Résumé
Resilience in business continuity of an entire industrial complex has direct local socioeconomic impact;however, there are few methods available for objective assessment of its status. This study investigated whether change in air quality could explain the state of economic activity in an industrial complex. Concentrations of PM2.5 and NO2 above several industrial complexes in central Thailand were extracted using the Google Earth Engine™ and analyzed to examine their temporal characteristics in relation to decline in business activity caused by the COVID-19 pandemic. Results confirmed that industrial complexes whose activities were diminished by the pandemic showed concurrent trends of reduction in each pollutant, proving that the concentration of airborne substances has potential to reveal the level of activity of industrial complexes. To enhance the application potential of the proposed method, further study should investigate specific causal inferences by extracting the characteristics of other airborne substances, and consider industrial complexes that include a greater number of companies and major industries. © 2023 IEEE.
Résumé
The number of refugees in the world peaked at 26.3 million as of mid-2020. More than 75 percent of these refugees are in a protracted situation, one in which refugees find themselves in a long-lasting and intractable state of limbo. However, the budget for refugee protection and care has not been sufficient for years. Due to the limited humanitarian and developmental budget, the role of refugee-related businesses is gaining more attention. The aim of this study is to show the feasibility of the partially online systems-based Evolutionary Learning Laboratory (ELLab) approach in the COVID-19 era via a case study of Uganda and to identify the current systems model of refugee-related businesses, their leverage points, and the action plans necessary for the development of an optimal systems model for refugee-related businesses. The authors suggested the efficacy of the online system-based ELLab and provided new ways for the application of the ELLab method in the COVID-19 era. They also managed to identify the current systems model of refugee-related businesses, their leverage points, and their action plans through the ELLab process. © ISSS 2021. All right reserved.
Résumé
The effects of COVID-19 measures on the quantitative changes in atmospheric substances associated with economic activities have been explored in various studies. However, the specific relationship between the changes in economic activities due to government interventions and the associated changes in atmospheric substances remains unclear. This relationship needs to be understood in detail, especially in the tourism industry where conflicting responses are needed, such as promoting people flow and socioeconomic development while adopting measures to prevent the spread of infectious diseases. Therefore, this study focused on the tourism industry in Japan, used Google Earth Engine to calculate the changes in five atmospheric substances before and during the government's Go To Travel Campaign, which was implemented to support domestic travel, and analyzed the correlations with statistical data such as the number of travelers, use of buses, and taxis. As a result, a series of connected behaviors clarified the fact that socioeconomic activities affected by the government's Go To Travel Campaign surfaced with the changes in the atmospheric substances. To further understand the relationship between interventions to promote tourism and air quality, additional datasets and approaches are needed, including data on the operation status of facilities and the behavioral characteristics of Japanese travelers.
Résumé
Various interventions were made by the Thai government to prevent the COVID-19 spread by controlling socioeconomic activities, but the effectiveness of these interventions and other factors have not yet been fully clarified. Thus, this study aims to provide further scientific evidence on those potential factors which affect the socioeconomic activities changes during the pandemic, by using spatial analysis on atmospheric composition. By taking Phra Nakhon Si Ayutthaya Province, Thailand as the case area. Results of the government's COVID-19 measures and statuses of industries were compared with changes in aerosols, including PM 2.5 which was analyzed by Google Earth Engine with nine open datasets including meteorological and hydrological factors. The analysis revealed that the aerosol index in ueban area of the province decreased at 28.03% in 2020 compared in 2019. Besides, PM 2.5 drastically decreased from March 2020, even without the influence of wind speed which as the highest causal relationship, and kept low level compared with previous years. The reason of the tendency would be explained that other than government interventions including national-level state of the emergency decree, reduction of factories' activities at Rojana Industrial Park and reduction of the number of tourists had significant influence to reduce the mean value of PM 2.5.
Résumé
The control of economic activities by governments for the purpose of minimizing COVID-19 spread influenced atmospheric conditions. Satellite-based technology is promising to monitor these changes and even non-specialists in geospatial analysis can use it through cloud-based open platforms. This study aims to give scientific interpretation on the causes of the atmospheric changes based on these governmental controls on human activity. The nitrogen dioxide (NO2) levels were monitored in Ayutthaya Province in Thailand in an urban area including industrial zones during January 1 to April 30, 2020. An analysis was conducted with Google Earth Engine by using four datasets including NO2 data from Sentinel-5P. The mean value of NO2 density in 2020 decreased 12.5% compared with that in 2019. The closure of industrial facilities by the government seemed to be a key cause of the phenomena. The decline was statistically tested and resulted in a significant difference between the two periods. As the new daily cases decreased to single digits, the difference became non-significant from May 1, 2020. Single timeseries analysis on NO2 density change enabled visualization of the brief impact of responses and policies made by the government and subsequent economic activities;however, further atmospheric and industrial activity data are required for further assessment.