• Title/Summary/Keyword: 인공순환

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Sulfate Reduction in the Marine Environments: Its Controlling Factors and Relative Significance in Mineralization of Organic Matter (해양환경의 황산염 환원율 조절요인 및 유기물 분해에 있어 황산염 환원의 중요성)

  • 현정호;이홍금;권개경
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.8 no.2
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    • pp.210-224
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    • 2003
  • Sulfate reduction is a microbiological process which occurs ubiquitously in anaerobic marine environment. Sulfate reducing bacteria play a significant role in anaerobic decomposition of organic matter and regeneration of inorganic nutrients which supports the primary production in the water column (i.e., benthic-pelagic coupling) and, in special case, could be responsible for the harmful algal bloom in the coastal marine environment. Summary of the sulfate reduction rates reported in various marine sedimentary environments revealed that supply of organic substrates and presence of various electron acceptors (i.e., $O_2$, NO$_{3}$$^{[-10]}$ , Fe(III) and Mn(IV), etc.) for other aerobic and anaerobic respiration directly affect the sulfate reduction rate and relative significance of sulfate reduction in organic matter mineralization. Significance of temperature, macrophytes and bioturbation is discussed as factors controlling supply of organic substrates and distribution of electron acceptors. Finally, we suggest studies on the anaerobic microbiological processes associated with biogeochemical element cycles in the coastal environments of Korea where massive operation of organic enriched fish cage farm, frequent occurrence of toxic algal bloom and hypoxia and conservation of tidal flat are of major environmental issues.

CO2 net atmospheric flux estimation and influence factors analysis in a stratified reservoir (성층화된 저수지에서 CO2 NAF 산정 및 영향 인자 분석)

  • Park, Hyung Seok;Chung, Se Woong;Lee, Eun Ju
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.73-73
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    • 2019
  • 지구 표면의 약 2%에 해당하는 담수에서 육상계 전체가 흡수하는 탄소의 50%가 배출되며, 이는 토양표면에서 배출되는 탄소량에 비해 더 큰 수치로 전 지구적 탄소순환 해석에 중요한 역할을 한다. 특히, 내륙수역과 대기의 경계면에서 $CO_2$ 이동은 전 지구적 탄소순환의 중요한 구성요소로 평가되고 있다. 호수와 저수지 같은 담수 저류시설은 육상에서 기인한 탄소의 운송 및 처리 역할을 한다. 하지만, 저수지에서 온실가스배출량을 평가할 수 있는 명확한 방법론이 부족하며, 전지구 규모 GHGs배출량에 대한 추정에 대한 불확실성이 상당히 큰 상황이다. 본 연구에서는 몬순기후대에 위치한 인공저수지를 대상으로 보다 신뢰도있는 온실가스 배출량 추정을 위해 $CO_2$ NAF 산정하고, 산정에 영향을 미치는 인자들을 분석 하였다. 분석을 위해 $CO_2$ NAF 산정에 필요한 수리 및 수질 인자들을 2017년부터 2018년까지 수집하고, 기초통계량 및 상관분석을 실시하였다. 또한, 주성분분석(PCA) 및 다중선형회귀모델(MLR)과 랜덤포레스트(RF) 기법을 사용해 변수 중요도를 평가하였으며, $CO_2$ NAF 산정 주요인자인 기체교환 계수를 경험적 모델 3종(Cole and Caraco, Crusius, Vachon), 표면갱신형 모델 4종(Heiskanen, Maclntyre, Read, Soloviev)을 비교, 검토하였다. 조사기간 동안 기체교환계수 산정 결과 Crusius 모델 예측값이 평균 $0.342(0.047{\sim}4.323)cm\;hr^{-1}$으로 검토한 모델중 가장 낮은 평균값을 보였으며, Heiskane 모델이 $2.135(0.337{\sim}5.152)cm\;hr^{-1}$으로 가장 큰 평균값을 보였다. 대상 수체는 연주기로 완전혼합되며 수온성층이 약화되는 시기에 저수지 표층 아래에 축적된 탄소가 표층으로 전달되어 높은 수준의 p$CO_2$를 보이며, 수표면에 큰 난류 강도가 작용하는 기간에 대기중으로 배출(pulse emission) 기작이 나타난다. NAF 산정결과 경험적 모델의 NAF값($-1246.0{\sim}6510.3mg-CO_2m^{-2}day^{-1}$)은 표면갱신형 모델 NAF값($-1436.1{\sim}8485.7mg-CO_2m^{-2}day^{-1}$)보다 낮은 수준을 보였으며, 풍속의 함수만을 이용하는 경험적 모델보다 부력 플럭스와 난류 혼합의 영향을 고려하는 Macintyre, Heiskanen모델이 성층 저수지의 $CO_2$ NAF 산정에 적합한 것으로 나타났다. $CO_2$ NAF 산정의 주요인자로 MLR모델은 Tw, EC, pH, Chla, TOC, Alk, RF모델은 EC, DO, TOC가 중요 변수로 평가되었다. PCA 분석결과, 수온이 낮고 성층이 약화되며 pH가 낮은 상태에서 NAF가 큰 것으로 나타났다.

