• Geomechanics and Engineering
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• 제37권6호
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• pp.577-590
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• 2024

With increasing demand for nuclear power generation, nuclear structures are being planned and constructed worldwide. A grave safety concern is that these structures are sensitive to large-magnitude shaking, e.g., during earthquakes. Seismic response analysis, which requires P- and S-wave velocities, is a key element in nuclear structure design. Accordingly, it is important to determine the P- and S-wave velocities in the Gyeongju and Pohang regions of South Korea, which are home to nuclear power plants and have a history of seismic activity. P- and S-wave velocities can be obtained indirectly through a correlation with physical properties (e.g., N values, Young's modulus, and uniaxial compressive strength), and researchers worldwide have proposed regression equations. However, the Gyeongju and Pohang regions of Korea have not been considered in previous studies. Therefore, a database was constructed for these regions. The database includes physical properties such as N values and P- and S-wave velocities of the soil layer, as well as the uniaxial compressive strength, Young's modulus, and P- and S-wave velocities of the bedrock layer. Using the constructed database, the geological characteristics and distribution of physical properties of the study region were analyzed. Furthermore, models for predicting P- and S-wave velocities were developed for soil and bedrock layers in the Gyeongju and Pohang regions. In particular, the model for predicting the S-wave velocity for the soil layers was compared with models from previous studies, and the results indicated its effectiveness in predicting the S-wave velocity for the soil layers in the Gyeongju and Pohang regions using the N values. The proposed models for predicting P- and S-wave velocities will contribute to predicting the damage caused by earthquakes.

• 대한원격탐사학회지
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• 제37권3호
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• pp.649-655
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• 2021

본 연구는 경주시를 대상으로 수행한 선행연구를 바탕으로 도출된 최적의 지진 취약성 평가 모델을 타 지역에 적용하여 그 성능을 교차 검증(cross-validation)하고자 한다. 테스트 지역은 2017 포항지진(Pohang Earthquake)이 발생한 포항시이며, 선행연구와 동일한 영향인자 및 피해현황 관련 데이터셋을 구축하였다. 검증 데이터 셋은 무작위로 추출해 구축하였으며, 경주시의 랜덤 포레스트(random forest, RF) 기반의 모델에 적용하여 예측 정확도를 도출하였다. 경주시의 모델(success) 및 예측(prediction) 정확도는 100%, 94.9%이며, 포항시 검증 데이터 셋을 적용해 예측 정확도를 확인한 결과 70.4%로 나타났다.

• 한국환경보건학회지
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• 제31권5호
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• pp.349-359
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• 2005

In this study, we focused on the geographical and the meterological conditions, the atmospheric examination, the soil contents and compositions in order to establish cultural properties conservation plan in Gyeongju and its surroundings. Also, the transport route with environmental contaminants in Ulsan and Pohang was examined. The results could be summarized as follows ; Air pollutant and environmental contaminant was transported by two types of winds. One is induced by local winds, the other is induced by synoptic winds. Air contaminant transported from coastal regions to inland regions were associated with wind velocity. Gyeongju had good atmospheric conditions, i.e. $SO_2\;0.009{\sim}0.011ppm,\;CO\;0.6{\sim}0.8ppm,\;NO_2\;0.015{\sim}0.020ppm,\;O_3\;0.017{\sim}0.032ppm,\;PM_{10}\;46{\sim}62{\mu}g/m^3\;and\;Pb\;0.034{\sim}0.060{\mu}g/m^3$, which was below environmental air qualify standards and was little lower than those of Pohang and Ulsan. However, Ulsan and Pohang city are located on south-east coast and have many industrial facilities. Hence, air pollution problems become serious issues in Ulsan, Pohang, Busan, Daegu and other cities due to the emission of air pollutants from the various industrial facilities, incinerator and power plants, etc. The soil of Gyeongju had heavy metals conditions, i.e. $Cd\;0.01{\sim}0.08mg/kg,\;Cu\;N.D{\sim}2.39mg/kg,\;As\;N.D{\sim}0.07mg/kg,\;Hg\;N.D{\sim}0.15mg/kg,\;Pb\;0.49{\sim}1.39mg/kg,\;Cr^{+6}\;0.02{\sim}0.42mg/kg,\;Fe\;0.74{\sim}1.55mg/kg,\;Mn\;0.11{\sim}0.49mg/kg\;and\;Zn\;1.11{\sim}3.56mg/kg$. However, pH value of soil had range of $4.12{\sim}7.45$. The results showed that high pH concentration of soil could occur due to air pollution diffusion and environmental contaminant transport at Ulsan and Pohang city.

