• 한국대기환경학회지
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• 제30권2호
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• pp.110-118
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• 2014

This paper addresses the fugitive emission factors of Reefer Container at use-phase and disposal-phase. The residual quantities and operation time of thirty nine Container were weighed, using a commercial recover of refrigerants to determine the emission factors at the use-phase. The emission factor at the disposal-phase, refrigerant is accomplished has not recycled, the residual rate was assumed that the emission factor. The average residual rate of thirty nine Container is determined to be $70.8{\pm}4.0%$. The emission factor at the use-phase is estimated to be $4.9{\pm}0.9%/yr$ in the case of using average age of 8.1 years and the average residual rate determined here. We estimate 162.7 g/yr for the average emission quantity of refrigerant per operating Container, while 2038.1 g for that per waste Container. Since the chemical compositions of refrigerant of waste Container were the same as those of new refrigerant, it is expected that the refrigerant recovered from waste Container can be reused for refrigerant.

• 대한간호학회지
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• 제52권2호
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• pp.173-186
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• 2022

Purpose: Climate change has various negative effects on human health, which has resulted in increased burden on the health care system. Nurses contribute significantly to assessing climate-related health risks and creating a healthy environment. This study aimed to evaluate the reliability and validity of the Korean version of the Climate, Health, and Nursing Tool (K-CHANT) to measure nurses' awareness, motivation, concern, and behaviors at work and at home regarding climate change and health. Methods: The 22 items of English CHANT were translated into Korean with forward-backward translation techniques. Internal consistency reliability, test-retest reliability, and construct validity using confirmatory factor analysis were performed using SPSS WIN (25.0) and AMOS (26.0). Survey data were collected from 220 master's, doctoral, and post-doctoral nursing students. Results: The K-CHANT consists of 20 items across 5 domains. Two items of the original CHANT were excluded because of low content validity index and standardized regression weights. The internal consistency reliability of the K-CHANT, assessed by Cronbach's α was .81, with an intraclass correlation coefficient of .66~.90. The five subscales model was validated by confirmatory factor analysis (SRMR < .08, RMSEA < .08, AGFI > .70, CFI > .70). Conclusion: The K-CHANT has satisfactory construct validity and reliability to measure nurses' awareness, motivation, concern, and behaviors at work and at home regarding climate change and health. Future research should examine nurses' perceptions and behaviors related to the health effects of climate change and develop an action plan to improve it.

• 한국경영과학회지
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• 제41권4호
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• pp.75-93
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• 2016

This study aims at analyzing the relationship between team characteristic and innovation performance. The mediating effect of creative climate on the team characteristic and innovation performance is also measured. Based upon literature review, individual creative characteristics, team diversity, team cohesion, task characteristics are presented as antecedents of team characteristic. Creative climate affects the creative behavior and innovative performance. Creative climate is measured as the Team Climate Inventory (TCI) proposed by Anderson & West (1998) including goal, participative-autonomy and innovative-support. Data were collected from 186 survey responses (54 Teams) out of total 462 (69 teams) from the R&D department of a major ICT firm in Korea. Empirical results show the diversity, cohesion, job characteristic, individual creative characteristic have a positive effect on the creative climate and innovation performance. The participative-autonomy climate factor appears to mediate the relationship between team characteristic (diversity, cohesion, job and individual characteristics) and innovation performance. However, the mediating effects of goals and innovative-support factors were not significant statistically. It was confirmed that the organization can contribute to improve the team innovation performance by facilitating a autonomy and participative climate as well as fostering the team characteristic.

• 한국기후변화학회지
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• 제5권4호
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• pp.349-357
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• 2014

Greenhouse gases (GHGs) from agricultural sector were categorized in a guideline book from Intergovernmental Panel on Climate Change (IPCC) as methane from rice paddy fields and nitrous oxide from agricultural soils. In general, GHG emissions were calculated by multiplying the activity data by emission factor. Tier 1 methodology uses IPCC default factors and Tier 2 uses country specific emission factors (CS). The CS and Scaling factors (SF) had been developed by NAAS (National Academy of Agricultural Science) projects from 2009 to 2012 to estimate how the advanced emissions. The purpose of this study was to compare GHG emissions calculated from IPCC default factors and NAAS CS and SF of agricultural sector in Korea. Methane emissions using CS and SF in rice paddy field was about 79% higher than those using IPCC default factors. In the agricultural soils, nitrous oxide emissions using CS from the 5 crops were about 40% lower than those using IPCC default. Except those 5 crops, approximately up to 52% lower emissions were calculated using CS compared to those using IPCC default factors. The total GHG emissions using CS and SF were about 33% higher than those using Tier 1 method by IPCC default factors.

• 한국학교보건학회지
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• 제28권2호
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• pp.47-55
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• 2015

Purpose: This study aims to explore whether health promoting schools (HPS) affect school climate. The study is the first research that investigates the effects of Korean HPS on school climate. Methods: The study examined 2,791 students who participated in a study on HPS effectiveness conducted by MOE (The Ministry of Education) in 2014. Data were analyzed through descriptive statistics, factor analysis, and ttest using SPSS/WINdow 22.0. Results: There was a significant difference between the HPS and the comparison schools in terms of three school climate criteria ' School atmosphere', 'Teacherstudent relationship', and 'Peer relationship'. Conclusion: The study's result that Korean HPS has positive effects on school climate indicates a need to expand HPS in Korea's education sector.

