• 농업과학연구
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• 제44권2호
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• pp.296-307
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• 2017

Globally, consumers' enormous and increasing appetite for meat is one of the biggest causes of climate change because livestock industry emits more greenhouse gas than transportation. The purpose of this study is to analyze consumer awareness about the impact of meat consumption on sustainability in response to climate change. Based on the theory of planned behavior, the attitudes, subjective norms, perceived behavioral control, prior knowledge, and risk perception variables were analyzed to evaluate the impact of climate change awareness over consumer behavior on meat consumption. Major findings are as follows: consumers were aware of climate change but has made few changes to their meat consumption. In addition, changes in meat consumption were found to be caused by health safety concerns, such as disease outbreaks. Significant variables related to meat consumption patterns associated to climate change impacts were household income, age, attitude, subjective norm, perceived behavioral control, and prior knowledge. These results suggest some implications for policy. There is a need for public relations and education to make the public aware of and better understanding of link between climate change and diet. Also, government should make efforts to raise awareness of mitigation of climate change such as comprehensive food labels which are identifying lesser impacts on climate and better dietary guideline instructions which would include coping with climate change.

• 대한안전경영과학회지
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• 제12권4호
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• pp.31-39
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• 2010

The purpose of this study was to examine the effects of stress response on safety behavior and to explore moderating effect of safety climate between stress response and safety behavior. 224 workers were asked to respond to the questionnaires that measured various demographic variables, stress response, safety climates and safety behaviors. A hierarchical regression was conducted to identify variables that had significant relationships with safety behavior and to examine moderating effect of safety climate between stress response and safety behavior. Results indicated that the depression response significantly predicted safety behavior. It was found that the safety climate was also a significant predictor for safety behavior. In addition, safety climate had a moderating effect on the relation between depression and anger responses and safety behavior.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.226-226
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• 2015

The complex climate system regarding human actions is well represented through global climate models (GCMs). The output from GCMs provides useful information about the rate and magnitude of future climate change. Especially, the temperature variable is most reliable among other GCM outputs. However, hydrological variables (e.g. precipitation) from GCM outputs for future climate change contain too high uncertainty to use in practice. Therefore, we propose a method that simulates temperature variable with increasing in a certain level (e.g. 0.5oC or 1.0oC increase) as a global warming scenario from observed data. In addition, a hydrometeorological variable can be simulated employing block-wise sampling technique associated with the temperature simulation. The proposed method was tested for assessing the future change of the seasonal precipitation in South Korea under global warming scenario. The results illustrate that the proposed method is a good alternative to levy the variation of hydrological variables under global warming condition.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.160-160
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• 2023

Generally, Global Climate Models (GCM) cannot be used directly due to their inherent error arising from over or under-estimation of climate variables compared to the observed data. Several bias correction methods have been devised to solve this problem. Most of the traditional bias correction methods are one dimensional as they bias correct the climate variables separately. One such method is the Quantile Mapping method which builds a transfer function based on the statistical differences between the GCM and observed variables. Laux et al. introduced a copula-based method that bias corrects simulated climate data by employing not one but two different climate variables simultaneously and essentially extends the traditional one dimensional method into two dimensions. but it has some limitations. This study uses objective functions to address specifically, the limitations of Laux's methods on the Quantile Mapping method. The objective functions used were the observed rank correlation function, the observed moment function and the observed likelihood function. To illustrate the performance of this method, it is applied to ten GCMs for 20 stations in South Korea. The marginal distributions used were the Weibull, Gamma, Lognormal, Logistic and the Gumbel distributions. The tested copula family include most Archimedean copula families. Five performance metrics are used to evaluate the efficiency of this method, the Mean Square Error, Root Mean Square Error, Kolmogorov-Smirnov test, Percent Bias, Nash-Sutcliffe Efficiency and the Kullback Leibler Divergence. The results showed a significant improvement of Laux's method especially when maximizing the observed rank correlation function and when maximizing a combination of the observed rank correlation and observed moments functions for all GCMs in the validation period.