• 한국대기환경학회지
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• 제34권4호
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• pp.517-533
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• 2018

We utilize the CAMx (Comprehensive Air Quality Model with eXtensions) system and the PSAT (Particulate Source Apportionment Technology) diagnostic tool to determine the $PM_{2.5}$ concentration and to perform its source apportionment in the southeastern region of South Korea. For a year-long simulation, eight local authorities in the region such as Pohang, Daegu, Gyeongju, Ulsan, Busan-Gimhae, Gosung-Changwon, Hadong, and all remaining areas in Gyeongsangnam-do, are selected as source areas based on the emission rates of $NO_x$, $SO_x$, VOC, and primary PM in CAPSS (Clean Air Policy Support System) 2013 emissions inventory. The CAMx-PSAT simulation shows that Pohang has the highest $PM_{2.5}$ self-contribution rate (25%), followed by Hadong (15%) and Busan-Gimhae (14%). With the exception of Pohang, which has intense fugitive dust emissions, other authorities are strongly affected by emissions from their neighboring areas. This may be measured as much as 1 to 2 times higher than that of the self-contribution rate. Based on these estimations, we conclude that the efficiency of emission reduction measures to mitigate $PM_{2.5}$ concentrations in the southeastern region of South Korea can be maximized when the efforts of local or regional emission controls are combined with those from neighboring regions. A comprehensive control policy planning based on the collaboration between neighboring jurisdictional boundaries is required.

• Weed & Turfgrass Science
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• 제3권1호
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• pp.6-12
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• 2014

본 조사는 2013년에 경북지역 13개 시 군의 320지점에서 논 잡초 발생 현황을 파악하기 위하여 수행되었다. 경북지역의 논잡초 조사결과, 27개과(family) 51초종(species)이었고 과별로는 벼과(family) 9초종, 사초과(family) 5초종, 마디풀과(family) 4초종, 국화과(family) 4초종 순으로 나타났다. 발생 잡초종의 생활형태는 일년생잡초 34종, 다년생잡초 17종으로 대부분 일년생잡초였다. 경북지역의 우점잡초는 물달개비(10.80%) > 좀개구리밥(10.74%) > 가막사리(8.77%) > 강피(7.17%) > 올챙이고랭이(6.20%) > 올방개(6.13%) > 벗풀(5.85%) 순이었다. 물달개비, 좀개구리밥, 가막사리, 강피, 올챙이고랭이, 올방개, 벗풀의 우점도는 전체 잡초종의 50%이상 차지하였고 TWINSPAN 분석을 통한 지역별 잡초종의 유사성은 여뀌바늘, 올챙이고랭이, 미국외풀, 마디풀, 뚝새풀에 의해 구분되어 추후 경북지역 논 잡초의 발생 양상을 예측하며 잡초군락의 변화를 파악함으로써 체계적인 논 잡초 관리방안을 마련할 수 있을 것으로 판단되었다.

• 한국지진공학회논문집
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• 제22권6호
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• pp.323-332
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• 2018

Recent two moderate earthquakes (2016 $M_w=5.4$ Gyeongju and 2017 $M_w=5.5$ Pohang) in Korea provided the unique chance of developing a set of relations to estimate instrumental seismic intensity in Korea by augmenting the time-history data from MMI seismic intensity regions above V to the insufficient data previously accumulated from the MMI regions limited up to IV. The MMI intensity regions of V and VI was identified by delineating the epicentral distance from the reference intensity statistics in distance derived by using the integrated MMI data obtained by combining the intensity survey results of KMA (Korea Meteorological Administration) and 'DYFI (Did You Feel It)' MMIs of USGS. The time-histories of the seismic stations from the MMI intensity regions above V were then preprocessed by applying the previously developed site-correction filters to be converted to a site-equivalent condition in a manner consistent with the previous study. The average values of the ground-motion parameters for the three ground motion parameters of PGA, PGV and BSPGA (Bracketed Summation of PGA per second for 30 seconds) were calculated for the MMI=V and VI and used to generate the dataset of the average values of the ground-motion parameters for the individual MMIs from I to VI. Based on this dataset, the linear regression analysis resulted in the following relations with proposed valid ranges of MMI. $MMI=2.36{\times}log_{10}(PGA(gal))+1.44$ ($I{\leq}MMI$$MMI=2.44{\times}log_{10}(PGV(kine))+4.86$ ($I{\leq}MMI$$MMI=2.59{\times}log_{10}(BSPGA(gal{\cdot}sec))-1.02$ ($I{\leq}MMI$

• 방사선산업학회지
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• 제17권3호
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• pp.299-307
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• 2023