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Vulnerability Assessment of the Climate Change on the Water Environment of Juam Reservoir (기후변화에 따른 주암호 수환경 취약성 평가)

  • Yoon, Sung Wan;Chung, Se Woong;Park, Hyung Seok
    • Proceedings of the Korea Water Resources Association Conference
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    • 2015.05a
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    • pp.519-519
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    • 2015
  • 2007년 발간된 IPCC의 4차 평가보고서에서 자연재해, 환경, 해양, 농업, 생태계, 보건 등 다양한 부분에 미치는 기후변화의 영향에 대한 과학적 근거들이 제시되면서 기후변화는 현세기 범지구적인 화두로 대두되고 있다. 또한, 기후변화에 의한 지구 온난화는 대규모의 수문순환 과정에서의 변화들과 연관되어 담수자원은 기후변화에 대단히 취약하며 미래로 갈수록 악영향을 받을 것으로 6차 기술보고서에서 제시하고 있다. 특히 우리나라는 지구온난화가 전 지구적인 평균보다 급속하게 진행될 가능성이 높기 때문에 기후변화에 대한 담수자원 취약성이 더욱 클 것으로 예상된다. 따라서 지표수에 용수의존도가 높은 우리나라의 댐 저수지를 대상으로 기후변화에 따른 수환경 변화의 정확한 분석과 취약성 평가는 필수적이다. 본 연구에서는 SRES A1B 시나리오를 적용하여 기후변화가 주암호 저수지의 수환경 변화에 미치는 영향을 분석하였다. 지역스케일의 미래 기후시나리오 생산을 위해 인공신경망(Artificial Neural Network.,ANN)기법을 적용하여 예측인자(강우, 상대습도, 최고온도, 최저온도)에 대해 강우-유출모형에 적용이 가능한 지역스케일로 통계적 상세화를 수행하였으며, 이를 유역모델에 적용하여 저수지 유입부의 유출량 및 부하량을 예측하였다. 유역 모델의 결과를 토대로 저수지 운영모델에 저수지 유입부의 유출량을 적용하여 미래 기간의 방류량을 산정하였으며, 최종적으로 저수지 모델에 유입량, 유입부하량 및 방류량을 적용하여 저수지 내 오염 및 영양물질 순환 및 분포 예측을 통해서 기후변화가 저수지 수환경에 미치는 영향을 평가하였다. 기후변화 시나리오에 따른 상세기 후전망을 위해서 기후인자의 미래분석 기간은 (I)단계 구간(2011~2040년), (II)단계 구간(2041~2070년), (III) 단계 구간(2071~2100년)의 3개 구간으로 설정하여 수행하였으며, Baseline인 1991~2010년까지의 실측값과 모의 값을 비교하여 검증하였다. 강우량의 경우 Baseline 대비 미래로 갈수록 증가하는 것으로 전망되었으며, 2011년 대비 2100년에서 연강수량 6.4% 증가한 반면, 일최대강수량이 7.0% 증가하는 것으로 나타나 미래로 갈수록 집중호우의 발생가능성이 커질 것으로 예측되었다. 유역의 수문 수질변화 전망도 강수량 증가의 영향으로 주암댐으로 유입하는 총 유량이 Baseline 대비 증가 하였으며, 유사량 및 오염부하량도 증가하는 것으로 나타났다. 저수지 수환경 변화 예측결과 유입량이 증가함에 따라서 연평균 체류시간이 감소하였으며, 기온 및 유입수온 상승의 영향으로 (I)단계 구간대비 미래로 갈수록 상층 및 심층의 수온이 상승하는 것으로 나타났다. 연중 수온성층기간 역시 증가하는 것으로 나타났으며, 남조류는 (I)단계 구간 대비 (III)단계 구간으로 갈수록 출현시기가 빨라지며 농도 역시 증가하였다. 또한 풍수년, 평수년에 비해 갈수년에 남조류의 연평균농도 상승폭과 최고농도가 크게 나타나 미래로 갈수록 댐 유입량이 적은 해에 남조류로 인한 피해 발생 가능성이 높아질 것으로 예상된다.

