Title: The arrhenius equation as means to simulate E. Coli survival in waters Authors
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: September 27, 2012
Publication Date: October 21, 2012
Citation: Blaustein, R., Pachepsky, Y.A., Hill Robert, Whelan, G., Molina, M., Zepp, R., Sadeghi, A.M. 2012. The arrhenius equation as means to simulate E. Coli survival in waters. [abstract]. Paper No. 357-3. Technical Abstract: E. coli is an important microorganism indicator used to show the presence of pathogens and fecal contamination in waters. Knowing E. coli survival rates is important for assessing the severity of contamination that has occurred and making appropriate management evaluations. E. coli survival rates are dependent on temperature. It was suggested to use an approximation of the Arrhenius equation to express these dependencies. This suggestion was made 34 years ago based on 20 survival curves from literature, and has not been revisited since then. The objective of this study was to re-evaluate the accuracy of the Arrhenius equation using published data accumulated more recently. We assembled a database consisting of 450 survival curves from 70 peer-reviewed papers on E. coli inactivation in water from various sources. This work was focused on 200 curves taken from experiments that were performed in laboratories under dark conditions to exclude effects of sunlight and other field factors that would cause additional variability in results. The coordinates in all curves were “log concentration vs. time.” There were several different ways that the curves were generally shaped. About half of the curves began with a section of fast inactivation followed by a section of slow inactivation, about a quarter of the curves started with a lag period followed by inactivation, another quarter were approximately linear throughout, and a small number of curves had the Weibull-type shape. The first-order inactivation rate constants were calculated from the linear sections of all survival curves and the data was grouped into categories based on the origin of the water used, which included waters of agricultural origin, pristine water sources, groundwater and wells, lakes and reservoirs, rivers and streams, estuaries and sea water, and wastewater. Dependencies of E. coli inactivation rates on temperature varied among different water sources. Change in inactivation rates with temperature at specific sites generally fit the Arrhenius equation. However, the activation energy constant appeared to be site-specific. This study will be extended to provide guidance in calibration of E. coli fate and transport modeling systems that are used in making environmental management decisions.