• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.83-94
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• 2022

In order to actively prepare to frost damage that occurs in the process of growing crops, the spatial and temporal distribution of frost occurrence in South Korea was derived using frost observation data from 20 regions over the past 21 years (2000~2020). The main products are the number of frost days, first frost day, and last frost day by region. And the climatic trends of these results were identified by performing the Mann-Kendall trend test and Sen's slope estimator. In South Korea, a lot of frost occurs in the inland area to the west of the Taebaek and Sobaek Mountains. Relatively closer to the coastal area, the number of frost days is small, the first frost day is slow, and the last frost day is early. The east coast region has fewer frost days, the first frost day is later, and the last frost day is earlier than the west coast region. The southern sea, the southeastern sea region, and the island region rarely experience frost. As a result of the annual time series trend analysis, although South Korea is a country where climate warming is progressing, there was no trend in reducing the number of frost days and slowing the first frost day, and it was found that the last frost day is delayed by 0.5 days per year.

• Analytical Science and Technology
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• v.7 no.3
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• pp.1069-1084
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• 1994

수 MV급 탄뎀형 가속기와 정전형, 자장형 질량분석기를 결합함으로써 존재비가 극히 작은 동위원소 측정이 가능해진다. 수 MeV로 가속이 되면 분해에 방해가 되는 모든 분자이온들이 제거되며, 탄뎀형 가속기에서는 음이온으로부터 가속이 개시되므로 몇몇 음이온을 형성하지 못하는 동중원소의 간섭으로부터 자유로워지기 때문에 고감도분석이 실현될 수 있다. 이외에 음이온을 형성하는 동중원소들은 주로 이온함인 최종 검출기에서의 유효 전하에 따른 에너지손실 차이를 이용하여 효과적으로 제거할 수 있다. 현재는 주로 장반감기 방사성동위원소인 $^{10}Be$, $^{14}C$, $^{26}Al$, $^{36}Cl$과 $^{129}I$ 등의 측정법이 확립되어 천연시료 중에서 동위원소 존재비 $10^{-12}$에서 $10^{-15}$까지의 정량이 가능하며, 원자수로 환산한 검출하한을 $10^5$개가 된다. 또한 해당 원소를 기준으로 소요 시료량은 대부분 mg 정도로 충분하다. 지금까지는 불가능했던 이러한 특징으로 인해 지난 수년간 AMS(Accelerator Mass Spectrometry)가 활용되어 온 연구분야는 지구과학(기후학, 우주화학, 빙하학, 수문학, 해양학, 퇴적학, 화산학 및 광물탐사), 인류 및 고고학(연대측정), 그리고 물리학(천체물리, 핵 및 입자물리) 등으로 다양하다. 이외에 생의학 및 재료과학 분야에서도 AMS를 활용하고자 하는 노력이 계속되고 있다. 본 해설에서는 가속기질량분석기술의 특징, 원리, 장치 및 활용분야 등을 소개하고자 하며, 이로써 관련 분야의 연구 활성화에 기여하고자 한다.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.79-105
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• 2023

Due to unprecedented extreme weather events such as global warming and climate change, many parts of the world suffer from severe pain, and economic losses are also snowballing. In order to address these problems, 'The Paris Agreement' was signed in 2016, and an intergovernmental consultative body was formed to keep the average temperature rise of the Earth below 1.5℃. Korea also declared 'Carbon Neutrality in 2050' to prevent climate catastrophe. In particular, it was found that the increase in temperature caused by greenhouse gas emissions hurts the environment and society as a whole, as well as the export-dependent economy of Korea. In addition, as the diversification of transportation types is accelerating, the change in means of choice is also increasing. As the development paradigm in the low-growth era changes to urban regeneration, interest in idle railway sites is rising due to reduced demand for routes, improvement of alignment, and relocation of urban railways. Meanwhile, it is possible to partially achieve the solar power generation goal of 'Renewable Energy 3020' by utilizing already developed but idle railway sites and take advantage of being free from environmental damage and resident acceptance issues surrounding the location; but the actual use and plan for these solar power facilities are still lacking. Therefore, in this study, using the big data provided by the Korea National Railway and the Renewable Energy Cloud Platform, we develop an algorithm to discover and analyze suitable idle sites where solar power generation facilities can be installed and identify potentially applicable areas considering conditions desired by users. By searching and deriving these idle but relevant sites, it is intended to devise a plan to save enormous costs for facilities or expansion in the early stages of development. This study uses various cluster analyses to develop an optimal algorithm that can derive solar power plant locations on idle railway sites and, as a result, suggests 202 'actively recommended areas.' These results would help decision-makers make rational decisions from the viewpoint of simultaneously considering the economy and the environment.

