• 제목/요약/키워드: Capacity estimation

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An Introduction of Korean Soil Information System (한국 토양정보시스템 소개)

  • Hong, S. Young;Zhang, Yong-Seon;Hyun, Byung-Keun;Sonn, Yeon-Kyu;Kim, Yi-Hyun;Jung, Sug-Jae;Park, Chan-Won;Song, Kwan-Cheol;Jang, Byoung-Choon;Choe, Eun-Young;Lee, Ye-Jin;Ha, Sang-Keun;Kim, Myung-Suk;Lee, Jong-Sik;Jung, Goo-Bok;Ko, Byong-Gu;Kim, Gun-Yeob
    • Korean Journal of Soil Science and Fertilizer
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    • 제42권1호
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    • pp.21-28
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    • 2009
  • Detailed information on soil characteristics is of great importance for the use and conservation of soil resources that are essential for human welfare and ecosystem sustainability. This paper introduces soil inventory of Korea focusing on national soil database establishment, information systems, use, and future direction for natural resources management. Different scales of soil maps surveyed and soil test data collected by RDA (Rural Development Administration) were computerized to construct digital soil maps and database. Soil chemical properties and heavy metal concentrations in agricultural soils including vulnerable agricultural soils were investigated regularly at fixed sampling points. Internet-based information systems for soil and agro-environmental resources were developed based on 'National Soil Survey Projects' for managing soil resources and for providing soil information to the public, and 'Agroenvironmental Change Monitoring Project' to monitor spatial and temporal changes of agricultural environment will be opened soon. Soils data has a great potential of further application in estimation of soil carbon storage, water capacity, and soil loss. Digital mapping of soil and environment using state-of-the-art and emerging technologies with a pedometrics concept will lead to future direction.

Estimation of carbon storage in reclaimed coal mines: Focused on Betula platyphylla, Pinus koraiensis and Pinus spp. plantations (폐탄광 산림복구지의 수종별 탄소 저장량 추정: 자작나무, 잣나무, 소나무류 식재지를 중심으로)

  • Kim, Gwangeun;Kim, Seongjun;Kim, Hyun-Jun;Chang, Hanna;Kim, Hyungsub;Park, Yong-Ha;Son, Yowhan
    • Korean Journal of Environmental Biology
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    • 제38권4호
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    • pp.733-743
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    • 2020
  • We estimated the carbon storage of coal mines reclaimed using Betula platyphylla (BP), Pinus koraiensis (PK), and Pinus spp. (PS, Pinus densiflora, Pinus rigida, and Pinus thunbergii). The carbon storage of tree biomass (TB), forest floor(FF), mineral soil (MS), and the total forest were quantified. Reclaimed sites were located in Gangwon-do, Gyeongsangbuk-do, and Jeollanam-do; reclamation was conducted at various times in each region. The carbon storage (ton C ha-1) in FF (BP: 3.31±0.59, PK: 3.60±0.93, PS: 4.65±0.92), MS (BP: 28.62±2.86, PK: 22.26±5.72, PS: 19.95±3.90), and the total forest(BP: 54.81±7.22, PK: 47.29±8.97, PS: 45.50±6.31) were lower than that of natural forests (NF). The carbon storage in TB was lower in BP (22.57±6.18) compared to NF, while those in PK(21.17±8.76) and PS (20.80±6.40) were higher than in NF. While there were no significant differences in the carbon storage of TB, FF, and the total forest among tree species, results from MS showed a significant difference among species. TB and the total forest carbon storages in all sites increased after reclamation. Soil pH and cation exchange capacity values in BP and PS were lower than in NF. Amounts of labile carbon, available phosphate, and microbial biomass carbon in reclaimed sites were less than half of NF. There are a number of methods that could increase the reclamation efficiency. Applications of lime or organic fertilizers, as well as tillage operations, may improve soil properties in reclaimed coal mines. Additionally, pruning and thinning would increase tree growth thereby increasing carbon storage.

Evaluating Global Container Ports' Performance Considering the Port Calls' Attractiveness (기항 매력도를 고려한 세계 컨테이너 항만의 성과 평가)

  • Park, Byungin
    • Journal of Korea Port Economic Association
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    • 제38권3호
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    • pp.105-131
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    • 2022
  • Even after the improvement in 2019, UNCTAD's Liner Shipping Connectivity Index (LSCI), which evaluates the performance of the global container port market, has limited use. In particular, since the liner shipping connectivity index evaluates the performance based only on the distance of the relationship, the performance index combining the port attractiveness of calling would be more efficient. This study used the modified Huff model, the hub-authority algorithm and the eigenvector centrality of social network analysis, and correlation analysis for 2007, 2017, and 2019 data of Ocean-Commerce, Japan. The findings are as follows: Firstly, the port attractiveness of calling and the overall performance of the port did not always match. However, according to the analysis of the attractiveness of a port calling, Busan remained within the top 10. Still, the attractiveness among other Korean ports improved slowly from the low level during the study period. Secondly, Global container ports are generally specialized for long-term specialized inbound and outbound ports by the route and grow while maintaining professionalism throughout the entire period. The Korean ports continue to change roles from analysis period to period. Lastly, the volume of cargo by period and the extended port connectivity index (EPCI) presented in this study showed a correlation from 0.77 to 0.85. Even though the Atlantic data is excluded from the analysis and the ship's operable capacity is used instead of the port throughput volume, it shows a high correlation. The study result would help evaluate and analyze global ports. According to the study, Korean ports need a long-term strategy to improve performance while maintaining professionalism. In order to maintain and develop the port's desirable role, it is necessary to utilize cooperation and partnerships with the complimentary port and attract shipping companies' services calling to the complementary port. Although this study carried out a complex analysis using a lot of data and methodologies for an extended period, it is necessary to conduct a study covering ports around the world, a long-term panel analysis, and a scientific parameter estimation study of the attractiveness analysis.

