• Proceedings of the Safety Management and Science Conference
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• 2005.11a
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• pp.423-426
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• 2005

The purpose of this research is to understand the role of safety climate in the safety management system. Based on the 121 responses from facilities got Occupational Health &Safety Assessment Series (OHSAS) 18000 certification, the results of statistic analysis show that there is significant relationship between safety climate, work attitudes and Organizational Citizenship Behaviors (OCB).

• Atmosphere
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• v.23 no.2
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• pp.237-243
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• 2013

A set of scripts for GrADS (Grid Analysis and Display System) and R was implemented to produce agricultural climate information using the future climate scenarios based on the Representative Concentration Pathways. The GrADS script was used to calculate agricultural climate indices including growing degree days and cooling degree days. The script generated agricultural climate maps of these indices, which are compatible with common Geographic Information System (GIS) applications. To perform a statistical analysis using the agricultural climate maps, a script for R, which is open source statistical software, was used. Because a large number of spatial climate data were produced, parallel processing packages such as SNOW, doSNOW, and foreach were used to perform a simple statistical analysis in the R script. The parallel script of R had speedup on workstations with multi-CPU cores.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.5
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• pp.69-80
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• 2015

The majority of projections of future climate come from Global Circulation Models (GCMs), which vary in the way they were modeled the climate system, and so it produces different projections about conceptualizing of the weather system. To implement climate change impact assessment, it is necessary to analyze trends of various GCMs and select appropriate GCM. In this study, climate data in 25 GCMs 41 outputs provided by Coupled Model Intercomparison Project Phase 5 (CMIP5) was downscaled at eight stations. From preliminary analysis of variations in projected temperature, precipitation and evapotranspiration, five GCM outputs were identified as candidates for the climate change impact analysis as they cover wide ranges of the variations. Also, GCM outputs are compared with trends of HadGCM3-RA, which are established by the Korean Meteorological Administration. From the results, it can contribute to select appropriate GCMs and to obtain reasonable results for the assessment of climate change.

• Journal of Climate Change Research
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• v.9 no.1
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• pp.75-80
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• 2018

The problem of water shortages and water related disasters caused by climate change has increased the seriousness of water problems and the importance of water treatment technology capable of securing clean water is expanding. In this study, we analyzed not only the water pollutant generated by the filtration system technology of various water treatment technologies but also the indirect greenhouse gas emissions generation, and analyzed the influence on the environment. The subjects of study are Fabric Filter, Reverse Osmosis System and Pressurized Microfiltration Device which are widely used for water treatment and we analyzed the impact on the environment using the Life Cycle Assessment (LCA) method using the electricity amount necessary for use, the water purification efficiency, the throughput per ton and the cost. The amount of greenhouse gas generated when the Pressurized Microfiltration Device operates for 1 year is $2.15E+04kg\;CO_2-eq$., Fabric Filter is $3.29E+04kg\;CO_2-eq$., and Reverse Osmosis System is $1.68E+05kg\;CO_2-eq$. As a result of analyzing the amount of greenhouse gas generated at the time of purifying 1 ton of the Pressurized Microfiltration Device and the conventional filtration system, the Pressurized Microfiltration Device was $20.5g\;CO_2-eq$., Fabric Filter was $34.7g\;CO_2-eq$., and Reverse Osmosis System was $191.7g\;CO_2-eq$. The amount of greenhouse gas generated was calculated to be 41.0% less than that of the Fabric Filter by the Pressurized Microfiltration Device and 89.3% less than the Reverse Osmosis System. From the viewpoint of climate change, it is necessary to select a filtration system that takes climate change into account, not from the viewpoint of water quality removal efficiency and economic efficiency according to future water treatment applications, and it is necessary to select a water treatment filtration system more researches and improvements will be made for.

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.3
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• pp.190-198
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• 2023

This study was conducted to calculate the damage of Italian ryegrass (IRG) by abnormal climate using machine learning and present the damage through the map. The IRG data collected 1,384. The climate data was collected from the Korea Meteorological Administration Meteorological data open portal.The machine learning model called xDeepFM was used to detect IRG damage. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The calculation of damage was the difference between the Dry matter yield (DMY)_normal and DMY_abnormal. The normal climate was set as the 40-year of climate data according to the year of IRG data (1986~2020). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization (WMO) standard. The DMY_normal was ranged from 5,678 to 15,188 kg/ha. The damage of IRG differed according to region and level of abnormal climate with abnormal temperature, precipitation, and wind speed from -1,380 to 1,176, -3 to 2,465, and -830 to 962 kg/ha, respectively. The maximum damage was 1,176 kg/ha when the abnormal temperature was -2 level (+1.04℃), 2,465 kg/ha when the abnormal precipitation was all level and 962 kg/ha when the abnormal wind speed was -2 level (+1.60 ㎧). The damage calculated through the WMO method was presented as an map using QGIS. There was some blank area because there was no climate data. In order to calculate the damage of blank area, it would be possible to use the automatic weather system (AWS), which provides data from more sites than the automated synoptic observing system (ASOS).