• Journal of Climate Change Research
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• v.8 no.3
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• pp.257-264
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• 2017

Carbon capture and storage (CCS) technology has been suggested as an ultimate strategy for mitigating climate change. However, potential leakage of $CO_2$ from the CCS facilities could lead to serious damage to environment. Plants can be a bio-indicator for $CO_2$ leakage as a cost-effective way, although plants' responses vary with plant species. In this study, a greenhouse experiment was conducted to investigate the relation between the $CO_2$ tolerance of corn species and the initial physiological responses to the elevated soil $CO_2$ concentration. Treatment groups included CI (99.99% $CO_2$ gas injection) and BI (no gas injection). Mean soil $CO_2$ concentration for the CI treatment was 19.5~39.4%, and mean $O_2$ concentration was 6.6~18.4%. The soil gas concentrations in the BI treatment were at the ambient levels. In the CI treatment, chlorophyll content was not decreased until the $13^{th}$ day of the $CO_2$ injection. On the $15^{th}$ day, leaf starch content and stomatal conductance were increased by 89% and 25% in the CI treatment compared to the BI treatment, respectively. This might be due to the compensatory reaction of corn to avoid high soil $CO_2$ stress. However, the prolonged $CO_2$ injection decreased chlorophyll content after 13 days. After $CO_2$ injection, plant biomass was reduced by 25% in the CI treatment compared to the BI treatment. Due to the inhibited root growth, leaf phosphorous and potassium contents were decreased by 54% on average in the CI treatment. This study indicates that corn has a high tolerance to soil $CO_2$ concentration of 30% for 2 weeks by its compensatory reactions such as an maintenance of chlorophyll content and an increase in stomatal conductance.

• Korean journal of applied entomology
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• v.46 no.1 s.145
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• pp.27-35
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• 2007

Seasonal occurrences of tobacco cutworm, Spodoptera litura and beet armyworm, Spodoptera exigua were observed using sex pheromone traps at different locations and climatic regions in Yeongnam district. In Gyeongnam province, S. litura male adults kept occur from mid or late March to mid or late November Whereas in Gyeongbuk province, S. litura occurred from mid or late April to early or mid November with exception at Uljin where it was late May to late October. According to the climatic regions, the peak occurrence of S. litura was middle September at the southern coast region, late August at the inland and the basin region, middle August at the inland mountainous region, and early September at the eastern middle coast region. The occurrence rate of S. litura was the highest at Jinju with 20.0% and the lowest at Changyeong with 8.6% in Cyeongnam province, while it was the highest at Sungju with 3.3% and the lowest at Uljin with 0.8% in Gyeongbuk province. In accordance with the climatic regions, the occurrence rate of S. litura was the highest at the inland region with 43.7%, and followed by the southern coast region (36.3%), the basin region (8.4%) and the inland mountainous region (7.0%), and was the lowest at the eastern middle coast legion with 4.6%. On the other hand, S. exigua occurred from early March to middle November with the exception of the eastern middle coast region including Pohang, Yeongdeog and U]ien in Cyeongbuk province where it occurred from mfd April to middle November. The peak occurrence of s. exigua was early August at the inland region, the basin region and the inland mountainous region, and was late of August at the southern coast region and the eastern middle coast region. The occurrence of S. exigua was the highest at Changyeong with 1.6% and the lowest at Busan with 0.4% in Gyeongnam province, while it was the highest at Sungju with 37.2% and the lowest at Uljin with 2.7% in Gyeongbuk province. The climatic regional occurrence rate of S. exigua was the highest at the basin region with 54.3%, and followed by the inland mountainous region (29.9%), the eastern middle coast region (9.3%) and the inland (3.9%), and was the lowest at the southern coast region with 2.6%. As a whole, S. litura occurred more in Gyeongnam province than Cyeongbuk province, while S. exigua occurred more in Gyeongbuk province than Gyeongnam province. According to the regions grouped by climatic differences, the occurrence of S. litura and S. exigua was the highest at the inland region in Gyeongnam province and at the basin region in Gyeongbuk province. The total number of S. litura captured by sex pheromone trap was 2.4 times higher than that of S. exigua. However, the first occurring time and the peak occurrence of S. exigua were slightly earlier than those of S. litura.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1199-1206
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• 2021

Accordingly, attention is also being paid to the agricultural use of remote sensing technique that non-destructively and continuously detects the growth and physiological status of crops. However, when remote sensing techniques are used for crop monitoring, it is possible to continuously monitor the abnormality of crops in real time. For this, standard growth information of crops is required and relative growth considering the cultivation environment must be identified. With the relationship between GDD (Growing Degree Days), which is the cumulative temperature related to crop growth obtained from ideal cultivation management, and the vegetation index as standard growth information, compared with the vegetation index observed with the spectralreflectance sensor(SRS_NDVI & SRS_PRI) in each rice paddy treated with standard cultivation management and non-fertilized, it was quantitatively identified as a time series. In the future, it is necessary to accumulate a database targeting various climatic conditions and varieties in the standard cultivation management area to establish a more reliable standard growth information.

