Journal article
Benefit-cost estimation for alternative drinking water maximum contaminant levels
Water resources research, v 37(8), pp 2213-2226
Aug 2001
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
A simulation model for estimating compliance behavior and resulting costs at U.S. Community Water Suppliers is developed and applied to the evaluation of a more stringent maximum contaminant level (MCL) for arsenic. Probability distributions of source water arsenic concentrations are simulated using a statistical model conditioned on system location (state) and source water type (surface water or groundwater). This model is fit to two recent national surveys of source waters, then applied with the model explanatory variables for the population of U.S. Community Water Suppliers. Existing treatment types and arsenic removal efficiencies are also simulated. Utilities with finished water arsenic concentrations above the proposed MCL are assumed to select the least cost option compatible with their existing treatment from among 21 available compliance strategies and processes for meeting the standard. Estimated costs and arsenic exposure reductions at individual suppliers are aggregated to estimate the national compliance cost, arsenic exposure reduction, and resulting bladder cancer risk reduction. Uncertainties in the estimates are characterized based on uncertainties in the occurrence model parameters, existing treatment types, treatment removal efficiencies, costs, and the bladder cancer dose-response function for arsenic. Copyright 2001 by the American Geophysical Union.
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Details
- Title
- Benefit-cost estimation for alternative drinking water maximum contaminant levels
- Creators
- Patrick L. Gurian - Carnegie Mellon UniversityMitchell J. SmallJohn R. LockwoodMark J. Schervish
- Publication Details
- Water resources research, v 37(8), pp 2213-2226
- Publisher
- American Geophysical Union
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Web of Science ID
- WOS:000170090100015
- Scopus ID
- 2-s2.0-0034927764
- Other Identifier
- 991019205521404721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Environmental Sciences
- Limnology
- Water Resources