Drinking Water and Unregulated Contaminants: Analyses of Epa by Cynthia Romero

By Cynthia Romero

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The UCMR program faces other limitations that may cause EPA to base its regulatory determinations on inaccurate or outdated information. In particular, EPA’s standard monitoring frequency may not be accurately estimating the occurrence of certain contaminants in the public’s drinking water, particularly those that occur sporadically like viruses or seasonally like pesticides. By not varying the monitoring frequency for contaminants when appropriate, for example by increasing the frequency during the months when EPA expects viruses to be present, the UCMR data may not provide reliable estimates of contaminant occurrence.

We identified 14 experts from academia, an analytical laboratory, environmental advocacy organizations, professional associations, water utilities, and federal and state government agencies. These experts were selected based on their demonstrated familiarity with EPA’s CCL, UCMR, and regulatory determination processes. The first round of the survey— which ran from December 12, 2012 to January 4, 2013—asked these experts to respond to 10 open-ended questions. These questions asked about various aspects of the UCMR program that helped or hindered EPA in (1) selecting priority contaminants, (2) monitoring for selected contaminants, and (3) using the data to support regulatory determinations.

These methods can detect a total of 67 unregulated contaminants, including 4 listed on CCL3 and 8 contaminants of emerging concern, according to our analysis of EPA data. 44 In addition, EPA officials who use the UCMR data to make regulatory determinations, while sensitive to the practical limitations of monitoring for additional contaminants, said that it would be helpful to have additional UCMR data if a method already in use for UCMR could detect the occurrence of additional contaminants. However, because of the SDWA limit of 30 contaminants, EPA cannot always take advantage of this efficiency and is unable to gain economies of scale by monitoring for additional contaminants using monitoring that is already under way.

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