Unmanned aerial vehicles (UAV, drones) used as delivery vehicles have received increasing attention due to their mobility and accessibility to remote areas. The purpose of this study is to evaluate the environmental impacts of drone versus motorcycle delivery and to compare the expected environmental improvements due to drone delivery in urban and rural areas. In addition, the potential environmental contributions of electric motorcycles were assessed to determine the effects of introducing this new type of vehicle. Changes in the national electricity generation plan were also examined. The results showed that global warming potential (GWP) per 1 km delivery by drone was one-sixth that of motorcycle delivery, and the particulates produced by drone delivery were half that of motorcycle delivery. The actual environmental impact reduction in consideration of the delivery distance was 13 times higher in a rural area than in an urban area. Increasing the use of environmentally friendly electricity systems, such as solar and wind power, would further enhance the environmental effects of a drone delivery system.

Regionalized lumped rainfall-runoff (RR) models have been widely employed as a means of predicting the streamflow of an ungauged watershed because of their simple yet effective simulation strategies. Parameter regionalization techniques relate the parameter values of a model calibrated to the observations of gauged watersheds to the geohydrological characteristics of the watersheds. Thus, the accuracy of regionalized models is dependent on the calibration processes, as well as the structure of the model used and the quality of the measurements. In this study, we have discussed the potentials and limitations of hydrological model parameter regionalization to provide practical guidance for hydrological modeling of ungauged watersheds. This study used a Tank model as an example model and calibrated its parameters to streamflow observed at the outlets of 39 gauged watersheds. Multiple regression analysis identified the statistical relationships between calibrated parameter values and nine watershed characteristics. The newly developed regional models provided acceptable accuracy in predicting streamflow, demonstrating the potential of the parameter regionalization method. However, uncertainty associated with parameter calibration processes was found to be large enough to affect the accuracy of regionalization. This study demonstrated the importance of objective function selection of the RR model regionalization.

Jeju Island experienced an approximately 42% increase in energy consumption from 2006 to 2015 and the demand for energy consumption is expected to continue to increase. Thus, Jeju Island is planning a project entitled “Carbon Free Island by 2030” to promote sustainable development and is required to estimate the environmental carrying capacity for future energy demand changes. The purpose of this study was to calculate the emergy inherent in Jeju Island’s energy, materials, and information in 2015 using the emergy analysis method and local characteristics. In addition, this study aimed to estimate the emergy indices to evaluate the environmental carrying capacity for sustainable development in 2005, 2015, and 2030 considering the future energy demand. This study’s outputs provide the environmental carrying capacity with emergy indices, such as the percent renewable (%Renew), emergy yield ratio (EYR), environmental loading ratio (ELR), sustainability index (SI), and carrying capacity of the population (CCP) for social and economic activities on Jeju Island, which are expected to be saturated. These findings show regions with heavy tourism require development strategies, including the concept of environmental carrying capacity.

The environmental impact of battery electric vehicles (BEVs) largely depends on the environmental profile of the national electric power grid that enables their operation. The purpose of this study is to analyze the environmental performance of BEV usage in Korea considering the changes and trajectory of the national power roadmap. We examined the environmental performance using a weighted environmental index, considering eight impact categories. The results showed that the weighted environmental impact of Korea’s national power grid supply would increase overall by 66% from 2015 to 2029 using the plan laid out by the 7th Power Roadmap, and by only 33% from 2017 to 2031 using the 8th Power Roadmap plan. This change reflects the substantial amount of renewables in the more recent power mix plan. In 2016, BEV usage in Korea resulted in emissions reductions of about 37% compared with diesel passenger vehicles, and 41% compared with gasoline vehicles per kilometer driven (100 g CO₂e/km versus 158 g and 170 g CO₂e/km, respectively) related to transportation sector. By 2030, BEV usage in Korea is expected to achieve a greater emissions reduction of about 53% compared with diesel vehicles and 56% compared with gasoline vehicles. However, trade-offs are also expected because of increased particulate matter (PM) pollution, which we anticipate to increase by 84% compared with 2016 conditions. Despite these projected increases in PM emissions, increased BEV usage in Korea is expected to result in important global and local benefits through reductions of climate-changing greenhouse gas (GHG) emissions.

In South Korea, there is an awareness of the risks of regional shrinkage and depopulation due to demographic changes and unbalanced population distribution. With concerns about the extinction of local cities and the hollowing out of rural communities, scholars have increasingly called for new population indices or indicators to evaluate the current state of the local population. The purpose of this study was to develop a vulnerability index to effectively analyze the age structure and population changes associated with regional shrinkage (i.e., hollowing out). This study applied ranking and correlation analysis results using data for population density and the population structure by age to develop a new index to assess a region’s vulnerability to the regional shrinkage effect. The new vulnerability index identified vulnerable regions by evaluating regional vulnerability using 2019 data. We also conducted a correlation analysis to validate the new index and found that the proposed index was significantly correlated with population growth and all other demographic indicators. The index developed in this study can be used to assess and compare the vulnerability of areas to regional shrinkage following population changes.