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Since recently, the potential of torrential downpour is increased and the flood damage shows increasing trend, in this study, the method to assess the flood vulnerability was established for the industrial parks, which is the driving power of the economic growth in Korea, and the results were analyzed. The vulnerability of each industrial parks was analyzed using three indicators: climate exposure, sensitivity and the adaptation ability, and the indicator value was calculated by selecting the proxy variable by each indicator. Among the primarily indicators, the final indicators were selected through the site investigation and in-depth interview.

Hot and humid heat exposures challenge the health of outdoor workers engaged in occupations such as construction, agriculture, first response, manufacturing, military, or resource extraction. Therefore, government institutes developed guidelines to prevent heat‐related illnesses and death during high heat exposures. The guidelines use Wet Bulb Globe Temperature (WBGT), which integrates temperature, humidity, solar radiation, and wind speed. However, occupational heat exposure guidelines cannot be readily applied to outdoor work places due to limited WBGT validation studies. In recent years, institutions have started providing experimental WBGT forecasts. These experimental products are continually being refined and have been minimally validated with ground‐based observations. This study evaluated a modified WBGT hindcast using the historical National Digital Forecast Database and the European Centre for Medium‐Range Weather Forecasts Reanalysis v5. We verified the hindcasts with hourly WBGT estimated from ground‐based weather observations. After controlling for geographic attributes and temporal trends, the average difference between the hindcast and in situ data varied from −0.64°C to 1.46°C for different Köppen‐Geiger climate regions, and the average differences are reliable for decision making. However, the results showed statistically significant variances according to geographical features such as aspect, coastal proximity, land use, topographic position index, and Köppen‐Geiger climate categories. The largest absolute difference was observed in the arid desert climates (1.46: 95% CI: 1.45, 1.47), including some parts of Nevada, Arizona, Colorado, and New Mexico. This research investigates geographic factors associated with systematic WBGT differences and points toward ways future forecasts may be statistically adjusted to improve accuracy.

Climate change will make significant impact on species distribution in forest. Pinus koraiensis which is commonly called as Korean Pine is normally distributed in frigid zones. Climate change which causes severe heat could affect distribution of Korean pine. Therefore, this study predicted the distribution of Korean Pine and the suitable habitat area with consideration on uncertainty by applying 52 안윤정․이동근․김호걸․박 찬․김지연․김재욱 climate change scenarios on an ensemble model. First of all, a site index was considered when selecting present and absent points and a stratified method was used to select the points. Secondly, environmental and climate variables were chosen by literature review and then confirmed with experts.Those variables were used as input data of BIOMOD2. Thirdly, the present distribution model was made. The result was validated with ROC. Lastly, RCP scenarios were applied on the models to create the future distribution model. As a results, each individual model shows quite big differences in the results but generally most models and ensemble models estimated that the suitable habitat area would be decreased in midterm future(40s) as well as long term future(90s).

Background Air conditioning usage is the most effective intervention to prevent heat-related illnesses such as heat exhaustion and heatstroke. However, limited geographic coverage and outdated information on air conditioning (AC) availability limit extreme heat risk mapping and prevention efforts. Methods This paper contributes to this research gap by using updated AC availability data to detect areas in Florida, U.S., with significant AC needs and to assess the factors associated with AC ownership. Leveraging property databases, this study first identified Florida, U.S. census tracts by applying Moran’s I and Local Indicators of Spatial Association (LISA) and applied Spatial Durbin Model (SDM) to investigate the relationship between AC ownership and sociodemographic characteristics. Results Clusters of significantly high and low values (p < 0.05) of AC ownership were found across Florida. High-high clusters of AC ownership were found in the northern and eastern coasts, including large metropolitan areas such as Jacksonville, Sarasota, Fort Lauderdale, and Daytona Beach. Clusters with no AC were located in the interior of Florida. We closely looked at AC prevalence clusters in Duval County which contains the city of Jacksonville. Clusters of households with low to no AC availability were found in the urban core, where there is high poverty, poor housing conditions, and low education levels. SDM results showed a significant association between AC ownership and socioeconomic and urbanicity (urban and rural) variables. In particular, we found that a higher proportion of households without an AC are located in predominantly Black or African American neighborhoods, indicating racial disparities in AC ownership. Conclusions Our results can be used to target neighborhoods that are in great need of heat prevention measures. For instance, part of the Low-Income Home Energy Assistance Program offers financial assistance to families with low incomes for energy bills initiated to provide AC units. The result of this study can be used to support this policy. Trial registration Not applicable