• 한국기후변화학회지
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• 제8권4호
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• pp.347-355
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• 2017

Methane and nitrous oxide are main greenhouse gases from agricultural system and their global warming potential are 25 and 258 times stronger than that of $CO_2$, respectively. In 2016, the emission was $21,290Gg\;tone\;CO_2-eq$. which was emitted from agriculture sector and about 3.1% of total GHG emission of Korea. Those guidelines that were published by IPCC have methodology for GHGs emission calculation as well as emission factor and so on. For recent 5 years, GHGs emissions in Korea have calculated by MRV which has been improved every year based on IPCC guidelines. Analysis as estimating method improvement showed that the methane emissions from rice cultivation were the lowest on 2012 methodology, and the highest on 2014 methodology. On the other hand, the emissions of agricultural soils were the lowest on 2015 methodology and the highest on 2012 methodology. Total emissions from agriculture sector were the lowest on 2015 methodology and the highest on 2012 methodology. Compared with 2016 methodology, the GHGs emitted as few as $-1,865Gg\;tone\;CO_2-eq$ and as many as $2,717Gg\;tone\;CO_2-eq$. GHGs emissions can vary greatly, depending on how to use the emission factor and activity data. Therefore, it need constantly a detailed analysis for methodology and GHGs emission in the future.

• Journal of Ecology and Environment
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• 제35권3호
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• pp.243-249
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• 2012

Biomass expansion factors, which convert timber volume (or dry weight) to biomass, are used for estimating the forest biomass and accounting for the carbon budget at a regional or national scale. We estimated the biomass conversion and expansion factors (BCEF), biomass expansion factors (BEF), root to shoot ratio (R), and ecosystem biomass expansion factor (EBEF) for Quercus mongolica Fisch. and Quercus variabilis Bl. forests based on publications in Korea. The mean BCEF, BEF, and R for Q. mongolica was 1.0383 Mg/$m^3$ (N = 27; standard deviation [SD], 0.5515), 1.3572 (N = 27; SD, 0.1355), and 0.2017 (N = 32; SD, 0.0447), respectively. The mean BCEF, BEF, and R for Q. variabilis was 0.7164 Mg/$m^3$ (N = 17; SD, 0.3232), 1.2464 (N = 17; SD, 0.0823), and 0.1660 (N = 8; SD, 0.0632), respectively. The mean EBEF, as a simple method for estimating the ground vegetation biomass, was 1.0216 (N = 7; SD, 0.0232) for Q. mongolica forest ecosystems, and 1.0496 (N = 8; SD, 0.0725) for Q. variabilis forest ecosystems. The biomass expansion factor values in this study may be better estimates of forest biomass in Q. mongolica or Q. variabilis forests of Korea compared with the default values given by the Intergovernmental Panel on Climate Change (IPCC).

• 한국물환경학회지
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• 제31권3호
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• pp.241-252
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• 2015

Runoff behaviors by five bias correction methods were analyzed, which were Change Factor methods using past observed and estimated data by the estimation scenario with average annual calibration factor (CF_Y) or with average monthly calibration factor (CF_M), Quantile Mapping methods using past observed and estimated data considering cumulative distribution function for entire estimated data period (QM_E) or for dry and rainy season (QM_P), and Integrated method of CF_M+QM_E(CQ). The peak flow by CF_M and QM_P were twice as large as the measured peak flow, it was concluded that QM_P method has large uncertainty in monthly runoff estimation since the maximum precipitation by QM_P provided much difference to the other methods. The CQ method provided the precipitation amount, distribution, and frequency of the smallest differences to the observed data, compared to the other four methods. And the CQ method provided the rainfall-runoff behavior corresponding to the carbon dioxide emission scenario of SRES A1B. Climate change scenario with bias correction still contained uncertainty in accurate climate data generation. Therefore it is required to consider the trend of observed precipitation and the characteristics of bias correction methods so that the generated precipitation can be used properly in water resource management plan establishment.

• 한국기후변화학회지
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• 제7권2호
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• pp.193-203
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• 2016

The importance of forecasting agricultural production is receiving attention while climate change is accelerating. This study suggested three types of crop yield forecasting model for major vegetable crops by using downscaled meteorological information of main production area on farmland level, which identified as limitation from previous studies. First, this study conducted correlation analysis with seven types of farm level downscaled meteorological informations and reported crop yield of main production area. After, we selected three types of meteorological factors which showed the highest relation with each crop species and regions. Parameters were deducted from meterological factor with high correlation but crop species number was neglected. After, crop yield of each crops was estimated by using the three suggested types of models. Chinese cabbage showed high accuracy in overall, while the accuracy of daikon and onion was quiet revised by neglecting the outlier. Chili and garlic showed differences by region, but Kyungbuk chili and Chungnam, Kyungsang garlic appeared significant accuracy. We also selected key meteorological factor of each crops which has the highest relation with crop yield. If the factor had significant relation with the quantity, it explains better about the variations of key meteorological factor. This study will contribute to establishing the methodology of future studies by estimating the crop yield of different species by using farmland meterological information and relatively simplify multiple linear regression models.

• 한국기후변화학회지
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• 제9권4호
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• pp.407-421
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• 2018

In this paper, I analyze the GHG (greenhouse gas) emission factor of the domestic railway transportation sector using the LMDI (Log Mean Divisia Index) methodology. These GHG factors are the emission factor effect, energy intensity effect, transportation intensity effect, and economic activity effect. The analysis period was from 2011 to 2016, and the analysis objects were an intercity railway, wide area railway, and urban railway. The results show that the GHG emission of railway transportation sector decreased during these 6 years. The factors decreasing the GHG emission are the emission factor effect, energy intensity effect, and transportation intensity effect, while the factor increasing the GHG emission is the economic activity effect.