Grantee Research Project Results

Statistical Models for the Concentrations of Chemicals in Source and Treated Drinking Water Supplies

EPA Grant Number: R826890
Title: Statistical Models for the Concentrations of Chemicals in Source and Treated Drinking Water Supplies
Investigators: Schervish, Mark J. , Small, Mitchell J.
Institution: Carnegie Mellon University
EPA Project Officer: Hahn, Intaek
Project Period: September 1, 1998 through August 31, 2001 (Extended to September 30, 2002)
Project Amount: $250,000
RFA: Environmental Statistics (1998) RFA Text | Recipients Lists
Research Category: Aquatic Ecosystems , Environmental Statistics , Human Health

Description:

Improvements in Risk Assessment: The distributions of contaminant concentrations and the distributions of treatment efficiencies should help the EPA to determine the sources and degrees of uncertainty associated with some of the information and assumptions that they use in making decisions for drinking water regulation.

Objectives: We propose to develop statistical models for the concentrations of multiple contaminants in both raw and finished drinking water sources. These models will be used to quantify the variability across the United States of the concentrations of these contaminants as well as the uncertainty associated with estimates of concentration. The key components will include models for concentrations in raw water, models for that choice of treatment to be used and models for the efficiency of the treatments. These models can be combined to produce a model for concentrations in finished water.

Approach:

We will model the way that various characteristics such as size of system, geographical location and water source affect concentrations, choice of treatment and treatment efficiency. We will create Bayesian hierarchical statistical models for each of the components and use several available data sets to form posterior and predictive distributions for quantities of interest.

Expected Results:

We expect to produce joint distributions for concentrations of contaminants that can be used by the EPA for assessing the potential impacts of proposed maximum contaminant levels mandated by the Safe Drinking Water Act of 1996. We also expect to develop new statistical methodology for dealing with multiple data sets and sources of expert opinion that each impact on different aspects of the overall research problem.

Publications and Presentations:

Publications have been submitted on this project: View all 6 publications for this project

Journal Articles:

Journal Articles have been submitted on this project: View all 1 journal articles for this project

Supplemental Keywords:

Co-occurrence,, RFA, Scientific Discipline, Water, Economic, Social, & Behavioral Science Research Program, Toxics, POLLUTANTS/TOXICS, Environmental Statistics, Chemistry, Contaminant Candidate List, Environmental Chemistry, Arsenic, Drinking Water, Environmental Engineering, Water Pollutants, Bayesian space-time model, community water system, data analysis, treatment, Bayesian hierarchical statistical models, multiple contaminants, environmental risks, innovative statistical models, drinking water supplies, monitoring, statistical methods, statistical models, co-pollutant effects, data synthesis, drinking water system, drinking water contaminants, exposure, hierarchical statistical analysis, water treatment, chemical concentrations, predictive distributors, drinking water treatment, other - risk assessment, data models, maximum contaminant levels, CCL, public water systems

Relevant Websites:

http://lib.stat.cmu.edu/cmu-stats/tr/tr700/tr700.html Exit EPA icon

Progress and Final Reports:

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.