthic health index (BHI) was developed using the relationship between benthic polychaete communities and organic matter, a major source of pollution in fish farms. In this study, the development process and calculation method of the BHI have been introduced. The BHI was calculated by classifying 225 species of polychaetes appearing in domestic coastal and aquaculture areas into four groups by linking the concentration gradient of the total organic carbon in the sediment and the distributional characteristics of each species and assigning differential weights to each group. Using BHI, the benthic fauna communities were assigned to one of the four ecological classes (Grade 1: Normal, Grade 2: Slightly polluted, Grade 3: Moderately polluted, and Grade 4: Heavily polluted). The application of the developed index in the field enabled effective evaluation of the Korean environment, being relatively more accurate and less affected by the season compared with the existing evaluation methods like the diversity index or AZTI's Marine Biotic Index developed overseas. In addition, using BHI will be useful in the environmental management of fish farms, as the environment can be graded in quantified figures.

• Journal of Food Hygiene and Safety
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• v.38 no.6
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• pp.517-527
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• 2023

This study aimed to examine the possibility of upcycling extracts of Angelica keiskei and Oenanthe javanica juice by-products through comparing enzyme extraction (EE) and complex extraction (CE) methods to increase the extraction yield and flavor of materials. A higher extraction yield was obtained for free amino acid content with EE and CE for A. keiskei and O. javanica juice by-products, respectively, and a higher extraction efficiency was achieved with juice by-products than with extracts prepared from raw materials before juice production. The content of major amino acids varied depending on the extraction method used. When used according to the characteristics of the extract, their use as a functional material was confirmed along with improvement in the flavor of the food. Consistently high extraction yields for organic acid and sugar levels were obtained with CE in A. keiskei and O. javanica juice by-products. The DPPH radical scavenging ability and TPC were consistently high with CE in A. keiskei and O. javanica juice by-products; the increase in extracted content was likely because of the reaction between the ethanol used for CE and the phenolic compounds. However, because the antioxidant capacity of the juice by-product extracts was somewhat lower than that of the extracts from raw materials before juice production, the amount used should be reviewed. The TFC was found to be higher in extracts obtained with EE than with CE for A. keiskei juice by-products; however, no significant difference was observed between EE and CE in the O. javanica juice by-products. Through this study, the taste compounds and antioxidant properties of extracts obtained from juice by-products produced after the production of A. keiskei and O. javanica green juice were analyzed, and the availability of high value-added materials was confirmed. Based on these research results, expanding specific R&D for practical use should be explored.

• Economic and Environmental Geology
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• v.56 no.6
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• pp.729-744
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• 2023

The value of lithium has significantly increased due to the rising demand for electric cars and batteries. Lithium is primarily found in pegmatites, hydrothermally altered tuffaceous clays, and continental brines. Globally, groundwater-fed salt lakes and oil field brines are attracting attention as major sources of lithium in continental brines, accounting for about 70% of global lithium production. Recently, deep groundwater, especially geothermal water, is also studied for a potential source of lithium. Lithium concentrations in deep groundwater can increase through substantial water-rock reaction and mixing with brines. For the exploration of lithim in deep groundwater, it is important to understand its origin and behavior. Therefore, based on a nationwide preliminary study on the hydrogeochemical characteristics and evolution of thermal groundwater in South Korea, this study aims to investigate the distribution of lithium in the deep groundwater environment and understand the geochemical factors that affect its concentration. A total of 555 thermal groundwater samples were classified into five hydrochemical types showing distinct hydrogeochemical evolution. To investigate the enrichment mechanism, samples (n = 56) with lithium concentrations exceeding the 90th percentile (0.94 mg/L) were studied in detail. Lithium concentrations varied depending upon the type, with Na(Ca)-Cl type being the highest, followed by Ca(Na)-SO₄ type and low-pH Ca(Na)-HCO₃ type. In the Ca(Na)-Cl type, lithium enrichment is due to reverse cation exchange due to seawater intrusion. The enrichment of dissolved lithium in the Ca(Na)-SO₄ type groundwater occurring in Cretaceous volcanic sedimentary basins is related to the occurrence of hydrothermally altered clay minerals and volcanic activities, while enriched lithium in the low-pH Ca(Na)-HCO₃ type groundwater is due to enhanced weathering of basement rocks by ascending deep CO₂. This reconnaissance geochemical study provides valuable insights into hydrogeochemical evolution and economic lithium exploration in deep geologic environments.