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Fundamental Properties of Lightweight Concrete with Dry Bottom Ash as Fine Aggregate and Burned Artificial Lightweight Aggregate as Coarse Aggregate (건식 바텀애시 경량 잔골재와 소성 인공경량 굵은골재를 사용한 콘크리트의 기초 특성)

  • Choi, Hong-Beom;Kim, Jin-Man
    • Journal of the Korean Recycled Construction Resources Institute
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    • v.6 no.4
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    • pp.267-274
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    • 2018
  • Though the wet bottom ash has been used as a type of lightweight aggregate, dry bottom ash, new type bottom ash from coal combustion power plant, has scarcely researched. It is excellent lightweight aggregate in the view point of construction material. This study is performed to check the applicability of dry bottom ash as a fine aggregate in lightweight aggregate concrete, by analyzing various properties of fresh and hardened concrete. We get results that the slump of concrete is within the target range at less than 75% replacement rate of dry bottom ash, the air content is not affected by the replacement rate of dry bottom ash, the bleeding capacity is less than $0.025cm^3/cm^2$ at 75% under of the replacement rate of dry bottom ash, and the compressive strength of concrete show 90% or more comparing the base mix while initial strength development is a little low. Oven dry unit weight of concrete is reduced by 8.9% when replaced 100% dry bottom ash, and dry shrinkage tends to decrease depending on increase of replacement rate of dry bottom ash. Modulus of elasticity of concrete shows no decease at 50% over of the replacement rate of dry bottom ash, while modulus of elasticity of concrete decreases when the replacement rate increases further. The dry bottom ash, when used as a fine aggregate in lightweight concrete, can be used effectively without any deterioration in quality.

CRNN-Based Korean Phoneme Recognition Model with CTC Algorithm (CTC를 적용한 CRNN 기반 한국어 음소인식 모델 연구)

  • Hong, Yoonseok;Ki, Kyungseo;Gweon, Gahgene
    • KIPS Transactions on Software and Data Engineering
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    • v.8 no.3
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    • pp.115-122
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    • 2019
  • For Korean phoneme recognition, Hidden Markov-Gaussian Mixture model(HMM-GMM) or hybrid models which combine artificial neural network with HMM have been mainly used. However, current approach has limitations in that such models require force-aligned corpus training data that is manually annotated by experts. Recently, researchers used neural network based phoneme recognition model which combines recurrent neural network(RNN)-based structure with connectionist temporal classification(CTC) algorithm to overcome the problem of obtaining manually annotated training data. Yet, in terms of implementation, these RNN-based models have another difficulty in that the amount of data gets larger as the structure gets more sophisticated. This problem of large data size is particularly problematic in the Korean language, which lacks refined corpora. In this study, we introduce CTC algorithm that does not require force-alignment to create a Korean phoneme recognition model. Specifically, the phoneme recognition model is based on convolutional neural network(CNN) which requires relatively small amount of data and can be trained faster when compared to RNN based models. We present the results from two different experiments and a resulting best performing phoneme recognition model which distinguishes 49 Korean phonemes. The best performing phoneme recognition model combines CNN with 3hop Bidirectional LSTM with the final Phoneme Error Rate(PER) at 3.26. The PER is a considerable improvement compared to existing Korean phoneme recognition models that report PER ranging from 10 to 12.

