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Site Investigation Work Plan Data Acquisition Carousel Cleaners, Sacramento, California and QA/QC 5.0 Data Acquisition and Quality Assurance/Quality Control This section discusses the procedures, objectives, functional activities, and specific QA/QC activities designed to achieve established data quality goals, for all quality-related field sampling and laboratory analysis activities to be implemented during investigation activities. The measures will be implemented to produce data that are scientifically valid,be of known and acceptable quality,meet established objectives, and be legally defensible through the assessment of precision, accuracy,representativeness, comparability, and completeness(PARCC). 5.1 Project Design and Rationale The CVWB has initiated this investigation to assess the nature and extent of VOC contamination in the project vicinity. All samples will be analyzed for select VOCs, specifically PCE and its daughter products, at a minimum. 5.2 Data Quality Objectives Data quality objectives(DQOs) are used to develop a scientific and resource-effective data collection design. DQOs should ensure that the data collected will meet the qualitative and quantitative goals of the project. The DQOs are based on the Guidance on Systematic Planning Using the Data Quality Objectives Process(USEPA 2006). The DQO process consists of the following seven steps: 1. State the Problem 2. Identify the Goal of the Study 3. Identify Information Inputs 4. Define the Boundaries of the Study 5. Develop the Analytic Approach 6. Specify Performance or Acceptance Criteria 7. Develop the Analytic Approach 5.3 Statistical Parameter Indicators Specific QA indicators will be established for each of the PARCC data assessment parameters. These acceptance limits will be expressed as quantitative and qualitative statements concerning the type of data needed to support a decision,based on a specified level of uncertainty. Table 3 lists acceptance criteria for precision, accuracy, and completeness for USEPA Methods TO-15 and TO-15 SIM. 5.3.1 Precision Precision is a measure of mutual agreement among replicate(duplicate) or co-located sample measurements of the same analyte within the same method and matrix. The closer that the numerical values of the measurements are to each other,the more precise the measurement. Precision for a single analyte will be expressed as the relative percent difference(RPD)between the results of any duplicates. Field duplicate(FD) samples will be collected and analyzed at a frequency of approximately 10 percent. Precision also will be assessed for laboratory control samples and sample duplicates (LCSs/LCSDs). 5-1