Development of a Probabilistic Timing Model for the Ingestion of Tap Water
Publication: Journal of Water Resources Planning and Management
Volume 135, Issue 5
Abstract
A contamination event in a water distribution system can result in adverse health impacts to individuals consuming contaminated water from the system. Assessing impacts to such consumers requires accounting for the timing of exposures of individuals to tap-water contaminants that have time-varying concentrations. Here we present a probabilistic model for the timing of ingestion of tap water that we developed for use in the U.S. Environmental Protection Agency’s Threat Ensemble Vulnerability Assessment and Sensor Placement Tool, which is designed to perform consequence assessments for contamination events in water distribution systems. We also present a statistical analysis of the timing of ingestion activity using data collected by the American Time Use Survey. The results of the analysis provide the basis for our model, which accounts for individual variability in ingestion timing and provides a series of potential ingestion times for tap water. It can be combined with a model for ingestion volume to perform exposure assessments and applied in cases for which the use of characteristics typical of the United States is appropriate.
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Acknowledgments
The U.S. Environmental Protection Agency through the Office of Research and Development funded, managed, and participated in the research described here under an interagency agreement. The views expressed in this paper are those of the writers and do not necessarily reflect the views or policies of the USEPA. Mention of trade names or commercial products does not constitute endorsement or recommendation for use. Work at Argonne National Laboratory was sponsored by the USEPA under an interagency agreement through U.S. Department of Energy Grant No. DOEDE-AC02-06CH11357. Karen Hamrick, Economic Research Service, U.S. Department of Agriculture, provided helpful advice on the use and interpretation of the ATUS data. We acknowledge helpful comments from anonymous reviewers. All data analysis and preparation of graphics for this paper were done with R (R Development Core Team 2007).
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Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 135 • Issue 5 • September 2009
Pages: 397 - 405
Copyright
© 2009 ASCE.
History
Received: Nov 27, 2007
Accepted: Feb 17, 2009
Published online: Aug 14, 2009
Published in print: Sep 2009
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