Solar energy, which is rapidly increasing in proportion, is being continuously developed and invested. As the installation of new and renewable energy policy green new deal and home solar panels increases, the supply of solar energy in Korea is gradually expanding, and research on accurate demand prediction of power generation is actively underway. In addition, the importance of solar radiation prediction was identified in that solar radiation prediction is acting as a factor that most influences power generation demand prediction. In addition, this study can confirm the biggest difference in that it attempted to predict solar radiation using medium-term forecast weather data not used in previous studies. In this paper, we combined the multi-linear regression model, KNN, random fores, and SVR model and the clustering technique, K-means, to predict solar radiation by hour, by calculating the probability density function for each cluster. Before using medium-term forecast data, mean absolute error (MAE) and root mean squared error (RMSE) were used as indicators to compare model prediction results. The data were converted into daily data according to the medium-term forecast data format from March 1, 2017 to February 28, 2022. As a result of comparing the predictive performance of the model, the method showed the best performance by predicting daily solar radiation with random forest, classifying dates with similar climate factors, and calculating the probability density function of solar radiation by cluster. In addition, when the prediction results were checked after fitting the model to the medium-term forecast data using this methodology, it was confirmed that the prediction error increased by date. This seems to be due to a prediction error in the mid-term forecast weather data. In future studies, among the weather factors that can be used in the mid-term forecast data, studies that add exogenous variables such as precipitation or apply time series clustering techniques should be conducted.
Due to water shortages caused by water pollution and climate change, total organic carbon (TOC) standards have been implemented for wastewater discharged from public sewage treatment facilities. Furthermore, there is a growing interest and body of research pertaining to the reuse of sewage treatment water as a secure alternative water resource. The membrane bio-reactor (MBR) method is commonly used for advanced wastewater treatment because it can remove organic and inorganic ions and it does not require or emit any chemicals. However, the MBR process uses a separation membrane (MF), which requires frequent film cleaning due to fouling caused by a high concentration of mixed liquor suspended solid (MLSS). In this study, process improvement and microbubble cleaning efficiency were evaluated to improve the differential pressure, water flow, and MF fouling, which are the biggest disadvantages of operating the MF. The existing MBR method was improved by installing a precipitation tank between the air tank and the MBR tank in which raw water was introduced. Microbubbles were injected into a separation membrane tank into which the supernatant water from the precipitation tank was introduced. The microbubble generator was operated with a 15 day on, 15 day off cycle for 5 months to collect discharged water samples (4L) and measure TOC. As the supernatant water from the precipitation tank flowed into the separation membrane tank, about 95% of the supernatant water MLSS was removed so the MF fouling from biological contamination was prevented. Due to the application of microbubbles to supernatant water from the precipitation tank, the differential pressure of the separation membrane tank decreased by 1.6 to 2.3 times and the water flow increased by 1.4 times. Applying microbubbles increased the TOC removal rate by more than 58%. This study showed that separately operating the air tank and the separation membrane tank can reduce fouling, and suggested that applying additional microbubbles could improve the differential pressure, water flow, and fouling to provide a more efficient advanced treatment method.
Seongyeop Jeong;Jongsu Yim;Sunjung Lee;Jungeun Song;Hyokeun Park;JungBin Lee;Kyujin Yeom;Yeongmo Son
Journal of Korean Society of Forest Science
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v.112
no.1
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pp.83-92
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2023
This study was established to investigate the site environment of mixed forests in Korea and to estimate the growth and yield of stands using national forest resources inventory data. The growth of mixed forests was derived by applying the Chapman-Richards model with diameter at breast height (DBH), height, and cross-sectional area at breast height (BA), and the yield of mixed forests was derived by applying stepwise regression analysis with factors such as cross-sectional area at breast height, site index (SI), age, and standing tree density per ha. Mixed forests were found to be growing in various locations. By climate zone, more than half of them were distributed in the temperate central region. By altitude, about 62% were distributed at 101-400 m. The fitness indexes (FI) for the growth model of mixed forests, which is the independent variable of stand age, were 0.32 for the DBH estimation, 0.22 for the height estimation, and 0.18 for the basal area at breast height estimation, which were somewhat low. However, considering the graph and residual between the estimated and measured values of the estimation equation, the use of this estimation model is not expected to cause any particular problems. The yield prediction model of mixed forests was derived as follows: Stand volume =-162.6859+6.3434 ∙ BA+9.9214 ∙ SI+0.7271 ∙ Age, which is a step- by-step input of basal area at breast height (BA), site index (SI), and age among several growth factors, and the determination coefficient (R2) of the equation was about 96%. Using our optimal growth and yield prediction model, a makeshift stand yield table was created. This table of mixed forests was also used to derive the rotation of the highest production in volume.