ITZ Analysis of Cement Matrix According to the Type of Lightweight Aggregate Using EIS (EIS를 활용한 경량골재 종류별 시멘트 경화체의 계면특성 분석)

  • Kim, Ho-Jin;Jung, Yoong-Hoon;Bae, Je-Hyun;Park, Sun-Gyu
    • Journal of the Korean Recycled Construction Resources Institute
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    • v.8 no.4
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    • pp.498-505
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    • 2020
  • Aggregate occupies about 70-85% of the concrete volume and is an important factor in reducing the drying shrinkage of concrete. However, when constructing high-rise buildings, it acts as a problem due to the high load of natural aggregates. If the load becomes large during the construction of a high-rise building, creep may occur and the ground may be eroded. Material costs increase and there are financial problems. In order to reduce the load on concrete, we are working to reduce the weight of aggregates. However, artificial lightweight aggregates affect the interface between the aggregate and the paste due to its higher absorption rate and lower adhesion strength than natural aggregates, affecting the overall strength of concrete. Therefore, in this study, in order to grasp the interface between natural aggregate and lightweight aggregate by type, we adopted a method of measuring electrical resistance using an EIS measuring device, which is a non-destructive test, and lightweight bone. The change in the state of the interface was tested on the outside of the material through a blast furnace slag coating. As a result of the experiment, it was confirmed that the electric resistance was about 90% lower than that in the air-dried state through the electrolyte immersion, and the electric resistance differs depending on the type of aggregate and the presence or absence of coating. As a result of the experiment, the difference in compressive strength depending on the type of aggregate and the presence or absence of coating was shown, and the difference in impedance value and phase angle for each type of lightweight aggregate was shown.

Research Status of Satellite-based Evapotranspiration and Soil Moisture Estimations in South Korea (위성기반 증발산량 및 토양수분량 산정 국내 연구동향)

  • Choi, Ga-young;Cho, Younghyun
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1141-1180
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    • 2022
  • The application of satellite imageries has increased in the field of hydrology and water resources in recent years. However, challenges have been encountered on obtaining accurate evapotranspiration and soil moisture. Therefore, present researches have emphasized the necessity to obtain estimations of satellite-based evapotranspiration and soil moisture with related development researches. In this study, we presented the research status in Korea by investigating the current trends and methodologies for evapotranspiration and soil moisture. As a result of examining the detailed methodologies, we have ascertained that, in general, evapotranspiration is estimated using Energy balance models, such as Surface Energy Balance Algorithm for Land (SEBAL) and Mapping Evapotranspiration with Internalized Calibration (METRIC). In addition, Penman-Monteith and Priestley-Taylor equations are also used to estimate evapotranspiration. In the case of soil moisture, in general, active (AMSR-E, AMSR2, MIRAS, and SMAP) and passive (ASCAT and SAR)sensors are used for estimation. In terms of statistics, deep learning, as well as linear regression equations and artificial neural networks, are used for estimating these parameters. There were a number of research cases in which various indices were calculated using satellite-based data and applied to the characterization of drought. In some cases, hydrological cycle factors of evapotranspiration and soil moisture were calculated based on the Land Surface Model (LSM). Through this process, by comparing, reviewing, and presenting major detailed methodologies, we intend to use these references in related research, and lay the foundation for the advancement of researches on the calculation of satellite-based hydrological cycle data in the future.

