WASHINGTON The costs to switch to numeric criteria for limiting nutrient pollutants in Florida waters are expected to exceed U.S. Environmental Protection Agency estimates, says a new National Research Council report. The committee that wrote the report questioned the validity of several assumptions in the EPA cost analysis and found that EPA did not adequately report on the uncertainties that could affect the cost of the rule change.
In 2009 EPA decided that numeric limits on the concentration of pollutants in water, such as nitrogen and phosphorus, were necessary in Florida to meet the requirements of the Clean Water Act. These numeric criteria would replace existing state "narrative" criteria, which use words to describe water pollution limits. For example, the Florida narrative standard refers to not causing a population imbalance in aquatic flora and fauna, while the numeric standard would express specific allowable concentrations of nitrogen and phosphorus in water.
In its economic analysis, EPA calculated the cost differential of switching from the narrative to numeric criteria. It considered only those waters that would be newly listed as "impaired" under the numeric criteria and estimated mitigation costs for a variety of sources of pollution that would affect these waters.
The committee concluded that EPA was correct in its approach to calculating the cost of the rule change. However, the agency underestimated both the number of newly impaired waters and the mitigation costs for the stormwater, agricultural, septic system, and government sectors. Furthermore, there was significant uncertainty in the estimates for the municipal and industrial wastewater sectors, making it difficult to know whether the EPA underestimated or overestimated those costs, the report says. The committee also found that the costs of the rule change would be small relative to the total costs that will ultimately be required to restore Fl
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| Contact: Lauren Rugani news@nas.edu 202-334-2138 National Academy of Sciences Source:Eurekalert |