Data and Method Quality Objectives

Data Quality Objectives (DQOs) and Measurement Quality Objectives (MQOs) are, or should be, the foundation of all monitoring studies. DQOs and MQOs define the objectives for the monitoring and the data quality needed to respond to those objectives.

DQOs are statements that define the confidence required in conclusions drawn from data produced by a project. MQOs are statements that contain specific units of measure such as percent recovery, percent relative standard deviation, standard deviation of X micrograms per liter, or detection level of Y parts per billion. MQOs should be thoroughly specified to allow specific comparisons of data to an MQO.

   Relevant Products

• DQO-PRO -- facilitates understanding the significance of DQOs by showing the relationships between numbers of samples and DQO parameters such as (1) confidence levels versus numbers of false positive or negative conclusions; (2) tolerable error versus analyte concentration, standard deviation, etc., and (3) confidence levels versus sampling area grid size
• EMMA -- an interactive software system used to plan improved and cost-effective monitoring projects. Also an effective teaching aid. Funding provided by the National Science Foundation.
• EPA Quality System -- EPA uses its Quality System to manage the quality of its environmental data collection, generation, and use. The primary goal of the Quality System is to ensure that our environmental data are of sufficient quantity and quality to support the data's intended use. Under the EPA Quality System, EPA organizations develop and implement supporting quality systems. Similar specifications may also apply to contractors, grantees, and other recipients of financial assistance from EPA

ACWI - NWQMC


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Page last modified: January 4, 2010 11:02 AM