Estimation of the SARS-CoV-2 Virus Inactivation Time Using Spectral Ultraviolet Radiation

파장별 지표 자외선 복사량을 이용한 SARS-CoV-2 바이러스 비활성화 시간 추정 연구

  • Park, Sun Ju (Atmospheric Sciences, Department of Astronomy, Space Science, and Geology, Chungnam National University) ;
  • Lee, Yun Gon (Atmospheric Sciences, Department of Astronomy, Space Science, and Geology, Chungnam National University) ;
  • Park, Sang Seo (Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST))
  • 박선주 (충남대학교 우주.지질학과 대기과학전공) ;
  • 이윤곤 (충남대학교 우주.지질학과 대기과학전공) ;
  • 박상서 (울산과학기술원 도시환경공학과)
  • Received : 2022.03.03
  • Accepted : 2022.03.21
  • Published : 2022.03.31


Corona Virus Disease 19 pandemic (COVID-19) causes many deaths worldwide, and has enormous impacts on society and economy. The COVID-19 was caused by a new type of coronavirus (Severe Acute Respiratory Syndrome Cornonavirus 2; SARS-CoV-2), which has been found that these viruses can be effectively inactivated by ultraviolet (UV) radiation of 290~315 nm. In this study, 90% inactivation time of the SARS-CoV-2 virus was analyzed using ground observation data from Brewer spectrophotometer at Yonsei University, Seoul and simulation data from UVSPEC for the period of 2015~2017 and 2020. Based on 12:00-13:00 noon time, the shortest virus inactivation time were estimated as 13.5 minutes in June and 4.8 minutes in July/August, respectively, under all sky and clear sky conditions. In the diurnal and seasonal variations, SARS-CoV-2 could be inactivated by 90% when exposed to UV radiation within 60 minutes from 10:00 to 14:00, for the period of spring to autumn. However, in winter season, the natural prevention effect was meaningless because the intensity of UV radiation weakened, and the time required for virus inactivation increased. The spread of infectious diseases such as COVID-19 is related to various and complex interactions of several variables, but the natural inactivation of viruses by UV radiation presented in this study, especially seasonal differences, need to be considered as major variables.



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