Chi-Yun Back;Dae-Sung Hyun;Sei-Jin Chang;Da-Yee Jeung
Safety and Health at Work
/
v.14
no.1
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pp.71-77
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2023
Background: This study investigated the relationship between trauma exposure and suicidal ideation. Moreover, this study examines the moderating roles of organizational climate on the association between trauma exposure and suicidal ideation in Korean male firefighters. Methods: A total of 15,104 male firefighters who completed a questionnaire were analyzed. The data were obtained using an online self-administered questionnaire from the Firefighter Research on Enhancement of Safety and Health Study. Poisson regression analysis was performed to determine the effects of trauma exposure on suicidal ideation and the moderating effect of organizational climate. Results: The results showed that 389 firefighters (2.6%) responded that they had experienced suicidal ideation. In the final model, trauma exposure was positively related to suicidal ideation (adjusted risk ratio [aRR], 1.076; 95% confidence interval [CI]: 1.051-1.103), and organizational climate was negatively associated with suicidal ideation (aRR, 0.772; 95% CI: 0.739-0.806). Additionally, the interaction term (trauma exposure × organizational climate) was related to suicidal ideation (aRR, 1.016; 95% CI: 1.009-1.023). Conclusions: This study suggests that trauma exposure might play a significant role in developing suicidal ideation and that positive organizational climate moderates the negative effects of trauma exposure on suicidal ideation among firefighters. It is necessary to perform a follow-up study of various intervention strategies to maintain a healthy organizational climate or work environment. Such interventions should promote lasting trust within teams, provide social support and belonging, and nurture job value.
The purpose of this study is to analyze the climate change exposure of fisheries and fish species in the southern sea of Korea under the RCP climate change scenarios. The extent of exposure was calculated through weighted sum of the sea temperature forecasted by National Institute of Fisheries Science, and the weight were obtained from the time-space distribution of each fisheries or species, based on the micro-data for the fishing information reported by each fisherman. Results show that all the exposed sea temperature of RCP8.5 is higher than that of RCP4.5 in year 2100 as well as in near 2030, therefore it is thought to be very important to reduce the GHG emission even in the short term. The extent of exposure was analyzed to be comparatively high especially in the fisheries such as anchovy drag nets and species like cod, anchovy and squid. Meanwhile the method of this study is considered to be excellent to obtain the accurate extent of exposure under RCP scenarios, and therefore it is applicable on assessing the vulnerability of climate change in fisheries.
Yong-Sang Choi;Changhyun Yoo;Minjeong Kong;Minjeong Cho;Haesoo Jung;Yoon-Kyoung Lee;Seon Ki Park;Myoung-Hwan Ahn;Jaehak Hwang;Sung Ju Kim
Atmosphere
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v.34
no.1
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pp.1-21
/
2024
Private companies are increasingly required to take more substantial actions on climate change. This study introduces the principle and cases of climate (physical) risk estimation for 11 private companies in Korea. Climate risk is defined as the product of three major determinants: hazard, exposure, and vulnerability. Hazard is the intensity or frequency of weather phenomena that can cause disasters. Vulnerability can be reflected in the function that explains the relationship between past weather records and loss records. The final climate risk is calculated by multiplying the function by the exposure, which is defined as the area or value of the target area exposed to the climate. Future climate risk is estimated by applying future exposure to estimated future hazard using climate model scenarios or statistical trends based on weather data. The estimated climate risks are developed into three types according to the demand of private companies: i) climate risk for financial portfolio management, ii) climate risk for port logistics management, iii) climate risk for supply chain management. We hope that this study will contribute to the establishment of the climate risk management system in the Korean industrial sector as a whole.
Climate vulnerability index is usually defined as a function of the climate exposure, sensitivity, and adaptive capacity, which requires adequate selection of proxy variables of each variable. We selected and used 9 proxy variables related to climate exposure in the literature, and diagnosed the adequacy of them for application in Korean peninsula. The selected proxy variables are: four variables from temperature, three from precipitation, one from wind speed, and one from relative humidity. We collected climate data over both previous year (1981~2010) and future climate scenario (A1B scenario of IPCC SERES) for 2020, 2050, and 2100. We introduced the spatial and temporal diagnostic statistical parameters, and evaluated both spatial and time variabilities in the relative scale. Of 9 proxy variables, effective humidity indicated the most sensitive to climate change temporally with the biggest spatial variability, implying a good proxy variable in diagnostics of climate change vulnerability in Korea. The second most sensitive variable is the frequency of strong wind speed with a decreasing trend, suggesting that it should be used carefully or may not be of broad utility as a proxy variable in Korea. The A1B scenario of future climate in 2020, 2050 and 2100 matches well with the extension of linear trend of observed variables during 1981~2010, indicating that, except for strong wind speed, the selected proxy variables can be effectively used in calculating the vulnerability index for both past and future climate over Korea. Other local variabilities for the past and future climate in association with climate exposure variables are also discussed here.