Forest biomass is used as a representative indicator of forest size, maturity, and productivity. Therefore, quantitative evaluation is important for management and harvest as well as the evaluation of ecosystem functions and services including CO2 absorption. The allometric equation is a widely used method for estimating the value of each component through the relative growth rate of plants. Recently, studies indicated that the relative growth of trees is changing because of the increased CO2 concentration in the atmosphere and the resulting climate change, raising the need to review the previously developed relative growth models and coefficients. In this study, the height-diameter at breast height (DBH) relationships of four major tree species in Korea [(Pinus densiflora (PD), Larix kaempferi (LK), Quercus variabilis (QV), and Quercus mongolica (QM)] were analyzed using the 5th-7th National Forest Inventory (NFI) data. Furthermore, these results were compared with the present yield table from the National Institute for Forest Science. This analysis revealed that the expected height for the same DBH increased as the NFI progressed. For example, in model analysis, the expected heights for PD, LK, QV, and QM for DBH of 25 cm were 12.48, 19.17, 14.47, and 13.19 m, respectively, in the 5th NFI data. In the 7th NFI data, these values were estimated as 13.61 (+9.1%), 21.58 (+12.7%), 15.76 (+8.9%), and 13.93 m (+5.6%), respectively. These results indicate that the major tree species in South Korean forests currently are more vigorous in height growth than in diameter growth when compared to the height-DBH development trends by tree species identified through past survey data.
Environment-friendly harvesting is practiced to maintain ecosystem, landscape, and forest protection functions. The present study was conducted at Simgok-ri, Sinbuk-myeon, Pocheon, Gyeonngi-do, where a 41-50-year-old Japanese larch forest was harvested in an environment-friendly manner from 2017 to 2019. The dynamics of organic matter in this forest were investigated at three years after the harvest. Specifically, organic matter content was measured on the forest floor and in overstory biomass, litterfall, and soil up to 30 cm in depth from June 2020 to January 2021. Owing to the harvest, the amount of overstory biomass of the Japanese larch stands decreased from 142.22 to 44.20 t ha-1. On the forest floor, the amount of organic matter was 32.87 t ha-1 in the control plots and 23.34 t ha-1 in the harvest plots. Annual litterfall was 4.43 t ha-1 yr-1 in the control plots and 1.16 t ha-1 yr-1 in the harvest plots. Soil bulk density in the B horizon was 0.97 g cm-3 in the control plots and 1.06 g cm-3 i n the harvest plots. Soil organic matter content was 11.5% in the control plots and 12.8% in the harvest plots. The total amount of soil organic matter did not differ significantly between the control plots (245.21 t ha-1) and harvest plots (263.92 t ha-1), although the amount of soil organic matter tended to be higher in the harvest plots. The total amount of organic matter in the forest was estimated to be 406.48 t ha-1 in the control plots and 338.21 t ha-1 in the harvest plots. In the harvest plots, the ratio of aboveground organic matter decreased to 13.1% and soil organic matter increased to 78.0%, indicating that the distribution of organic matter changed significantly in these plots. Overall, the carbon accumulated in aboveground biomass was substantially reduced by environment-friendly harvesting, whereas the soil carbon level increased, which played a role in mitigating the reduction of system carbon in the forest. These results highlight one possible resolution for forest management in terms of coping with climate change. However, given that only three years of environment-friendly harvesting data were analyzed, further research on the dynamics of organic matter and tree growth is needed.
This study aimed to check habitat distribution and analyze influencing factors by analyzing the mating calls of Auritibicen intermedius inhabiting limited locations in South Korea by applying bioacoustic detection techniques. The study sites were 20 protection areas nationwide. The mating call analysis period was 4 years from 2017 to 2021, excluding 2020. The bioacoustic recording system installed at each study site collected recordings of mating calls every day for 1 minute per hour. Climate data received from the Meteorological Agency, such as temperature, humidity, rainfall, cloudiness, and sunshine, were analyzed. The results of this study identified A. intermedius habitat only in four national parks in the highlands of Gangwon Province (Mt. Seorak, Mt. Odae, Mt. Chiak, and Mt. Taebak) out of 20 study sites. During the four years of study, the mating call period of A. intermedius was between August 5 and September 28, and the duration of the mating call was 31 to 52 days. The temperature analysis during the appearance period of A. intermedius showed that A. intermedius mainly produced mating calls at temperatures between 13.1℃ and 35.3℃, and the average temperature during the circadian cycle of mating calls (09:00 to 16:00) was 24.4 to 24.9℃. The analysis of the circadian cycle of mating calls at four study sites where A. intermedius appeared in 2019 showed that A. intermedius produced mating calls from 06:00 to 16:00 and that they peaked around 11:00 to 12:00. During the appearance period of A. intermedius, four species appeared in common: Hyalessa maculaticollis, Meimuna opalifera, Graptopsaltria nigrofuscata, and Suisha coreana. A logistic regression analysis confirmed that sunlight was the environmental factor affecting the mating call of A. intermedius. Regarding interspecific influence, it was confirmed that A. intermedius exchanged interspecific influence with 4 other common species (H. maculaticollis, M. opalifera, G. nigrofuscata, and S. coreana). The above results confirmed that A. intermedius habitats were limited in the highlands of Gangwon Province highlands in Korea and produced mating calls at a lower temperature compared to other species. These results can be used as basic data for future research on A. intermedius in Korea.