• Proceedings of KOSOMES biannual meeting
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• 2017.04a
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• pp.212-212
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• 2017

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.222-222
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• 2015

Vietnam is one of the most vulnarable countries affected by climate change and sea level rise. One of the consequences of climate change and sea level rise is the increase of salinity intrusion into the rivers which is challenging to irrigation systems in coastal areas. This indicates the necessary to study the ability of taking water through sluice gates of irrigation systems in coastal zones, especially in the dry season with the effects of climate change and sea level rise in the future. In this paper, Nam Thai Binh irrigation system is selected as a case study. The irrigation system is one of 22 biggest irrigation systems of the Red River delta in Vietnam located in coastal region. The computed duration is selected in dry season to irrigate for Winter-Spring crops. The irrigation water for the study area is taken from different sluice gates along the Red River and the Tra Ly River. In this paper, MIKE-11 model was applied to assess the ability of taking water for irrigation of the study area in current situation and in the context of climate change and sea level rise senario in 2050 (under the medium emissions scenario (B2) published by the Ministry of Natural Resources and Environment of Vietnam published in 2012) with different condition of water availability. The operation of the gates depends on the water levels and sanility conditions. The sanility and water level at different water intake gates of Nam Thai Binh irrigation system were simulated with different senarios with and without climate change and sea level rise. The result shows that, under climate change and sea water level rise, some gates can take more water but some can not take water because of salinity excess and the total water taking from the different gates along the rivers decrease while the water demand is increase. The study indicates the necessary to study quantitatively some recommended solutions in the study area particularly and in coastal region generally in Vietnam to ensure water demand for irrigation and other purposes in the context of climate change and sea level rise in the future.

• Atmosphere
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• v.17 no.4
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• pp.483-492
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• 2007

The objective of this study is to describe scientific progresses in understanding of climate change in the Intergovernmental Panel on Climate Change (IPCC) assessment reports, contributed by Working group I. Since 1988, IPCC's four assessment reports showed significant improvements in understanding of observed climate change, drivers of climate change, detection and attribution of climate change, climate models, and future projection. The results are based on large amounts of observation data, sophisticated analyses of data, improvements of climate models and the simulations. While the First Assessment Report (FAR) in 1990 reported that a detectable anthropogenic influence on climate has little observational evidence, the Fourth Assessment Report (AR4) reported that warming of the climate system is unequivocal and is very likely due to human influences. It is also noted that anthropogenic warming and sea level rise would continue for centuries due to the time scales associated with climate processes and feedbacks, even if greenhouse gas were to be stabilized.

• Atmosphere
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• v.23 no.3
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• pp.347-356
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• 2013

The climate projection with a high spatial resolution is required for the studies on regional climate changes. The Korea Meteorological Administration (KMA) has provided downscaled RCP (Representative Concentration Pathway) scenarios over Korea with 1 km spatial resolution. If there are additional climate projections produced by dynamically downscale, the quality of impacts and vulnerability assessments of Korea would be improved with uncertainty information. This technical note intends to instruct the methods to downscale the climate projections dynamically from the Community Earth System Model (CESM) to the Weather Research and Forecast (WRF) model. In particular, here we focus on the instruction to utilize CAM2WRF, a sub-program to link output of CESM to initial and boundary condition of WRF at Linux platform. We also provide the example of the dynamically downscaled results over Korean Peninsula with 50 km spatial resolution for August, 2020. This instruction can be helpful to utilize global scale climate scenarios for studying regional climate change over Korean peninsula with further validation and uncertainty/bias analysis.

• Journal of Climate Change Research
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• v.7 no.1
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• pp.69-75
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• 2016

Recently, many countries all over the world have been suffered from disaster caused by climate change. Especially in case of developed countries, the disaster is concentrated in the industry sector. In this research, we analyzed industrial vulnerable homogeneous hotspot for the climate change using spatial autocorrelation analysis on the south Korea. Homogeneous hot spot areas through autocorrelation analysis indicate the spatial pattern of areas interacted each other. Industry sector have responsibility of green house gas emissions, and should adapt to the climate change caused by greenhouse gas already released. So, we integrated the areas sensitive to mitigation option with the areas hardly adapt to climate change because of vulnerable infrastructure. We expected that the result of this research could contribute to the decision-making system of climate change polices.