• Journal of Korea Water Resources Association
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• v.53 no.10
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• pp.845-859
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• 2020

Climate change and recent heat waves have drawn public attention toward other environmental issues, such as water pollution in the form of algal blooms, chemical leaks, and oil spills. Water pollution by the leakage of chemicals may severely affect human health as well as contaminate the air, water, and soil and cause discoloration or death of crops that come in contact with these chemicals. Chemicals that may spill into water streams are often colorless and water-soluble, which makes it difficult to determine whether the water is polluted using the naked eye. When a chemical spill occurs, it is usually detected through a simple contact detection device by installing sensors at locations where leakage is likely to occur. The drawback with the approach using contact detection sensors is that it relies heavily on the skill of field workers. Moreover, these sensors are installed at a limited number of locations, so spill detection is not possible in areas where they are not installed. Recently hyperspectral images have been used to identify land cover and vegetation and to determine water quality by analyzing the inherent spectral characteristics of these materials. While hyperspectral sensors can potentially be used to detect chemical substances, there is currently a lack of research on the detection of chemicals in water streams using hyperspectral sensors. Therefore, this study utilized remote sensing techniques and the latest sensor technology to overcome the limitations of contact detection technology in detecting the leakage of hazardous chemical into aquatic systems. In this study, we aimed to determine whether 18 types of hazardous chemicals could be individually classified using hyperspectral image. To this end, we obtained hyperspectral images of each chemical to establish a spectral library. We expect that future studies will expand the spectral library database for hazardous chemicals and that verification of its application in water streams will be conducted so that it can be applied to real-time monitoring to facilitate rapid detection and response when a chemical spill has occurred.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.12
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• pp.1287-1293
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• 2008

In this study, a blend of 2-amino-2-methyl-1-propanol (AMP) and ammonia (NH$_3$) was used to achieve high absorption rates for carbon dioxide (CO$_2$) as suggested at several literatures. The absorption rates of aqueous AMP and blended AMP+NH$_3$ solutions with CO$_2$ and nitrogen dioxide (NO$_2$) were measured using a stirred-cell reactor at 303 K. The effect of the added NH$_3$ to enhance absorption characteristics of AMP was studied. The performances were evaluated under various operating conditions. The absorption rates increased following the increase of the concentration of NH$_3$. The absorption rate of NH$_3$ blended into 30 wt.% AMP solution with NO$_2$ at 303 K was 12.6$\sim$32.6% higher than that of aqueous AMP solution without NH3. Also, the addition of 3 wt.% NH$_3$ to 30 wt.% AMP increased 48.2$\sim$41.6% values for the reactions with CO$_2$ and NO$_2$ at 303 K. Therefore, it clearly shows that the reaction rate of AMP with CO$_2$ and NO$_2$ can be increased by the addition of NH$_3$.

• Journal of Korean Society of Disaster and Security
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• v.13 no.1
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• pp.59-75
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• 2020

This study is a case study that applied 'UNDRR's Urban Disaster Resilience Scorecard', an evaluation tool necessary for Incheon Metropolitan City to be certified as an international safe city. I would like to present an example that the results derived from this scorecard contributed to the Incheon Metropolitan City Disaster Reduction Plan. Of course, the Disaster Resilience Scorecard can't provide a way to improve the resilience of every disaster facing the city. However, it is to find the weakness of the resilience that the city faces, and to propose a solution to reduce the city's disaster risk. This is to help practitioners to recognize the disaster risks that Incheon Metropolitan City faces. In addition, the solution recommended by UNDRR was suggested to provide resilience in areas vulnerable to disasters. It was confirmed that this process can contribute to improving the disaster resilience of Incheon Metropolitan City. UNDRR has been spreading 'Climate Change, Disaster-resistant City Creation Campaign', aka MCR (Making Cities Resilient) Campaign, to cities all over the world since 2010 to reduce global cities' disasters. By applying the disaster relief guidelines adopted by UNDRR, governments, local governments, and neighboring cities are encouraged to collaborate. As a result of this study, Incheon Metropolitan city's UN Urban Resilience Scorecard was evaluated as a strong resilience field by obtaining scores of 4 or more (4.3~5.0) in 5 of 10 essentials; 1. Prepare organization for disaster resilience and prepare for implementation, 4. Strong resilience Urban development and design pursuit, 5. Preservation of natural cushions to enhance the protection provided by natural ecosystems, 9. Ensure effective disaster preparedness and response, 10. Rapid restoration and better reconstruction. On the other hand, in the other five fields, scores of less than 4 (3.20~3.85) were obtained and evaluated as weak resilience field; 2. Analyze, understand and utilize current and future risk scenarios, 3. Strengthen financial capacity for resilience, 6. Strengthen institutional capacity for resilience, 7. Understanding and strengthening social competence for resilience, 8. Strengthen resilience of infrastructure. In addition, through this study, the risk factors faced by Incheon Metropolitan City could be identified by priority, resilience improvement measures to minimize disaster risks, urban safety-based urban development plans, available disaster reduction resources, and integrated disasters. Measures were prepared.

