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Page 2 of 24 SOP NUMBER 28.0 Analytical Data Validation duplicates, rinsate blanks, field blanks, and trip blanks). The sample-specific review is described in Section 4.1. Sample-specific parameters will be reviewed and evaluated for all data. The review of laboratory performance parameters includes evaluating operations that are in the control of the laboratory, but are independent of the field samples being analyzed. These include: initial calibration, initial and continuing calibration verification, laboratory control sample analysis, compound identification, result calculation (i.e., quantitation), data transcription (i.e.,verification), and method specific quality control requirements (e.g. thermal stability, tuning, resolution, mass calibration, interference check sample analysis). Evaluation of these parameters provides an assessment of overall system performance. The review of laboratory performance parameters is discussed in Section 4.2. Laboratory performance parameters will be reviewed for at least 10% of the data packages (per method per sampling event) received. During the data review process, data validation qualifiers, as defined in Table 1, will be assigned to the results, as necessary, to indicate any potential limitation on the use of the data. In addition, data qualifier codes and bias codes as defined in Table 2 will be added to the results to indicate the reason(s) for qualification and the associated bias direction, if discernable. Data validation narratives will be generated which document the results of all data review activities, all data qualification assigned, and any limitations on the use of the data. 4.1 REVIEW OF SAMPLE-SPECIFIC CRITERIA The review of sample-specific criteria includes evaluating parameters that are sample related. Each of the subsections below describes how each parameter is evaluated. While most parameters to evaluate are pertinent to all methods, some are method specific (e.g. see Section 4.1.6). In general, the hierarchy for acceptance criteria used to evaluate each parameter is as follows: • Method specified acceptance criteria. • Acceptance ranges based on laboratory historical data. According to this hierarchy, a parameter is first evaluated against the requirements set forth in the quality assurance plan. If the criteria are not specified in the quality assurance plan, then the parameter is evaluated against the requirements stated in the analytical method. If the method does not specify acceptance criteria, results for the parameter are compared to acceptance ranges based on laboratory historical data. No recalculation of results from the raw data or transcription error checking will be performed during the review of the sample-specific criteria as recalculation and transcription error checking is completed during the review of laboratory performance criteria. 4.1.1 Case Narrative Comments The data validation process begins with an examination of the case narrative. Any analytical problems noted "in the case narrative are noted in the data validation narrative along with a summary of the effect on the usability of the data. Powertech R Squared Inc Rev 28-1 JAB Attachment A 4/23/2007