• 한국초지조사료학회지
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• 제41권1호
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• pp.47-55
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• 2021

본 연구는 기후요인과 토양요인이 알팔파 건물수량에 어느 정도 영향을 미치는지를 기여도로 평가할 목적으로, 기상변수와 토양물리성변수를 고려하여 일반선형모형으로 수량예측모델을 구축하였다. 알팔파 수량예측모델 구축과정은 알팔파, 기상 및 토양자료수집, 가공, 통계분석 및 모델구축 순이었다. 수량예측모델은 알팔파와 양적자료인 기상변수를 선택하기 위한 다중회귀분석과 질적자료인 토양물리성변수도 고려하기 위해서 일반선형모형을 사용하였다. 그 결과 DMY에 영향을 미치는 기상변수는 적산온도와 생육일수이었으며, 토양물리성변수는 점토함량이 선택되었다. DMY에 영향을 미치는 변수별 기여도는 점토함량(63%), 적산온도(21%) 및 생육일수(11%)순 이었으며 요인별 기여도는 기후요인(적산온도, 21%와 생육일수, 11%)이 32%, 토양요인(점토함량)이 63%로 나타나 토양요인이 기후요인보다 알팔파 건물수량에 더 기여하는 것으로 평가하였다. 본 연구에서 이용한 알팔파 자료는 토성, 시비수준 및 품종이 제한되어 있어 앞으로 이들 요인을 고려한 다양한 조건의 재배실험을 통하여 보다 많은 자료축적이 요구된다.

• 자원ㆍ환경경제연구
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• 제24권2호
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• pp.343-363
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• 2015

본 연구는 기후변화가 국가의 총요소생산성에 미치는 영향을 분석하였다. 구체적으로 대표적 기후변수인 기온와 강수량이 국가의 총요소생산성에 미치는 영향을 분석하였다. 기존 연구와는 달리 본 연구는 최근 기후변화의 패턴인 기후 변동성이 높아지는 현상을 고려하기 위해 기후변수들의 평균값뿐만 아니라 최고값을 고려하여 분석하였다. 선형회귀분석 결과 평균기온의 상승은 생산성에 부정적 영향을 미치는 것으로 나타났으나 강수량의 평균적 증가는 긍정적 영향을 미치는 것으로 분석되었다. 하지만 최대 강수량은 평균 강수량과는 달리 총요소생산성을 증가시키는 것으로 분석되었다. 이러한 결과는 기존의 연구와 부합하는 것으로 나타났다. 하지만 패널자료를 분석한 결과 평균기온 이외에 다른 기후변수들(평균 강수량, 최대기온, 최대 강수량)은 유의미하게 영향을 주지 않는 것으로 나타났다. 또한 평균기온의 상승은 총요소생산성을 증가시키는 것으로 분석되었다. 이는 본 연구가 장기시계열 자료를 이용하여 국가들의 기후변화 적응능력에 의해 영향을 받은 것으로 분석된다.

• 환경영향평가
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• 제22권6호
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• pp.677-693
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• 2013

IPCC showed that calculation of climate vulnerability index requires standardization process of various proxy variables for the estimation of climate exposure, sensitivity, and adaptive capacity. In this study, four different methodologies of standardization methods: Z-score, Rescaling, Ranking, and Distance to the reference country, are employed to evaluate climate vulnerability-VRI (Vulnerability-Resilience Indicator) over Korean peninsula, and the error ranges of VRI, arising from employing the different standardization are estimated. All of proxy variables are provided by CCGIS (Climate Change adaptation toolkit based on GIS) which hosts information on both past and current socio-economic data and climate and environmental IPCC SRES (A2, B1, A1B, A1T, A1FI, and A1 scenarios) climate data for the decades of 2000s, 2020s, 2050s, and 2100s. The results showed that Z-score and Rescaling methods showed statistically undistinguishable results with minor differences of spatial distribution, while Ranking and Distance to the reference country methods showed some possibility to lead the different ranking of VRI among South Korean provinces, depending on the local characteristics and reference province. The resultant VRIs calculated from different standardization methods showed Cronbach's alpha of more than 0.84, indicating that all of different methodologies were overall consistent. Similar horizontal distributions were shown with the same trends: VRI increases as province is close to the coastal region and/or it close toward lower latitude, and decreases as it is close to urbanization area. Other characteristics of the four different standardization are discussed in this study.

