Literature DB >> 23445252

Regression model for estimating inactivation of microbial aerosols by solar radiation.

Avishai Ben-David1, Jose-Luis Sagripanti.   

Abstract

The inactivation of pathogenic aerosols by solar radiation is relevant to public health and biodefense. We investigated whether a relatively simple method to calculate solar diffuse and total irradiances could be developed and used in environmental photobiology estimations instead of complex atmospheric radiative transfer computer programs. The second-order regression model that we developed reproduced 13 radiation quantities calculated for equinoxes and solstices at 35(°) latitude with a computer-intensive and rather complex atmospheric radiative transfer program (MODTRAN) with a mean error <6% (2% for most radiation quantities). Extending the application of the regression model from a reference latitude and date (chosen as 35° latitude for 21 March) to different latitudes and days of the year was accomplished with variable success: usually with a mean error <15% (but as high as 150% for some combination of latitudes and days of year). This accuracy of the methodology proposed here compares favorably to photobiological experiments where the microbial survival is usually measured with an accuracy no better than ±0.5 log10 units. The approach and equations presented in this study should assist in estimating the maximum time during which microbial pathogens remain infectious after accidental or intentional aerosolization in open environments. © Published 2013. This article is a U.S. Government work and is in the public domain in the USA. Photochemistry and Photobiology
© 2013 The American Society of Photobiology.

Mesh:

Substances:

Year:  2013        PMID: 23445252     DOI: 10.1111/php.12060

Source DB:  PubMed          Journal:  Photochem Photobiol        ISSN: 0031-8655            Impact factor:   3.421


  1 in total

1.  Estimated Inactivation of Coronaviruses by Solar Radiation With Special Reference to COVID-19.

Authors:  Jose-Luis Sagripanti; C David Lytle
Journal:  Photochem Photobiol       Date:  2020-07-09       Impact factor: 3.521

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.