• Korean Journal of Environment and Ecology
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• v.24 no.1
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• pp.62-68
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• 2010

This study was conducted to find out how the germination, phenology and leaf morphology of Phytolacca insularis(endemic species of Korea) and P. americana(alien species) react to the global warming situation. Seed and seedlings of two species were sampled and placed under two separate conditions for the experiment. One of the seed and seedlings was treated in the glass house with control(ambient $CO_2$+ambient temperature, (AC-AT), and the other with control(elevated $CO_2$+ elevated temperature, EC-ET), over the period of one year, 2008-2009. The germination rate of two species was fast, and the time of their germination started early, when they were treated at EC-ET than at AC-AT. Furthermore, the germination rate of Phytolacca insularis(endemic species of Korea) was found to be comparatively lower than that of P. americana(alien species). The former showed only vegetative growth whereas the latter showed both vegetative growth and reproductive growth in one year period. The more $CO_2$ degree and temperature increased, phenological responses of two species, including leaf growth, the formation of flower stems, flowering, and fruit maturing, became much faster, and the time of their leaf-yellowing was delayed. The lamina length of P. insularis was not significantly affected by elevated $CO_2$ and temperature. The lamina length of P. americana, on the other hand, became longer at EC-ET than at AC-AT, but the leaf width of both species increased at EC-ET. As for the number of leaves, both species showed no difference. Finally, the ratio of the leaf area of P. insularis was high at AC-AT, but P. americana was high at EC-ET. These results indicate that P. americana, aliens species, reacts more sensitively to global warming than P. insularis, endemic species, does.

• Korean Journal of Agricultural and Forest Meteorology
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• v.1 no.1
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• pp.1-11
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• 1999

Rice yield and primary productivity (NPP) are dependent upon the variability of climate and soil. The variability and regionality of the rice yield and net primary productivity were evaluated with the meteorological data collected from Korea Meteorology Administration and the actual rice yield data from the Ministration of Agriculture and Forestry, Korea. The estimated NPP using the three models, dependent upon temperature(NPP-T), precipitation(NPP-P) and net radiation(NPP-R), ranged from 10.87 to 17.52 Mg ha$^{-1}$ with average of 14.69 Mg ha$^{-1}$ in the South Korea and was ranged 6.47 to 15.58 Mg ha$^{-1}$ with average of 12.59 Mg ha$^{-1}$ in the North Korea. The primary limiting factor of NPP in Korea was net radiation, and the secondary limiting factor was temperature. Spectral analysis on the long term change in air temperature in July and August showed periodicity. The short periodicity was 3 to 7 years and the long periodicity was 15 to 43 years. The coefficient of variances, CV, of the rice yield from 1989 to 1998 ranged 3.23 percents to 12.37 percents which were lower than past decades. The CV's in Kangwon and Kyeongbuk were high while that in Chonbuk was the lowest. The prediction model based on th e yield index and yield response to temperature obtain ed from the field crop situation showed reasonable results and thus the spatial distributions of rice yield and predicted yield could be expressed in the maps. The predicted yields was well fitted with the actual yield except Kyungbuk. For better prediction, modification should be made considering radiation factor in further development.

• Korean Journal of Breeding Science
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• v.43 no.4
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• pp.233-240
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• 2011

Food security has been a main global issue due to climate changes and growing world population expected to 9 billion by 2050. While biodiversity is becoming more highlight, breeders are confronting shortage of various genetic materials needed for new variety to tackle food shortage challenge. Though biotechnology is still under debate on potential risk to human and environment, it is considered as one of alternative tools to address food supply issue for its potential to create a number of variations in genetic resource. The new technology, phenomics, is developing to improve efficiency of crop improvement. Phenomics is concerned with the measurement of phenomes which are the physical, morphological, physiological and/or biochemical traits of organisms as they change in response to genetic mutation and environmental influences. It can be served to provide better understanding of phenotypes at whole plant. For last decades, high-throughput screening (HTS) systems have been developed to measure phenomes, rapidly and quantitatively. Imaging technology such as thermal and chlorophyll fluorescence imaging systems is an area of HTS which has been used in agriculture. In this article, we review the current statues of high-throughput screening system in phenomics and its application for crop improvement.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.135-145
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• 2019