• Environmental and Resource Economics Review
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• v.32 no.4
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• pp.217-238
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• 2023

Currently, automobile tax in Korea is imposed by multiplying the vehicle's engine displacement by a certain tax rate. However, the need for revision is being raised as it is pointed out that the current system does not reflect the immediate task of reducing greenhouse gas emissions. Accordingly, this study focuses on the positive relationship between engine displacement and CO₂ emissions, and seeks to calculate an appropriate automobile tax rate considering average CO₂ emissions. To this end, first, we estimated the average annual CO₂ emissions (kg/vehicle) for each engine displacement using the average CO₂ emissions for each vehicle displacement as of 2020. Next, multiple scenarios were analyzed considering the standard tax rate at $75 per ton of CO₂ emissions proposed by the IMF (2019). In particular, we compared the case of imposing a uniform carbon tax of $75 and the case of imposing a progressive tax based on CO₂ emissions by displacement. According to the results, it was confirmed that the uniform tax rate proposed by the IMF is difficult to apply to Korea as it is due to the impact of a decrease in tax revenue, and a tax scheme needs to be designed appropriately considering maintenance of tax revenue according to the current automobile tax, greenhouse gas reduction effect, and automobile tax reform trends in developed countries. For example, in the case of the K3 (1,598cc) of Kia Motors, a representative compact car sold in Korea, if we compare the tax burdens for each tax scenario, the tax burden will be about 220,000 KRW under the current system, about 79,000 KRW under the uniform tax rate, about 83,000 KRW under the progressive tax rate, and about 240,000 KRW under the progressive tax rate similar to the UK tax system, respectively. In this way, this study identified the current statuses of automobile registration and tax in Korea, and automobile tax reform trends in major developed countries, and analyzed the impact of automobile tax reform considering engine displacement and CO₂ emissions, focusing on the tax burden of the people.

• Journal of Nutrition and Health
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• v.56 no.6
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• pp.667-682
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• 2023

Purpose: This study aimed to investigate the changes in health behavior, mental health, and nutritional status of Korean adolescents before and after the coronavirus disease 2019 (COVID-19) pandemic outbreak. Methods: A total of 800 adolescents (12~18 years old) who participated in the 2019-2020 Korea National Health and Nutrition Examination Survey (KNHANES) were included as study subjects and divided into four groups (204 middle school boys, 172 middle school girls, 219 high school boys, and 205 high school girls). The 2019 and 2020 KNHANES data were classified into data collected before and after the COVID-19 outbreak, respectively. Results: After the COVID-19 pandemic outbreak, middle school boys showed an increased tendency toward becoming overweight and obese, with significantly increased levels of diastolic blood pressure and insulin. While there was no major change in the subjective health status among adolescents, the high school boys showed a significantly decreased physical activity after COVID-19 outbreak. Moreover, the proportion of middle school students feeling a little stressed significantly increased after the COVID-19 outbreak. The rate of skipping breakfast significantly increased in middle school girls, but the rate of having lunch with companions significantly increased among all adolescents after the COVID-19 outbreak. However, the intake of milk, vegetables, fruits, seaweeds, and pulses significantly decreased, although the intake of sugars, beverages, and seasonings significantly decreased as well, during this period. These changes may lead to an increased proportion of adolescents with insufficient intake of nutrients, including potassium, vitamin C, and riboflavin. Conclusion: These results highlight the impact of COVID-19 on comprehensive changes in physical and mental health status, lifestyle behavior, and nutritional status in adolescents, suggesting the need for targeted prevention and intervention for physical and mental well-being during the pandemic.

• Journal of Nutrition and Health
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• v.56 no.6
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• pp.683-701
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• 2023

Purpose: The purpose of the study was to analyze the status of dietary behavior and nutrition intakes according to the gender and the level of physical activity of adolescents. Methods: Data from 659 adolescents aged 13 to 18 years who participated in the Korea National Health and Nutrition Examination Survey (2017-2018) were analyzed. Collected data were analyzed using complex sampling data analysis with SPSS v. 27.0. Results: The adolescents were categorized into three groups based on their physical activity as follows: The first group with high physical activity (8.9%), a second group with normal physical activity (29.7%), and a third group without physical activity (61.4%). Boys showed significantly higher physical activity than the girls. Adolescents with high physical activity had a significantly lower body mass index than adolescents without physical activity, but their meal regularity, subjective health status, and recognition of body image were significantly higher. In terms of biochemical factors, adolescents with high physical activity had lower triglycerides and cholesterol than adolescents without physical activity, while hemoglobin and hematocrit were significantly higher. In addition, the intakes of energy, carbohydrates, proteins, fat, vitamin B₁, niacin, calcium, phosphorus, sodium, potassium, iron increased significantly as adolescents' physical activity increased. Conclusion: The physical activity of adolescents had a positive effect on dietary behavior, lifestyle, and nutritional factors. Therefore, it is necessary to increase participation in physical classes in schools and develop various programs considering the level of physical activity among adolescents.