Local governments play a critical role in achieving carbon neutrality and reducing national carbon emissions. To manage carbon emissions effectively, it is essential for local governments to analyze regional carbon emissions. In this study, we developed a model for estimating carbon emissions based on land use and analyzed regional characteristics of carbon emissions to suggest policies for achieving carbon neutrality at the regional level. Our model for calculating carbon emissions is based on an analysis of the activities that contribute to carbon emissions for each land use, and we established the spatial scope of carbon emission calculation. We applied this model to the cities and counties in Gyeongsangnam province, calculating carbon emissions from settlement and agricultural production activities and comparing regional characteristics of carbon emissions. Our analysis showed that areas with larger populations generally produced higher emissions in all categories, but we observed different results in terms of unit emissions, emissions divided by area, population, and household. Based on these findings, we propose policies such as increasing the generation of new and renewable energy using public institutions, promoting the conversion to cleaner cooking and heating energy sources, and encouraging the adoption of eco-friendly automobiles on roads. We believe that our analysis of the spatial and regional characteristics of carbon emissions can help local governments establish effective policies for reducing carbon emissions in their regions.
Evaluation of Maximum Dry Unit Weight Prediction Model Using Deep Neural Network Based on Particle Size Analysis
The compaction properties of the soil change depending on the physical properties, and are also affected by crushing of the particles. Since the particle size distribution of soil affects the engineering properties of the soil, it is necessary to analyze the material properties to understand the compaction characteristics. In this study, the size of each sieve was classified into four in the particle size analysis as a material property, and the compaction characteristics were evaluated by multiple regression and maximum dry unit weight. As a result of maximum dry unit weight prediction, multiple regression analysis showed R2 of 0.70 or more, and DNN analysis showed R2 of 0.80 or more. The reliability of the prediction result analyzed by DNN was evaluated higher than that of multiple regression, and the analysis result of DNN-T showed improved prediction results by 1.87% than DNN. The prediction of maximum dry unit weight using particle size distribution seems to be applied to evaluate the compacting state by identifying the material characteristics of roads and embankments. In addition, the particle size distribution can be used as a parameter for predicting maximum dry unit weight, and it is expected to be of great help in terms of time and cost of applying it to the compaction state evaluation.
A Study to Evaluate and Remedy Universal Soil Loss Equation Application for Watersheds and Development Projects
우원희 Woo Won Hee , 채민서 Chae Min Suh , 박종윤 Park Jong-yoon , 이한용 Lee Hanyong , 박윤식 Park Youn Shik
Universal Soil Loss Equation (USLE) is suggested and employed in the policy to conserve soil resources and to manage the impact of development, since soil loss is very essential to nonpoint source pollution management. The equation requires only five factors to estimate average annual potential soil loss, USLE is simplicity provides benefits in use of the equation. However, it is also limitation of the model, since the estimated results are very sensitive to the five factors. There is a need to examine the application procedures. Three approaches to estimate potential soil loss were examined, In the first approach, all factors were prepared with raster data, soil loss were computed for each cell, and sum of all cell values was determined as soil loss for the watersheds. In the second approach, the mean values for each factor were defined as representing USLE factors, and then the five factors were multiplied to determine soil loss for the watersheds. The third approach was same as the second approach, except that the Vegetative and Mechanical measure was used instead of the Cover and management factor and Support practice factor. The approaches were applied in 38 watersheds, they displayed significant difference, moreover no trends were detected for the soil loss at watersheds with the approaches. Therefore, it was concluded that there is a need to be developed and provided a typical guideline or public systems so that soil loss estimations have consistency with the users.
Analysis of Residents’ Perception Changes on Regional Capacity Empowerment Project in the Village - Comparison of Changes in the Perception of Residents in Rural and Fishing Village -
양민호 Yang Minho , 김기성 Kim Kisung , 고진영 Koh Jinyoung , 김명일 Kim Myungil
Analysis of Residents’ Perception Changes on Regional Capacity Empowerment Project in the Village - Comparison of Changes in the Perception of Residents in Rural and Fishing Village -
양민호 Yang Minho , 김기성 Kim Kisung , 고진영 Koh Jinyoung , 김명일 Kim Myungil
The Korean government has promoted rural development projects aimed at bridging the gap between cities and rural areas. However, prior research in assessing available rural projects was mainly focused on only part of the agricultural area, evaluation of project types and improvement measures, analysis of operating management policies, and measuring levels of importance by sub-project categories, and yet the study found a little study on residents’ satisfaction of the project who is the direct and fundamental beneficiary. In particular, comparative studies on rural and fishing village residents were insufficient. Thus, the present study chose village residents from Chodo-ri where the Ministry of Oceans and Fisheries held the Customized Capacity Empowerment Project from the Gangwon Fishing Village Specialized Support Center and Songgye-ri where was the project area for rural revitalization project to navigate changes on both perception and satisfaction of the village residents before and after the education.
Flash Drought Onset and Development Mechanisms Using Flash Drought Intensity Index (FDII) Based on Satellite-Based Soil Moisture
이희진 Lee Hee-jin , 남원호 Nam Won-ho , 서찬양 Sur Chanyang , Jason A. Otkin , Yafang Zhong , Mark D. Svoboda
A flash drought is a rapid-onset drought that develops over a short period of time as weather and environmental factors change rapidly, unlike general droughts, due to meteorological abnormalities. Abnormally high evapotranspiration rates and rapid declines in soil moisture increase vegetation stress. In addition, crop yields may decrease due to flash droughts during crop growth and may damage agricultural and economic ecosystems. In this study, Flash Drought Intensity Index (FDII) based on soil moisture data from Gravity Recovery Climate Experiment (GRACE) was used to analyze flash drought. FDII, which is calculated using soil moisture percentile, is expressed by multiplying two factors: the rate of intensification and the drought severity. FDII was developed for domestic flash drought events from 2014 to 2018. The flash drought that occurred in 2018, Chungcheongbuk-do showed the highest FDII. FDII was higher in heat wave flash drought than in precipitation deficit flash drought. The results of this study show that FDII is reliable flash drought analysis tool and can be applied to quantitatively analyze the characteristics of flash drought in South Korea.
Study on the Methodology for Generating Future Precipitation Data by the Rural Water District Using Grid-Based National Standard Scenario
Representative meteorological data of the rural water district, which is the spatial unit of the study, was produced using the grid-based national standard RCP scenario rainfall data provided by the Korea Meteorological Administration. The retrospective reproducibility of the climate model scenario data was analyzed, and the change in climate characteristics in the water district unit for the future period was presented. Finally the data characteristics and differences of each meteorological element according to various spatial resolution conversion and post-processing methods were examined. As a main result, overall, the distribution of average precipitation and R95p of the grid data, has reasonable reproducibility compared to the ASOS observation, but the maximum daily rainfall tends to be distributed low nationwide. The number of rainfall days tends to be higher than the station-based observation, and this is because the grid data is generally calculated using the area average concept of representative rainfall data for each grid. In addition, in the case of coastal regions, there is a problem that administrative districts of islands and rural water districts do not match. and In the case of water districts that include mountainous areas, such as Jeju, there was a large difference in the results depending on whether or not high rainfall in the mountainous areas was reflected.
The results of this study are expected to be used as foundation for selecting data processing methods when constructing future meteorological data for rural water districts for future agricutural water management plans and climate change vulnerability assessments.
