TY - JOUR
T1 - Modeling the endogenous sunlight inactivation rates of laboratory strain and Wastewater E. coli and enterococci using biological weighting functions
AU - Silverman, Andrea I.
AU - Nelson, Kara L.
N1 - Funding Information:
This research was supported by the National Science Foundation (Grant CBET-1335673) and the Engineering Research Center for Reinventing the Nations Urban Water Infrastructure (ReNUWIt; Grant EEC-1028968). We thank Mi Nguyen, Peter Maraccini, and Alexandria Boehm for sharing data; Daisy Benitez for her assistance in the laboratory; and the staff at the Town of Discovery Bay for their invaluable assistance at the wetland.
Publisher Copyright:
© 2016 American Chemical Society.
PY - 2016/11/15
Y1 - 2016/11/15
N2 - Models that predict sunlight inactivation rates of bacteria are valuable tools for predicting the fate of pathogens in recreational waters and designing natural wastewater treatment systems to meet disinfection goals. We developed biological weighting function (BWF)-based numerical models to estimate the endogenous sunlight inactivation rates of E. coli and enterococci. BWF-based models allow the prediction of inactivation rates under a range of environmental conditions that shift the magnitude or spectral distribution of sunlight irradiance (e.g., different times, latitudes, water absorbances, depth). Separate models were developed for laboratory strain bacteria cultured in the laboratory and indigenous organisms concentrated directly from wastewater. Wastewater bacteria were found to be 5-7 times less susceptible to full-spectrum simulated sunlight than the laboratory bacteria, highlighting the importance of conducting experiments with bacteria sourced directly from wastewater. The inactivation rate models fit experimental data well and were successful in predicting the inactivation rates of wastewater E. coli and enterococci measured in clear marine water by researchers from a different laboratory. Additional research is recommended to develop strategies to account for the effects of elevated water pH on predicted inactivation rates.
AB - Models that predict sunlight inactivation rates of bacteria are valuable tools for predicting the fate of pathogens in recreational waters and designing natural wastewater treatment systems to meet disinfection goals. We developed biological weighting function (BWF)-based numerical models to estimate the endogenous sunlight inactivation rates of E. coli and enterococci. BWF-based models allow the prediction of inactivation rates under a range of environmental conditions that shift the magnitude or spectral distribution of sunlight irradiance (e.g., different times, latitudes, water absorbances, depth). Separate models were developed for laboratory strain bacteria cultured in the laboratory and indigenous organisms concentrated directly from wastewater. Wastewater bacteria were found to be 5-7 times less susceptible to full-spectrum simulated sunlight than the laboratory bacteria, highlighting the importance of conducting experiments with bacteria sourced directly from wastewater. The inactivation rate models fit experimental data well and were successful in predicting the inactivation rates of wastewater E. coli and enterococci measured in clear marine water by researchers from a different laboratory. Additional research is recommended to develop strategies to account for the effects of elevated water pH on predicted inactivation rates.
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U2 - 10.1021/acs.est.6b03721
DO - 10.1021/acs.est.6b03721
M3 - Article
C2 - 27934240
AN - SCOPUS:85021852604
SN - 0013-936X
VL - 50
SP - 12292
EP - 12301
JO - Environmental Science & Technology
JF - Environmental Science & Technology
IS - 22
ER -