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Environ Sci Technol. 2012 Sep 4;46(17):9491-500. doi: 10.1021/es300564w. Epub 2012 Aug 21.

Deposition of Cryptosporidium parvum oocysts in porous media: a synthesis of attachment efficiencies measured under varying environmental conditions.

Author information

1
Land, Air, and Water Resources, University of California, Davis, California 95616-8628, United States.

Abstract

An extensive set of column experiments was performed with freshly harvested Cryptosporidium parvum oocysts to evaluate the effects of solution chemistry, surface coatings, interactions with other suspended particles, and pore fluid velocity on the fate and transport of this widely occurring waterborne pathogen in sandy porous media. We synthesized our data set with a comprehensive literature survey of similar experiments, to compute attachment (collision) efficiencies (α) used in colloid filtration theory (CFT) using three models for the single collector efficiency (η) across a wide range of experimental conditions. Most prior experiments have observed the transport of surface-treated, sterile C. parvum oocyst in porous media. Our column data confirm for freshly harvested oocysts that the presence of iron coatings on the sand medium and the presence of suspended illite clay drastically enhance oocyst deposition. Increasing ionic strength and decreasing pH also systematically enhance the attachment efficiency. Attachment efficiency decreases only at a very high ionic strength, most likely as a result of steric repulsion and possibly other changes in oocyst surface properties. Attachment efficiencies vary with fluid flow rate but without showing specific trends. We found that the computed attachment efficiency across all reported experiments could be reliably estimated using a regression model based on parameters related to ionic strength and pH. The regression model performed better with the Nelson-Ginn η model and Tufenkji-Elimelech η model than with the Rajagopalan-Tien η model. When CFT is used in environmental assessments, the proposed regression model provides a practical estimator for attachment efficiencies of C. parvum oocyst deposition in porous media for a variety of environmental conditions unfavorable to attachment.

PMID:
22861686
DOI:
10.1021/es300564w
[Indexed for MEDLINE]

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