Analysis of Development Characteristics of the Terra Nova Bay Polynya in East Antarctica by Using SAR and Optical Images (SAR와 광학 영상을 이용한 동남극 Terra Nova Bay 폴리냐의 발달 특성 분석)

  • Kim, Jinyeong;Kim, Sanghee;Han, Hyangsun
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1245-1255
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    • 2022
  • Terra Nova Bay polynya (TNBP) is a representative coastal polynya in East Antarctica, which is formed by strong katabatic winds. As the TNBP is one of the major sea ice factory in East Antarctica and has a great impact on regional ocean circulation and surrounding marine ecosystem, it is very important to analyze its area change and development characteristics. In this study, we detected the TNBP from synthetic aperture radar (SAR) and optical images obtained from April 2007 to April 2022 by visually analyzing the stripes caused by the Langmuir circulation effect and the boundary between the polynya and surrounding sea ice. Then, we analyzed the area change and development characteristics of the TNBP. The TNBP occurred frequently but in a small size during the Antarctic winter (April-July) when strong katabatic winds blow, whereas it developed in a large size in March and November when sea ice thickness is thin. The 12-hour mean wind speed before the satellite observations showed a correlation coefficient of 0.577 with the TNBP area. This represents that wind has a significant effect on the formation of TNBP, and that other environmental factors might also affect its development process. The direction of TNBP expansion was predominantly determined by the wind direction and was partially influenced by the local ocean current. The results of this study suggest that the influences of environmental factors related to wind, sea ice, ocean, and atmosphere should be analyzed in combination to identify the development characteristics of TNBP.

Effects of Vegetation on Pollutants and Carbon Absorption Capacity in LID Facilities (LID시설에서의 오염물질 및 탄소흡수능에 식생이 미치는 영향)

  • Hong, Jin;Kim, Yuhyeon;Gil, Kyungik
    • Journal of Wetlands Research
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    • v.24 no.2
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    • pp.115-122
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    • 2022
  • As the impermeable area of soil increases due to urbanization, the water circulation system of the city is deteriorating. The existing guidelines for low impact development (LID) facilities installed to solve these water problems or in previous studies, engineering aspects are more prominent than landscaping aspects. This study attempted to present an engineering and landscaping model for reducing pollutants by identifying the effects of vegetation on rainfall outflows and pollutant reduction in bioretention and the economic aspects of planting. Based on the results of artificial rainfall monitoring at Jeonju Seogok Park and the literature on vegetation rainfall runoff and pollutant reduction performance, the best vegetation for reducing pollution compared to cost was Lythrum salicaria L and Salix gracilistyla Miq. was the best vegetation for carbon storage. If you insist to design plants with only these two plantation, there is no choice but to take risks such as biodiversity. Herbaceous plants such as Lythrum salicaria L can be replaced by death of the plants or pests if considered planting various plants. The initial planting cost could expensive, but it is also necessary to mix and plant Salix gracilistyla Miq, which are woody plants that are advantageous in terms of maintenance, according to the surrounding environment and conditions. Based on the conclusions drawn in this study, it can be a reference material when considering the reduction of pollution by species and carbon storage of vegetation in LID facilities.

Analysis and Prediction Methods of Marine Accident Patterns related to Vessel Traffic using Long Short-Term Memory Networks (장단기 기억 신경망을 활용한 선박교통 해양사고 패턴 분석 및 예측)

  • Jang, Da-Un;Kim, Joo-Sung
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.5
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    • pp.780-790
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    • 2022
  • Quantitative risk levels must be presented by analyzing the causes and consequences of accidents and predicting the occurrence patterns of the accidents. For the analysis of marine accidents related to vessel traffic, research on the traffic such as collision risk analysis and navigational path finding has been mainly conducted. The analysis of the occurrence pattern of marine accidents has been presented according to the traditional statistical analysis. This study intends to present a marine accident prediction model using the statistics on marine accidents related to vessel traffic. Statistical data from 1998 to 2021, which can be accumulated by month and hourly data among the Korean domestic marine accidents, were converted into structured time series data. The predictive model was built using a long short-term memory network, which is a representative artificial intelligence model. As a result of verifying the performance of the proposed model through the validation data, the RMSEs were noted to be 52.5471 and 126.5893 in the initial neural network model, and as a result of the updated model with observed datasets, the RMSEs were improved to 31.3680 and 36.3967, respectively. Based on the proposed model, the occurrence pattern of marine accidents could be predicted by learning the features of various marine accidents. In further research, a quantitative presentation of the risk of marine accidents and the development of region-based hazard maps are required.