• Journal of Climate Change Research
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• v.8 no.4
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• pp.305-312
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• 2017

We aimed at investigating the difference in $N_2O$ emission factors of chemical and organic fertilizers and identifying the main factors influencing annual fluctuations in $N_2O$ emission. We conducted two-year experiments in 2016 and 2017 in an agricultural field planted with sweet potato (Ipomoea batatas). Treatments included chemical NPK fertilizer (NPK) and chicken compost application at $10\;ton\;ha^{-1}$, $20\;ton\;ha^{-1}$, and $30\;ton\;ha^{-1}$ rates (CK1, CK2 and CK3). Control was also employed with no addition. Results showed that $N_2O$ emission rates were significantly related with soil water status and soil available N contents. Significant correlation between % water filled pore space (WFPS) and $N_2O$ emission was observed only when the %WFPS was greater than 40% and during the initial stage of the experiment (<60 d). Comparison of the emission factors in 2016 and 2017 showed us that the emission factor was greater in 2016 when the %WFPS was maintained higher by 16.5% compared to that in 2017. In 2016, the emission factor of organic fertilizer was higher than that of chemical fertilizer, while in 2017, the pattern was reversed. Annual variability in $N_2O$ emission could also be originated from the available N contents remaining in soil after being taken up by plants. If we apply excessive N fertilizer, the soil would contain excess amount of N which was not uptaken by plants, leading to a huge increase in $N_2O$ emission. This case would overestimate emission factor, which was the case for the organic fertilizer in 2016. Over-fertilization should be avoided when we set up an experiment to determine $N_2O$ emission factor.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.1
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• pp.11-18
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• 2012

Daily temperature data produced by harmonic analysis of monthly climate summary have been used as an input to plant phenology model. This study was carried out to evaluate the performance of the harmonic based daily temperature data in prediction of major phenological developments and to apply the results in improving decision support for agricultural production in relation to the climate change scenarios. Daily maximum and minimum temperature data for a climatological normal year (Jan. 1 to Dec. 31, 1971-2000) were produced by harmonic analysis of the monthly climate means for Seoul weather station. The data were used as inputs to a thermal time - based phenology model to predict dormancy, budburst, and flowering of Japanese cherry in Seoul. Daily temperature measurements at Seoul station from 1971 to 2000 were used to run the same model and the results were compared with the harmonic data case. Leaving no information on annual variation aside, the harmonic based simulation showed 25 days earlier release from endodormancy, 57 days longer period for maximum cold tolerance, delayed budburst and flowering by 14 and 13 days, respectively, compared with the simulation based on the observed data. As an alternative to the harmonic data, 30 years daily temperature data were generated by a stochastic process (SIMMETEO + WGEN) using climatic summary of Seoul station for 1971-2000. When these data were used to simulate major phenology of Japanese cherry for 30 years, deviations from the results using observed data were much less than the harmonic data case: 6 days earlier dormancy release, 10 days reduction in maximum cold tolerance period, only 3 and 2 days delay in budburst and flowering, respectively. Inter-annual variation in phenological developments was also in accordance with the observed data. If stochastically generated temperature data could be used in agroclimatic mapping and zoning, more reliable and practical aids will be available to climate change adaptation policy or decision makers.

• Journal of the Korean Geographical Society
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• v.45 no.1
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• pp.11-25
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• 2010

Green Growth was declared as a national development agenda in 2008. There are many contributing concepts and factors in the process of molding the agenda, such as climate change, sustainable development, globalization, the so-called 747 campaign pledges by President Lee in 2007, and the hunger for economic growth in Asia and the Pacific. Green Growth is rather growth-oriented and pays less attention to environmental conservation and social justice. Green Development would fit better as the name of the agenda, dealing with the weaknesses of Green Growth. Climate change itself is a testing ground for geographic knowledges, whose demand is growing rapidly. The contemporary issue increasingly bears complexity that Earth System Science and Sustainability Science have emerged as a research and applications program. Geography is widely recognized as a portal to these programs, where inter- and trans-disciplinary studies are required. Regional potentials should be evaluated from a holistic view so that proper development goals are chosen. Different development trajectory should be taken, depending on the amount of potential a region bears. Material loop should be closed for environmentally sound regions. Green way of life is essential for low carbon society. In the circumstances of climate change in Korean Peninsula and needing of energy efficiency, geographic insight or imagination is urgent for Green Development.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.347-357
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• 2019

The usefulness of processing and analysis systems of GIS-based agricultural climate data is affected by the reliability and availability of computing infrastructures such as cloud, on-premises, and hybrid. Cloud technology has grown in popularity. However, various reference cases accumulated over the years of operational experiences point out important features that make on-premises technology compatible with cloud technology. Both cloud and on-premises technologies have their advantages and disadvantages in terms of operational time and cost, reliability, and security depending on cases of applications. In this study, we have described characteristics of four general computing platforms including cloud, on-premises with hardware-level virtualization, on-premises with operating system-level virtualization and hybrid environments, and compared them in terms of advantages and disadvantages when a huge amount of GIS-based agricultural climate data were stored and processed to provide public services of agro-meteorological and climate information at high spatial and temporal resolutions. It was found that migrating high-resolution agricultural climate data to public cloud would not be reasonable due to high cost for storing a large amount data that may be of no use in the future. Therefore, we recommended hybrid systems that the on-premises and the cloud environments are combined for data storage and backup systems that incur a major cost, and data analysis, processing and presentation that need operational flexibility, respectively.