Given that toxic substances are diffused by the various movements of the atmosphere, it is very important to evaluate the risks associated with this phenomenon. When analyzing the behavioral characteristics of these atmospheric diffusion models, the main input data are the wind speed and wind direction among the meteorological data. In particular, it is known that a certain wind direction occurs in summer and winter in Korea under the influence of westerlies and monsoons. In this study, synoptic meteorological observation data provided by the Korea Meteorological Administration were analyzed from January 1, 2012 to the end of August of 2022 to understand the regional wind characteristics of nuclear power plants and surrounding areas. The selected target areas consisted of 16 weather stations around the Hanbit, Kori, Wolsong, Hanul, and Saeul nuclear power plants that are currently in operation. The analysis was based on the temperature, wind direction, and wind speed data at those locations. Average, maximum, minimum, median, and mode values were analyzed using long-term annual temperature, wind speed, and wind direction data. Correlation coefficient values were also analyzed to determine the linear relationships among the temperature, wind direction, and wind speed. Among the 16 districts, Uljin had the highest wind speed. The median wind speed values for each region were lower than the average wind speed values. For regions where the average wind speed exceeds the median wind speed, Yeongju, Gochang, Gyeongju, Yeonggwang, and Gimhae were calculated as 0.69 m s^-1, 0.54m s^-1, 0.45m s^-1, 0.4m s^-1, and 0.36m s^-1, respectively. The average temperature in the 16 regions was 13.52 degrees Celsius; the median temperature was 14.31 degrees and the mode temperature was 20.69 degrees. The average regional temperature standard deviation was calculated and found to be 9.83 degrees. The maximum summer temperatures were 39.7, 39.5, and 39.3 in Yeongdeok, Pohang, and Yeongcheon, respectively. The wind directions and speeds in the 16 regions were plotted as a wind rose graph, and the characteristics of the wind direction and speed of each region were investigated. It was found that there is a dominant wind direction correlated with the topographical characteristics in each region. However, the linear relationship between the wind speed and direction by region varied from 0.53 to 0.07. Through this study, by evaluating meteorological observation data on a long-term synoptic scale of ten years, regional characteristics were found.

• 환경생물
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• 제31권3호
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• pp.225-231
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• 2013

동해안의 암반조간대 무척추동물상의 분포 특성을 연구하기 위하여 독도를 비롯한 울릉도, 경상북도의 경주, 포항, 영덕, 울진 그리고 강원도 등 총 19개 정점의 암반 조간대무척추동물상을 조사하여 출현종의 유사도를 공통종의 출현비율 (%)과 Bray-Curtis similarity matrix를 이용한 집괴분석과 MDS를 이용하여 분석하였으며 SIMPER를 이용하여 독도와 그 외의 동해안 암반저서 무척추동물의 특징종을 선출하였다. 공통종의 출현비와 집괴분석결과, 가장 가까이 위치한 울릉도를 제외하면, 경상북도의 영덕이 가장 높은 유사도를 보였으나, 전체적으로 독도 암반저서생태계는 다른 동해안 연안과 차이를 보인 것으로 나타났다.

• 한국동물위생학회지
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• 제34권3호
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• pp.251-258
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• 2011

This study was performed to determine the prevalence of Theileria sergenti (T. sergenti) in cattle reared in eastern areas of Gyeongbuk province by PCR. Among 443 samples collected from 42 cattle farms, 96 (21.7%) samples from 13 (31.0%) farms were positive for T. sergenti. By regions, 87 (26.6%) out of 327 cattle in Gyeongju, 8 (9.5%) out of 84 cattle in Pohang, and 1 (3.1%) out of 32 cattle in Ulleung were positive for T. sergenti. T. sergenti infection in dairy cattle (27.9%) was significantly higher than that in Korean cattle (9.4%, P<0.0001). Accordingly, Korean cattle were more resistant to T. sergenti infection. Prevalence of T. sergenti in cattle was increased with age (P<0.0001). The infection rate in cows (23.3%) was significantly higher than that in bulls (5.0%, P<0.01). Seasonally, prevalence of T. sergenti in cattle was highest in autumn (32.7%, P<0.01). Prevalence of T. sergenti in grazing cattle (66.7%) was significantly higher than that in non-grazing cattle (15.8%, P<0.0001). Since prevalence of T. sergenti infection is high in cattle reared in eastern areas of Gyeongbuk province, survey on other hemoparasites and appropriate control programs need to be established in this region.

• 한국경제지리학회지
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• 제23권1호
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• pp.1-17
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• 2020

본 연구는 기업 간 거래망을 활용하여 지역 간 경제적 연계를 확인하고 경제적 상호의존성에 기초한 기능적 경제권을 설정하는데 그 목적이 있다. 기존의 경제권은 이미 알려진 행정도 경계나 문화적 동질성을 기준으로만 설정되거나 실증자료를 활용하더라도 통근, 인구이동, 화물흐름 등 경제활동을 충분히 설명하지 못하는 자료에만 의존하였다. 본 연구는 이러한 한계를 극복하기 위해 한국기업데이터의 CRETOP+ 데이터베이스를 활용하여 실제 기업 간 거래망을 구축하고, 커뮤니티 발견법을 적용해 우리나라의 기능적 경제권을 파악하였다. 분석결과 거래망에 따라 6~7개의 경제권이 도출되었다. 특히 수도권, 충청권, 강원권을 통합한 하나의 거대한 경제권역이 형성되어 있었으며, 전북, 전남은 서로 간의 기업 간 거래빈도가 매우 낮아 호남권으로 묶이기보다 별도의 경제권을 형성하고 있는 것으로 나타났다. 대구, 경북의 경제권과 부산, 경남의 경제권이 각각 존재하는 것으로 나타났지만 울산, 경주, 포항은 도 경계를 넘어서 별도의 권역을 형성하고 있는 것으로 나타났다. 이를 통해 본 연구는 향후 국가균형발전정책에서 실증 자료에 기반한 정책공간의 설정이 필요함을 주장한다.