Environmental work inherently involves unknown conditions that require sampling and data collection to understand the nature of contamination and determine how best to address associated risks. Data Quality Objectives (DQOs) enable environmental professionals to clearly define data needs, the purpose of the data, and the decisions that will be made based on the data generated. The DQO Process also prompts consideration of the most appropriate sampling method(s) to yield representative and defensible data. U.S. Environmental Protection Agency (EPA) Guidance Document QA/G-4 states that the DQO Process is "a systematic planning tool based on scientific method, to develop sampling design for data collection activities that support decision making."
While there are various DQO and systematic processes that serve a similar purpose, the EPA DQO Process is most commonly used to support environmental investigations. The process consists of the following seven steps:
Decisions are only as good as the inputs that go into making those decisions. By using the DQO Process for relevant project work, the Envirologic team can systematically define the issue at hand and determine the project objectives, inputs needed, data quality requirements, and how the data will be used. Documenting DQOs also helps to prevent scope creep and misuse of data by clearly identifying the intent, limitations, and purpose of the corresponding sampling/data gathering tasks. The DQO Process provides a foundation for strategic planning and generation of solid evidence, thereby increasing confidence in our decisions and better serving our clients' needs.
For more information on the DQO Process, please refer to the following resources:
If you would like to discuss the DQO Process, please contact Alisa Lindsay, P.E. by phone at (269) 342-1100 or email.
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