United Slates Environmental Protection Agency f 9355.9-03 PB94-963207 FPA 5n-F-P3- November 1993 Superfund What are DQOs? DQOs are qualitative and quantitative state- ments derived from the outputs of each step of the DQO Process that: (1) Clarify the study objective; (2) Define the most appropriate type of data to collect; (3) Determine the most appropriate condi- tions from which to collect the data; and (4) Specify acceptable levels of decision errors that will be used as the basis for establishing the quantity and quality of data needed to support the decision. The DQOs are then used to develop a scien- tific and resource-effective sampling design. What is the Data Quality Objective Process? The DQO Process is a scientific and legally defensible data collection planning process to help users decide what type, quality, and quantity of data will be sufficient for envi- ronmental decision making. How does the DQO Process address early and time-critical sampling activities? The DQO Process should be used to plan all significant Superfund field investigations, regardless of the sampling objectives. For early and time-critical decisions, a less rigor- ous approach to DQO development is consis- tent with Superfund policy on accelerated response activities. Where can more information about the Superfund DQO guidance, the DQO process, and QA training be found? For more information on Superfund DQO guidance contact Duane Geuder, QA Manager for the Office of Emergency and Remedial Response (OERR) at 703-603-8891. EPA provides quarterly DQO and DQA training and quality assurance workshops at the EPA Institute (202-260-3297). The training courses are a series of presentations and exercises that engage the audience in actual DQO develop- ment and DQA activities. EPA Data Quality Objectives Process for Superfund DQO DQO DQO DQC DQi DC How does the DQO Process fit into integrated site assessment? By emphasizing the need to place limits on the probability of taking incorrect actions, the DQO Process complements the integrated site assessment objective of evaluating the need for action. The DQO Process places a worth- while investment in planning, which results in timely and efficient cleanups. Copies of the DQO Fact Sheet and related Superfund DQO documents can be obtained from: National Technical Information Service (NTIS) 703-487-4650 Interim Final Guidance PB94-963203 Workbook PB94-963204 Fact Sheet PB94-963205 ------- 1 State the Problem Purpose Summarize the contamination problem that will require new environmental data, and identify the resources available to resolve the problem. • Identify members of the scoping team. • Develop/refine the conceptual site model. • Define the exposure scenarios. • Specify available resources. • Write a brief summary of the contamination problem. £ Identify the Decision Purpose Identify the decision that requires new environmental data to address the contami- nation problem. Identify the key decision for the current phase or stage of the project. Identify alternative actions that maybe taken based on the findings of the field investigation. Identify relationships between this decision and any other current or subsequent decisions. 3 Identify Inputs Purpose Identify the information needed to support the decision, and specify which inputs require new environmental measurements. Identify the informational inputs needed to resolve the decision. Identify sources for each informational input, and list those inputs that are obtained through environmental measurements. Define the basis for establishing contaminant-specific action levels. Identify potential sampling approaches and appropriate analytical methods. The Data Quality Objectives Process 1. State the Problem * 2. Identify the Decision 3. Identify Inputs to the Decision 4. Define the Study Boundaries * 5. Develop a Decision Rule * 6. Specify Limits on Decision Errors ** 7. Optimize the Design for Obtaining Data Sampling and Analysis Plan Development Implementation Data Quality Assessment Define Boundaries 5 Develop a Decision Rule Develop a logical "if...then..." statement that defines the conditions that would cause the decision maker to choose among the alternative actions. Specify the parameter of interest (such as mean, median, or proportion). Specify the preliminary action level for the decision. Combine the outputs of the previous DQO steps into an "if...then..." decision rule that includes the parameter of interest, the action level, and the alternative actions. Purpose Specify the spatial and temporal aspects of the environmental media that the data must represent to support the decision. • Define the geographic areas of the field investigation. • Specify the characteristics that define the population of interest. • Divide the population into strata having 'relatively homogeneous characteristics. • Define the scale of decision making. • • Determine the time frame to which the decision applies. • Determine when to collect samples. • Identify practical constraints that may hinder sample collection (reconsider previous steps as necessary). Optimize the Design Identify the most resource-effective sampling and analysis design for generating data that are expected to satisfy the DQOs. Review the DQO outputs and existing environmental data. ' Develop general sampling and analysis design alternatives. For each design alternative, verify that the DQOs are satisfied. Select the most resource-effective design that satisfies all of the DQOs. Document the operational details and theoretical assumptions of the selected design in the Sampling andAnalysis Plan. Specify Limits on Decision Errors Purpose Specify the decision maker's acceptable limits on decision errors, which are used to establish appropriate performance goals for limiting uncertainty in the data. Activities • Determine the range of contaminant levelsthatmaybe encountered a t the site. • Define both types of decision errors and identify the potential consequences of each. • Specify a range of contaminant levels over which the consequences of decision errors are relatively minor (the gray region). Assign acceptable limits on decision errors above and below the gray region. Check for consistency. ------- |