To prevent the spread of COVID-19, the Korean government promoted strong social distancing policies and restricted the use of confined areas and spaces that are likely to cause widespread infection, including religious facilities. The policies affect the consumption behaviours of Korean citizens. The purpose of this study is to examine changes in the consumer behaviours of citizens following the outbreak of COVID-19 in South Korea. Using credit card data from January to June 2020 in Seoul, this study examines the changes in consumption by industry type. Consumption types were classified into education, wholesale and retail, online purchases, food service, leisure, and travel. The industry that was most affected was the travel industry, which did not recover following the decline in consumption due to COVID-19. To examine consumer changes in credit card transactions due to widespread infection, a correlation analysis was conducted between the amount of consumption according to credit card transaction data (card consumption) and the number of confirmed patients and policy implementation by step. For more detailed analyses, group infections in the Guro-gu and Yongsan-gu neighbourhoods were investigated. In Guro-gu, no significant results were found in the area experiencing massive group infection. In Yongsan-gu, a significant negative correlation in consumption and number of cases was found in Itaewon 1-dong, an area with mass infection, and a positive correlation was found in the surrounding areas. Nevertheless, no significant correlations between changes in consumer behaviours and effects of COVID-19 were found as a result of the analysis herein.

In this study, a traffic demand model was created based on a simulation network, and another model was built to calculate exhaust-gas emissions generated by vehicles based on the emission function. Subsequently, emissions for three scenarios were analyzed based on the traffic restriction policy according to the vehicle grading system implemented in Seoul. According to the results of the analysis, emission reduction under the vehicle restriction policy was the highest among passenger cars in the low-speed range, while the emissions of cargo trucks in the high-speed range were found to be high. The emissions showed a high ratio of carbon monoxide and nitrogen oxides, and high emissions were generated from liquefied petroleum gas and diesel vehicles. Furthermore, the effects of vehicle restriction policy were confirmed to reduce emissions from diesel and other vehicle types. Using the established model, we were able to confirm that the vehicle restriction policy contributed to the improvement of air quality. Furthermore, the diesel vehicle restriction policy also had an impact on reducing the emissions of vehicle types other than those using diesel.

The recent increase in energy consumption worldwide has accelerated global warming. Thus, developed countries are aiming to reduce energy consumption in cities and promote eco-friendly policies. Buildings account for most of the energy used in a city. Therefore, it is necessary to identify the factors that affect electrical energy consumption in urban buildings. In this study, we use multiscale geographically weighted regression (MGWR) to analyze these urban characteristic factors at the global and local scales in Seoul, Korea. It is found that population and household characteristics, outdoor temperature, green and water areas, building area according to building usage, and construction age significantly affect the electrical energy consumption of buildings. In addition, the influences of these variables change with the region. Variables with different coefficients by region are winter temperature, green and water area, and households with three or more persons. The results confirm that even within a city, the influence of the aforementioned factors varies in terms of spatial distribution and patterns. This study is significant as it carried out basic research for energy consumption reduction in buildings by deriving related influencing factors.