Guide for developing data quality objectives for ecological risk assessment at DOE Oak Ridge Operations facilities
For the past several years the US Environmental Protection Agency (EPA) has been attempting to streamline and increase the efficiency of field data collection programs, especially Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) Remedial Investigation (RI) programs, by encouraging project managers to develop Data Quality Objectives (DQOs) prior to sampling. The DQO process is a strategic planning approach that is used to prepare for a data collection activity. It provides a systematic procedure for defining the criteria that a data collection design should satisfy, including when to collect samples, where to collect samples, the tolerable level of decision errors for study, and how many samples to collect. It is important to note that DQOs are developed through a process that ties data collection to specific problems and decisions.
- Research Organization:
- Lockheed Martin Energy Systems, Inc., Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- AC05-84OR21400
- OSTI ID:
- 242678
- Report Number(s):
- ES/ER/TM-185; ON: DE96010598
- Resource Relation:
- Other Information: PBD: May 1996
- Country of Publication:
- United States
- Language:
- English
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