## 4 Conclusions  
We investigated the impact of COVID-19 control actions on air quality and the resulting health benefits. Dramatic air quality improvements were observed in both cities. In the case of PM\({}_{2.5}\), it was reduced by 30.6-30.8% and PM\({}_{10}\) was significantly reduced by 59.5-63.3%. NO\({}_{2}\) also decreased by 26.1-39.6%, supporting the positive effects of human activities. The PM\({}_{2.5}\)/PM\({}_{10}\) ratio significantly decreased from 0.69-0.70 before SD to 0.52-0.53 after SD. This proves that while the effect of improving air quality before SD was due to reductions in transboundary pollutants, the reductions in anthropogenic emissions in Korea after SD also affected the results. The AQI of PM\({}_{2.5}\) and PM\({}_{10}\) showed air quality improvement more clearly. South Korea generally experiences severe air pollution from winter to spring, but it was never rated as unhealthy in 2020. In addition, the number of days assessed as unhealthy for sensitive groups was considerably reduced, and it is thought that there would be a significant health effect on at-risk groups. However, the PM\({}_{2.5}\)/PM\({}_{10}\) ratio still exceeded 0.5 and the AQI distribution often exceeded 100, confirming that PM\({}_{2.5}\) was still a contributory pollutant to Korean air quality. We were able to assess the deaths prevented from reduced air pollutant levels. PM\({}_{2.5}\) was still a key pollutant in the health benefit evaluation, and there were 250 and 78 preventable deaths in Seoul and Daegu, respectively. The resulting health benefits were estimated at USD 884 million and USD 278 million, respectively. This was a conservative approach and could be evaluated as a greater health benefit when the effects of PM\({}_{10}\) and NO\({}_{2}\) are considered together. The number of deaths caused by COVID-19 showed a large difference, with two and 154 in Seoul and Daegu, and USD 7.1 million and USD 543.6 million in economic losses, respectively, showing a prime example of the remarkable health effects from the initial spread of coronavirus. Several limitations exist in this study. First, the evaluation of air pollutant levels reflecting meteorological conditions was not performed. Precipitation, wind speed, and temperature can affect atmospheric diffusion, and more accurate concentration comparisons are needed in consideration of meteorological conditions. Second, since 2020 mortality data were not available, the past average mortality rate was used. Differences in mortality rates due to COVID-19 may occur, and the mortality statistics for 2020 can be used to access health benefits in more detail. Nevertheless, we confirmed that COVID-19 control actions caused changes in air quality and contributed to preventing deaths from air pollution. Moreover, the results implied that changes in air quality in the neighboring countries caused effects across borders. Meanwhile, we assessed health benefits due to improved air quality, but it was evaluated that the global disease burden caused by COVID-19 is even greater. Figure 9: Avoided deaths from PM\({}_{2.5}\), PM\({}_{10}\), and NO\({}_{2}\) reductions over 18 weeks, and associated economic outcomes (+). The economic outcome from COVID-19 deaths was evaluated as (-). ((a): Seoul and (b): Daegu)The results of this study indicate the direction we should take to lead a sustainable and healthy life in preparation for the post-COVID-era and emphasize the necessity of national and global efforts. The following are available online at [[http://www.mdpi.com/2076-3417/10/23/8720/s1](http://www.mdpi.com/2076-3417/10/23/8720/s1)]([http://www.mdpi.com/2076-3417/10/23/8720/s1](http://www.mdpi.com/2076-3417/10/23/8720/s1)): Table S1: Meteorological conditions during COVID-19 pandemic and control periods, Table S2: Relative risks (RRs) and attributable factors (AFs) for PM\({}_{2.5}\), PM\({}_{10}\), and NO\({}_{2}\) (Seoul), and Table S3: Relative risks (RRs) and attributable factors (AFs) for PM\({}_{2.5}\), PM\({}_{10}\), and NO\({}_{2}\) (Daegu). Conceptualization, J.H.S.