Analysis of Greenhouse Thermal Environment by Model Simulation (시뮬레이션 모형에 의한 온실의 열환경 분석)

  • 서원명;윤용철
    • Journal of Bio-Environment Control
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    • 제5권2호
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    • pp.215-235
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    • 1996
  • The thermal analysis by mathematical model simulation makes it possible to reasonably predict heating and/or cooling requirements of certain greenhouses located under various geographical and climatic environment. It is another advantages of model simulation technique to be able to make it possible to select appropriate heating system, to set up energy utilization strategy, to schedule seasonal crop pattern, as well as to determine new greenhouse ranges. In this study, the control pattern for greenhouse microclimate is categorized as cooling and heating. Dynamic model was adopted to simulate heating requirements and/or energy conservation effectiveness such as energy saving by night-time thermal curtain, estimation of Heating Degree-Hours(HDH), long time prediction of greenhouse thermal behavior, etc. On the other hand, the cooling effects of ventilation, shading, and pad ||||&|||| fan system were partly analyzed by static model. By the experimental work with small size model greenhouse of 1.2m$\times$2.4m, it was found that cooling the greenhouse by spraying cold water directly on greenhouse cover surface or by recirculating cold water through heat exchangers would be effective in greenhouse summer cooling. The mathematical model developed for greenhouse model simulation is highly applicable because it can reflects various climatic factors like temperature, humidity, beam and diffuse solar radiation, wind velocity, etc. This model was closely verified by various weather data obtained through long period greenhouse experiment. Most of the materials relating with greenhouse heating or cooling components were obtained from model greenhouse simulated mathematically by using typical year(1987) data of Jinju Gyeongnam. But some of the materials relating with greenhouse cooling was obtained by performing model experiments which include analyzing cooling effect of water sprayed directly on greenhouse roof surface. The results are summarized as follows : 1. The heating requirements of model greenhouse were highly related with the minimum temperature set for given greenhouse. The setting temperature at night-time is much more influential on heating energy requirement than that at day-time. Therefore It is highly recommended that night- time setting temperature should be carefully determined and controlled. 2. The HDH data obtained by conventional method were estimated on the basis of considerably long term average weather temperature together with the standard base temperature(usually 18.3$^{\circ}C$). This kind of data can merely be used as a relative comparison criteria about heating load, but is not applicable in the calculation of greenhouse heating requirements because of the limited consideration of climatic factors and inappropriate base temperature. By comparing the HDM data with the results of simulation, it is found that the heating system design by HDH data will probably overshoot the actual heating requirement. 3. The energy saving effect of night-time thermal curtain as well as estimated heating requirement is found to be sensitively related with weather condition: Thermal curtain adopted for simulation showed high effectiveness in energy saving which amounts to more than 50% of annual heating requirement. 4. The ventilation performances doting warm seasons are mainly influenced by air exchange rate even though there are some variations depending on greenhouse structural difference, weather and cropping conditions. For air exchanges above 1 volume per minute, the reduction rate of temperature rise on both types of considered greenhouse becomes modest with the additional increase of ventilation capacity. Therefore the desirable ventilation capacity is assumed to be 1 air change per minute, which is the recommended ventilation rate in common greenhouse. 5. In glass covered greenhouse with full production, under clear weather of 50% RH, and continuous 1 air change per minute, the temperature drop in 50% shaded greenhouse and pad & fan systemed greenhouse is 2.6$^{\circ}C$ and.6.1$^{\circ}C$ respectively. The temperature in control greenhouse under continuous air change at this time was 36.6$^{\circ}C$ which was 5.3$^{\circ}C$ above ambient temperature. As a result the greenhouse temperature can be maintained 3$^{\circ}C$ below ambient temperature. But when RH is 80%, it was impossible to drop greenhouse temperature below ambient temperature because possible temperature reduction by pad ||||&|||| fan system at this time is not more than 2.4$^{\circ}C$. 6. During 3 months of hot summer season if the greenhouse is assumed to be cooled only when greenhouse temperature rise above 27$^{\circ}C$, the relationship between RH of ambient air and greenhouse temperature drop($\Delta$T) was formulated as follows : $\Delta$T= -0.077RH+7.7 7. Time dependent cooling effects performed by operation of each or combination of ventilation, 50% shading, pad & fan of 80% efficiency, were continuously predicted for one typical summer day long. When the greenhouse was cooled only by 1 air change per minute, greenhouse air temperature was 5$^{\circ}C$ above outdoor temperature. Either method alone can not drop greenhouse air temperature below outdoor temperature even under the fully cropped situations. But when both systems were operated together, greenhouse air temperature can be controlled to about 2.0-2.3$^{\circ}C$ below ambient temperature. 8. When the cool water of 6.5-8.5$^{\circ}C$ was sprayed on greenhouse roof surface with the water flow rate of 1.3 liter/min per unit greenhouse floor area, greenhouse air temperature could be dropped down to 16.5-18.$0^{\circ}C$, whlch is about 1$0^{\circ}C$ below the ambient temperature of 26.5-28.$0^{\circ}C$ at that time. The most important thing in cooling greenhouse air effectively with water spray may be obtaining plenty of cool water source like ground water itself or cold water produced by heat-pump. Future work is focused on not only analyzing the feasibility of heat pump operation but also finding the relationships between greenhouse air temperature(T$_{g}$ ), spraying water temperature(T$_{w}$ ), water flow rate(Q), and ambient temperature(T$_{o}$).

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