In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.
Compared to the EU, which legislates the Carbon Border Adjustment System (CBAM), the United States' carbon border adjustment policy movement is still relatively slow. Recently, however, a related bill has been proposed in the United States, and research institutes have been presenting research results on how to introduce an upstream carbon tax rather than an emission trading system and carry out carbon border adjustment based on it. Therefore, in this study, we looked at the economic and environmental effects of introducing this type of upstream carbon tax and carbon border adjustment in Korea. If an upstream carbon tax of KRW 30,000 per ton of CO2 is applied to the net supply of domestic fossil energy, the expected carbon tax revenue is approximately KRW 22.9961 trillion, equivalent to about 5.7% of the total revenue of the Korean government of KRW 402 trillion in 2019. In addition, the carbon dioxide content of the steel sector, calculated based on the energy supply and demand status of the steel sector, which emits the most greenhouse gas emissions in Korea and has a considerable amount of overseas exports, was 106.22 million tons of CO2. On the other hand, assuming that the upstream carbon tax of 30,000 won per ton of CO2 embodied is directly passed on to the production cost of the steel sector, the carbon tax burden in the steel sector is estimated to reach approximately KRW 3.1865 trillion. Even after deducting KRW 1.1599 trillion in export refunds estimated by using the share of exports of steel products, the net carbon tax burden on steel products for domestic demand amounts to KRW 2.0266 trillion, which is analyzed to act as a factor in increasing the price of steel products.
Lee, Seungmin;Baek, Seonuk;Lee, Junhak;Kim, Kyungtak;Kim, Soojun;Kim, Hung Soo
Journal of Korea Water Resources Association
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v.56
no.4
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pp.261-272
/
2023
In recent years, natural disasters such as heavy rainfall and typhoons have occurred more frequently, and their severity has increased due to climate change. The Korea Meteorological Administration (KMA) currently uses the same criteria for all regions in Korea for watch and warning based on the maximum cumulative rainfall with durations of 3-hour and 12-hour to reduce damage. However, KMA's criteria do not consider the regional characteristics of damages caused by heavy rainfall and typhoon events. In this regard, it is necessary to develop new criteria considering regional characteristics of damage and cumulative rainfalls in durations, establishing four stages: blue, yellow, orange, and red. A classification model, called DSCM (Disaster Severity Classification Model), for the four-stage disaster severity was developed using four machine learning models (Decision Tree, Support Vector Machine, Random Forest, and XGBoost). This study applied DSCM to local governments of Seoul, Incheon, and Gyeonggi Province province. To develop DSCM, we used data on rainfall, cumulative rainfall, maximum rainfalls for durations of 3-hour and 12-hour, and antecedent rainfall as independent variables, and a 4-class damage scale for heavy rain damage and typhoon damage for each local government as dependent variables. As a result, the Decision Tree model had the highest accuracy with an F1-Score of 0.56. We believe that this developed DSCM can help identify disaster risk at each stage and contribute to reducing damage through efficient disaster management for local governments based on specific events.
The 50th anniversary of the UNESCO World Heritage Convention was in 2022. In order to reflect on the present and future of the meaning of World Heritage, this paper examines the development and changes of the UNESCO World Heritage system. After promulgating the convention in 1972, the UNESCO World Heritage system prioritized the protection of heritage sites in the world that were at risk due to armed conflicts and natural disasters to bequeath heritage to the next generation. In addition, the UNESCO World Heritage's emphasis on Outstanding Universal Value represents the particular culture of human beings formed during a certain period of time, and acts as a significant source of soft power in public diplomacy. The UNESCO World Heritage might be perceived as a shared heritage that has not only become a channel to understand various national values, but also an effective medium to convey one of UNESCO's main principles, that is, peacebuilding. However, the UNESCO World Heritage is now at the center of conflicts of heritage interpretation between many stakeholders related to invisible wars, such as cultural wars, memory wars, and history wars as the social, political, and cultural contexts concerning World Heritage have dramatically shifted with the passing of time. Paying attention to such changing contexts, this paper seeks to understand the main developments in UNESCO World Heritage's discourse concerning changes to the World Heritage Operation Guidelines and heritage experts' meetings by dividing its 50-year history into five phases. Next, this paper analyzes the main shifts in keywords related to UNESCO World Heritage through UNESDOC, which is a platform on which all UNESCO publications are available. Finally, this paper discusses three main changes of UNESCO World Heritage: 1) changes in focus in World Heritage inscriptions, 2) changes in perception of World Heritage protection, and 3) changes of view on the role of the stakeholders in World Heritage. It suggests new emerging issues regarding heritage interpretation and ethics, climate change, and human rights.
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