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The United States Environmental Protection Agency`s (EPA) Data Quality Objectives (DQO) process was applied to two environmental monitoring networks for the purpose of optimizing field quality control sampling to give the highest quality monitoring data with minimal impact on resources. The DQO process, developed primarily to aid in cleanup and restoration activities, is a systematic approach to designing sampling, and analysis programs with improved efficiency, cost savings, and measureable and traceable data quality. The two monitoring- networks studied had not been subjected to the systematic review and analysis of the DQO process defined by the EPA. The two monitoring networks studied had relied upon field duplicates or replicates as the main source of field quality control data. Sometimes, both duplicate and routine sample were analyzed by the same analytical laboratory; at other times they were analyzed by different laboratories. This study identified some potential inconsistencies between analytical data and reporting limits from two different laboratories. Application of the EPA DQO process resulted in recommendations for changes in the field quality control sampling program, allowed new insight into the monitoring data, and raised several issues that should be the subject of further investigation.

Application of the Environmental Protection Agency`s data quality objective process to environmental monitoring quality control