• 간호행정학회지
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• 제16권1호
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• pp.86-100
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• 2010

Purpose: This study was done to examine the relationship of job satisfaction and organizational commitment of perioperative nurses. Method: The subjects of this study were 500 perioperative nurses from 11 hospitals. The data were collected by self-reporting questionnaires from Sep. 19 to Sep. 27, 2009. Results: There was statistically significant relationship among the five variables. The analyses of covariance of these five variables revealed overall significant (p<.05). Stepwise linear multiple regression analyses were used to examine the influence of these five variables. Results indicated that the variables for verbal abuse (p<.01), workplace climate (p<.01), internal marketing (p<.001), and job transfer (p<.001) contributed significantly to the job satisfaction (adjusted R square=.426), while the verbal abuse (p<.01), internal marketing (p<.01), leadership style (p<.001) and workplace climate (p<.001) did to the organizational commitment (adjusted R square=.351). Canonical correlation analyses revealed that internal marketing and workplace climate contributed most significantly both to job satisfaction and organizational commitment. Conclusion: This study found that all these five nursing managerial factors were important influential on both job satisfaction and organizational commitment of perioperative nurses. Addressing these factors with further research will surely improve the commitment of these nurses and ultimately lead to better perioperative nursing care.

• 간호행정학회지
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• 제13권2호
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• pp.156-166
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• 2007

Purpose: The purpose of the present study was to examine the causal relationships among hospital nursing organizational characteristics (organizational climate, workload), individual characteristics (experience, education) and outcome variables (job satisfaction, job stress, task performance) by constructing and testing a conceptual framework. Method: Five large general hospitals located in Seoul were selected to participated. The total sample of 245 registered nurses represents a response rate of 94 percent. Data for this study was collected from January to February in 2006 by questionnaire. Path analyses with LISREL program were used to test the fit of the proposed model to the data and to examine the causal relationships among variables. Result: Both the proposed model and the modified model fit the data excellently. The model revealed relatively high explanatory power of work stress (40%), job satisfaction (46%) and task performance (27%) by predicted variables. In predicting work stress, job satisfaction and task performance, the finding of this study clearly demonstrate organizational climate might be the most important variable. Conclusion: Based on the findings of the study, it was suggested that desirable organizational climate was needed to increase the nurses' mental and physical health as well as qualified task performance.

• 한국안전학회지
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• 제25권4호
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• pp.76-83
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• 2010

As one of crucial industries, the service industry occupies a large part of economy in Korea poor in natural resources. However, prevention of industrial disasters has been promoted mainly in manufacturing and construction industries where the frequencies of such disasters and victims are high. Research on the evaluation of workplace safety climate has been conducted centering on traditional industries like manufacturing and construction, and few studies have been made for service businesses. The objective of this study was to evaluate workplace safety climate perceived in the field by workers engaged in service businesses and to contribute to the establishment of industrial safety and health policies in consideration of the characteristics of each business category. Using research variables safety knowledge, safety attitude, safety motivation, safety participation, safety compliance, and safeness of work environment, we evaluated comprehensive workplace safety climate based on the causal relations among the variables. In the results of analyzing data from a questionnaire survey of service business employees, statistically significant effect relations among the variables were identified, and the fitness of the model with approved reliability and validity was verified.