Grantee Research Project Results
2000 Progress Report: Statistical Models for the Concentrations of Chemicals in Source and Treated Drinking Water Supplies
EPA Grant Number: R826890Title: 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 Period Covered by this Report: September 1, 1999 through August 31, 2000
Project Amount: $250,000
RFA: Environmental Statistics (1998) RFA Text | Recipients Lists
Research Category: Human Health , Aquatic Ecosystems , Environmental Statistics
Objective:
The objective of the project is 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 the 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.The project has interacted closely with a smaller, ongoing project with the EPA Office of Ground Water and Drinking Water to develop more effective methods for benefit-cost analysis, and uncertainty analysis, for conducting Regulatory Impact Assessments (RIAs) of proposed drinking water maximum contaminant levels (MCLs). As such, our research team has focused both on the development of new, fundamental approaches in statistics and the direct translation and application of these methods into regulatory policy and decision making for the EPA.
Progress Summary:
We have revised a manuscript describing a model for a single contaminant, arsenic, in source waters. The manuscript has received favorable reviews from a leading statistical journal, and we hope that it will soon be accepted. We also have produced a manuscript that develops methodology for estimating treatments that different facilities already have in place. Such information is not publicly available for all water treatment facilities. This will help us to predict levels of arsenic (or another contaminant) in finished waters. We are working on estimation of costs and benefits for alternative MCLs and expect to have a manuscript ready soon. We have nearly produced a working multiple-contaminant model, which should be ready to estimate joint distributions in the near future.Future Activities:
We hope to complete the multiple contaminant model and then prepare a finished water model. The finished water model should combine the occurrence model with the treatment-in-place model. We hope to be able to validate it with the finished water data that is becoming available from the EPA.Journal Articles on this Report : 1 Displayed | Download in RIS Format
| Other project views: | All 6 publications | 1 publications in selected types | All 1 journal articles |
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Gurian PL, Small MJ. Point-of-use treatment and the revised arsenic MCL. Journal of the American Water Works Association 2002, Volume: 94, Number: 3 (MAR), Page: 101-108. |
R826890 (2000) |
not available |
Supplemental Keywords:
Bayesian analysis, geographic variation, water treatment., RFA, Scientific Discipline, Economic, Social, & Behavioral Science Research Program, Toxics, Water, POLLUTANTS/TOXICS, Environmental Chemistry, Chemistry, Contaminant Candidate List, Arsenic, Environmental Statistics, Water Pollutants, Drinking Water, Environmental Engineering, monitoring, public water systems, data synthesis, CCL, Bayesian space-time model, co-pollutant effects, exposure and effects, Bayesian hierarchical statistical models, environmental risks, predictive distributors, exposure, other - risk assessment, community water system, drinking water supplies, treatment, statistical models, maximum contaminant levels, data analysis, drinking water contaminants, water treatment, data models, hierarchical statistical analysis, innovative statistical models, chemical concentrations, drinking water treatment, drinking water system, multiple contaminantsRelevant Websites:
The first manuscript on arsenic occurrence can be found athttp://lib.stat.cmu.edu/cmu-stats/tr/tr700/tr700.html
.Progress and Final Reports:
Original AbstractThe 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.