Analysis of a long cycle or a trend of time series data based on a long-term observation would require comparability between data observed in the past and the present. In the present study, we proposed an approach to ensure the compatibility among the instruments used for the long-term observation, which would allow to secure continuity of the data. An open-path gas analyzer (Model LI-7500, LI-COR, Inc., USA) has been used for eddy covariance flux measurement in the Gwangneung deciduous forest for more than 10 years. The open-path gas analyzer was replaced by an enclosed-path gas analyzer (Model EC155, Campbell Scientific, Inc., USA) in July 2015. Before completely replacing the gas analyzer, the carbon dioxide ($CO_2$) and latent heat fluxes were collected using both gas analyzers simultaneously during a five-month period from August to December in 2015. It was found that the $CO_2$ fluxes were not significantly different between the gas analyzers under the condition that the daily mean temperature was higher than $0^{\circ}C$. However, the $CO_2$ flux measured by the open-path gas analyzer was negatively biased (from positive sign, i.e., carbon source, to 0 or negative sign, i.e., carbon neutral or sink) due to the instrument surface heating under the condition that the daily mean temperature was lower than $0^{\circ}C$. Despite applying the frequency response correction associated with tube attenuation of water vapor, the latent heat flux measured by the enclosed-path gas analyzer was on average 9% smaller than that measured by the open-path gas analyzer, which resulted in >20% difference of the sums over the study period. These results indicated that application of the additional air density correction would be needed due to the instrument heat and analysis of the long-term observational flux data would be facilitated by understanding the underestimation tendency of latent heat flux measurements by an enclosed-path gas analyzer.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• Ecology and Resilient Infrastructure
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• v.10 no.3
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• pp.85-96
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• 2023

The study involved the categorization of domestic lakes located in South Korea into three groups based on their salinity levels: upstream reservoirs with salinity less than 0.3 psu, estuarine reservoirs with salinity ranging from 0.3 to 2 psu, and brackish lagoons with salinity exceeding 2 psu. Subsequently, the research assessed variations in the concentrations of total nitrogen (T-N) and total phosphorus (T-P) in the sediment of these lakes using statistical analysis, specifically one-way analysis of variance (ANOVA). Additionally, a laboratory core incubation test was conducted to investigate the benthic nutrient fluxes in Songji lagoon (salinity: 11.80 psu), Ganwol reservoir (salinity: 0.73 psu), and Janggun reservoir (salinity: 0.08 psu) under both aerobic and anoxic conditions. The findings revealed statistically significant differences in the concentrations of T-N and T-P among sediments in the lakes with varying salinity levels (p<0.05). Further post-hoc analysis confirmed significant distinctions in T-N between upstream reservoirs and estuarine reservoirs (p<0.001), as well as between upstream reservoirs and brackish lagoons (p<0.01). For T-P, a significant difference was observed between upstream reservoirs and brackish lagoons (p<0.01). Regarding benthic nutrient fluxes, Ganwol Lake exhibited the highest diffusive flux of NH₄⁺-N, primarily due to its physical characteristics and the inhibition of nitrification resulting from its relatively high salinity. The flux of NO₃^--N was lower at higher salinity levels under aerobic conditions but increased under anoxic conditions, attributed to the impact of salinity on nitrification and denitrification. Additionally, the flux of PO₄^3--P was highest in Songji Lake, followed by Ganwol Lake and Janggun Reservoir, indicating that salinity promotes the diffusive flux of phosphate through anion adsorption competition. It's important to consider the influence of salinity on microbial communities, growth rates, oxidation-reduction processes, and nutrient binding forms when studying benthic diffusive nutrient fluxes from lake sediments.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.5
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• pp.417-426
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• 2023

Rapid climate change has resulted in glacial retreat and increased meltwater inputs in the Antarctic Peninsula, including King George Island where Marian Cove is located. Consequently, these phenomena are expected to induce changes in the water column light properties, which in turn will affect phytoplankton communities. To comprehend the effects of glacial retreat on the marine ecosystem in Marian Cove, we investigated on phytoplankton biomass (chlorophyll-a, chl-a) and various environment parameters in this area in December 2021 and January 2022. The average temperature at the euphotic depth in January 2022 (1.41 ± 0.13 ℃) was higher than that in December 2021 (0.87 ± 0.17 ℃). Contrastingly, the average salinity was lower in January 2022 (33.9 ± 0.10 psu) than in December 2021 (34.1 ± 0.12 psu). Major nutrients, including dissolved inorganic nitrogen, phosphate, and silicate, were sufficiently high, and thus, did not act as limiting factors for phytoplankton biomass. In December 2021 and January 2022, the mean chl-a concentrations were 1.03 ± 0.64 and 0.66 ± 0.15㎍ L^-1, respectively. The mean concentration of suspended particulate matter (SPM) was 24.9 ± 3.54 mgL^-1 during the study period, with elevated values observed in the vicinity of the inner glacier. However, relative lower chl-a concentrations were observed near the inner glacier, possibly due to high SPM load from the glacier, resulting in reduced light attenuation by SPM shading. Furthermore, the proportion of nanophytoplankton exceeded 70% in the inner cove, contributing to elevated mean fractions of nanophytoplankton in the glacier retreat marine ecosystem. Overall, our study indicated that freshwater and SPM inputs from glacial meltwater may possibly act as main factors controlling the dynamics of phytoplankton communities in glacier retreat areas. The findings may also serve as fundamental data for better understanding the carbon cycle in Marian Cove.