Kim, Soo-Jin;Hwang, Syewoon;Bae, Seung-Jong;Yoo, Seunghwan;Choi, Jin-Yong;Jang, Min-Won
Journal of The Korean Society of Agricultural Engineers
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v.63
no.6
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pp.141-150
/
2021
In order to assess the impact of climate change on irrigation reservoirs, climate exposure (EI), sensitivity (SI), and potential impact (PI) were evaluated for 1,651 reservoirs nationwide. Climate exposure and sensitivity by each reservoir were calculated using data collected from 2011 to 2020 for seven proxy variables (e.g. annual rainfall) and six proxy variables (e.g. irrigation days), respectively. The potential impact was calculated as the weighted sum of climate exposure and sensitivity, and was classified into four levels: 'Low (PI<0.4)', 'Medium (PI<0.6)', 'High (PI<0.8)', and 'Critical (PI≥0.8)'. The result showed that both the climate exposure index and the sensitivity index were on average high in Daegu and Gyeongbuk with high temperature and low rainfall. About 79.8% of irrigation reservoirs in Daegu, Gyeongbuk, and Ulsan with high climate exposure and sensitivity resulted in a 'High' level of potential impact. On the contrary, 64.5% of the study reservoirs in Gyeongnam and Gangwon showed 'Low' in potential impact. In further studies, it is required to reorganize the proxy variables and the weights in accordance with practical alternatives for improving adaptive capacity to drought, and it is expected to contribute to establishing a framework for vulnerability assessment of an irrigation reservoir.
Objectives: This study was conducted to evaluate the vulnerability of the human health sector to $PM_{10}$ due to climate change in Incheon over the period of 2005-2014. Methods: Vulnerability to $PM_{10}$ consists of the three categories of climate exposure, sensitivity, and adaptive capacity. The indexes for climate exposure and sensitivity indicate positive effects, while adaptive capacity shows a negative effect on vulnerability to $PM_{10}$. The variables in each category were standardized by the rescaling method, and respective relative regional vulnerability was analyzed through the vulnerability index calculation formula of the Intergovernmental Panel on Climate Change. Results: Regions with a high exposure index were the western and northern urban areas with industrial complexes adjacent to a highway, including Bupyong-gu and Seo-gu. Major factors determining the climate exposure index were the $PM_{10}$ concentration, days of $PM_{10}$ >= $100{\mu}g/m^3$, and $PM_{10}$ emissions. The regions showing a high sensitivity index were urban regions with high populations; these commonly had a high mortality rate for related diseases and vulnerable populations. Conclusions: This study is able to support regionally adjusted adaptation policies and the quantitative background of policy priority since it provides information on the regional health vulnerability to $PM_{10}$ due to climate change in Incheon.
Journal of the Korean Society of Environmental Restoration Technology
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v.24
no.6
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pp.97-107
/
2021
Abnormal climate caused by climate change causes enormous social and economic damage. And such damage and its impact may vary depending on the location and regional characteristics of the region and the social and economic conditions of local residents. Therefore, it is necessary to continuously monitor whether there are indicators that are weaker than other regions among the detailed indicators that constitute the risk, exposure and vulnerability of climate change risk. In this study, the concept of climate change risk was used for heatwave to determine regional inequality of climate change risk. In other words, it was judged that inequality in climate change risk occurred in regions with high risk but high exposure and low vulnerability compared to other regions. As a result of the analysis, it was found that 13 local governments in Korea experienced regional inequality in climate change risk. In order to resolve regional inequality in climate change risks, the current status of regional inequality in climate change should be checked based on the analysis proposed in this study, there is a need for an evaluation and monitoring system that can provide appropriate feedback on areas where inequality has occurred. This continuous evaluation and monitoring-based feedback system is expected to be of great help in resolving regional inequality in climate change risks.
Kim, Seong-Gil;Jang, Seok-Woo;Lee, Young-Ju;Kim, Seong-Soo
Fisheries and Aquatic Sciences
/
v.14
no.3
/
pp.210-217
/
2011
Olive flounder, Paralichthys olivaceus were exposed to waterborne Cu (control, 50, 80, 150, and 320 ${\mu}g$/L) for 30 days and then depurated for 20 days to investigate the effects of waterborne Cu exposure on growth, accumulation, and elimination. The weight-specific growth rate was significantly negatively related to waterborne Cu concentrations at 150 and 320 ${\mu}g$/L. The order of Cu accumulation in different tissues of exposed fish was liver>intestines>gills>kidneys>muscle, suggesting that the liver is more important than other tissues for the storage of Cu in olive flounder. The accumulation factor for the gills, intestines, liver, and muscle increased with increasing exposure time, and accumulation was negatively related to exposure concentration for the gills, kidneys, and muscle. Cu concentrations in the gills, intestines, and liver continuously decreased for 20 days of depuration. The fastest elimination rate occurred in the intestines at all exposure concentrations, and the order of Cu elimination in the different tissues was intestines>liver>gills.
