Comparison of biological weighting functions used to model endogenous sunlight inactivation rates of MS2 coliphage

Andrea I. Silverman, Nerissa Tay, Nikolaos Machairas

Research output: Contribution to journalArticlepeer-review

Abstract

Sunlight inactivation is important for disinfection of viruses in sunlit waters. As such, attempts have been made to predict the endogenous photoinactivation rate of bacteriophage MS2 using biological weighting functions, which describe microorganism sensitivity to sunlight inactivation as a function of wavelength. In this study, four biological weighting function models were compared to assess their ability to predict endogenous inactivation rates (kendo) of MS2. Previously-published and newly-collected datasets consisting of an incident irradiance spectrum (used as an input to the model) and a measured inactivation rate (kobs) were used for model validation and comparison. kendo values predicted by each model were compared with measured kobs to evaluate the ability of each biological weighting function to predict endogenous sunlight inactivation rates. A model previously developed by Mattle et al. (Env. Sci. Technol. 49, 334–342) over-predicted inactivation rates, whereas the other three models – a model from Fisher et al. (Env. Sci. Technol. 45, 9249–9255), a new model developed in this study, and a modification of the model by Mattle et al. (developed as part of this study) – were better able to estimate inactivation rates. The biological relevance of the spectral shape of each biological weighting function is discussed.

Original languageEnglish (US)
Pages (from-to)439-446
Number of pages8
JournalWater Research
Volume151
DOIs
StatePublished - Mar 15 2019

Keywords

  • Biological weighting function
  • Photoinactivation
  • Solar disinfection model
  • Virus inactivation
  • Waste stabilization pond

ASJC Scopus subject areas

  • Water Science and Technology
  • Ecological Modeling
  • Pollution
  • Waste Management and Disposal
  • Environmental Engineering
  • Civil and Structural Engineering

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