Lee, Bae Hun;Cheon, Dong Won;Park, Hyung Soo;Choi, Ki Choon;Shin, Jeong Seop;Oh, Mi Rae;Jung, Jeong Sung
Journal of The Korean Society of Grassland and Forage Science
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v.41
no.3
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pp.189-197
/
2021
Climate change effects are particularly apparent in many cool-season grasslands in South Korea. Moreover, the probability of climate extremes has intensified and is expected to increase further. In this study, we performed climate change vulnerability assessments in cool-season grasslands based on the analytic hierarchy process method to contribute toward effective decision-making to help reduce grassland damage caused by climate change and extreme weather conditions. In the analytic hierarchy process analysis, vulnerability was found to be influenced in the order of climate exposure (0.575), adaptive capacity (0.283), and sensitivity (0.141). The climate exposure rating value was low in Jeju-do Province and high in Daegu (0.36-0.39) and Incheon (0.33-0.5). The adaptive capacity index showed that grassland compatibility (0.616) is more important than other indicators. The adaptation index of Jeollanam-do Province was higher than that of other regions and relatively low in Gangwon-do Province. In terms of sensitivity, grassland area and unused grassland area were found to affect sensitivity the most with index values of 0.487 and 0.513, respectively. The grassland area rating value was low in Jeju-do and Gangwon-do Province, which had large grassland areas. In terms of vulnerability, that of Jeju-do Province was lower and of Gyeongsangbuk-do Province higher than of other regions. These results suggest that integrating the three aspects of vulnerability (climate exposure, sensitivity, and adaptive capacity) may offer comprehensive and spatially explicit adaptation plans to reduce the impacts of climate change on the cool-season grasslands of South Korea.
The purpose of this study is to set the direction to manage national parks to cope with climate change, and offer basic data to establish the relevant policies. Towards this end, this study analyzed the current and future climate change vulnerability of national parks using the 24 proxy variables of vulnerability in the LCCGIS program, a tool to evaluate climate change vulnerability developed by the National Institute of Environmental Research. To analyze and evaluate the current status of and future prospect on climate change vulnerability of national parks, the proxy variable value of climate exposure was calculated by making a GIS spatial thematic map with $1km{\times}1km$ grid unit through the application of climate change scenario (RCP8.5). The values of proxy variables of sensitivity and adaptation capability were calculated using the basic statistics of national parks. The values of three vulnerability evaluation items were calculated regarding the present (2010s) and future (2050s). The current values were applied to the future equally under the assumption that the current state of the proxy variables related to sensitivity and adaptation capability without a future prediction scenario continues. Seoraksan, Odaesan, Jirisan and Chiaksan National Parks are relatively bigger in terms of the current (2010s) climate exposure. The national park, where the variation of heat wave is the biggest is Wolchulsan National Park. The biggest variation of drought occurs to Gyeryongsan National Park, and Woraksan National Park has the biggest variation of heavy rain. Concerning the climate change sensitivity of national parks, Jirisan National Park is the most sensitive, and adaptation capability is evaluated to be the highest. Gayasan National Park's sensitivity is the lowest, and Chiaksan National Park is the lowest in adaptation capability. As for climate change vulnerability, Seoraksan, Odaesan, Chiaksan and Deogyusan National Parks and Hallyeohaesang National Park are evaluated as high at the current period. The national parks, where future vulnerability change is projected to be the biggest, are Jirisan, Woraksan, Chiaksan and Sobaeksan National Parks in the order. Because such items evaluating the climate change vulnerability of national parks as climate exposure, sensitivity and adaptation capability show relative differences according to national parks' local climate environment, it will be necessary to devise the adaptation measures reflecting the local climate environmental characteristics of national parks, rather than establishing uniform adaptation measures targeting all national parks. The results of this study that evaluated climate change vulnerability using climate exposure, sensitivity and adaptation capability targeting Korea's national parks are expected to be used as basic data for the establishment of measures to adapt to climate change in consideration of national parks' local climate environmental characteristics. However, this study analyzed using only the proxy variables presented by LCCGIS program under the situation that few studies on the evaluation of climate change vulnerability of national parks are found, and therefore this study may not reflect overall national parks' environment properly. A further study on setting weights together with an objective review on more proper proxy variables needs to be carried out in order to evaluate the climate change vulnerability of national parks.
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