DATA CONSULTING SERVICES

Stage 2A data validation includes all elements of Stage 1 data validation, as well as checks on the compliance of sample-related quality control (QC). This includes verification that sample-related QC elements, checks, or standards were performed at the required frequencies. Sample-related QC data is compared to performance criteria, and where criteria are not met, associated sample data are qualified.  Performance criteria may derive from the project QAPP, agency guidance documents, contractual requirements, and/or the analytical methods. Stage 2A data validation includes review of the following QC elements:

• Sample holding times
• Percent recoveries for surrogates and laboratory control sample (LCS), matrix spike (MS), and post-digestion spike samples.
• Relative percent difference (RPD) for LCS duplicates, MS duplicates, Field duplicates, and Laboratory duplicates
• Blank samples to check for sample contamination; this includes method blanks, trip blanks, field blanks, and equipment blanks, and other blanks at the field or preparatory batch level.

Stage 2B data validation includes all elements of Stage 2A data validation, as well as reviewing compliance of instrument-related quality control. This includes verification that instrument-level QC elements, checks, or standards were performed at the required frequencies. Stage 2B data validation includes review of the following QC elements:

• Initial calibration
• Initial calibration verification
• Continuing calibration verification
• Continuing calibration blanks (instrument blanks)
• Additional method-specific performance criteria, including:
  • Internal standard responses and retention times
  • Dual-column confirmation
  • Mass specrometer tuning checks
  • DDT/Endrin breakdown and benzidine/PCP tailing factor performance checks
  • Linear dynamic range, spectral interference, and dilution checks

Stage 3 data validation includes all elements of Stage 2B data validation, as well as recalculating field and QC sample results from the laboratory instrument responses. Once results are recalculated, they are reviewed for compliance with regard to Stage 2A and Stage 2B performance criteria, and compared to original results reported by the laboratory. Where compliance failures or substantial deviations from the original results are identified, data are qualified appropriately. Stage 3 recalculations are labor intensive, and thus are typically performed on a small subset of the data. Stage 3 recalculations should be performed by an experienced chemist familiar who is familiar with the preparatory and analytical methods used. Coordination with the laboratory is useful to ensure calculations are set up correctly. When planning for Stage 3 data validation, it is important to specify in your QAPP what percentage of the data will be recalculated, and how that percentage will be selected.

Stage 4 data validation builds on Stage 3 data validation to include review of raw instrument outputs. Stage 4 data validation is labor intensive and is typically performed on a small subset of the data. Examples of raw instrument outputs reviewed during a Stage 4 data validation include chromatograms, mass spectra, and atomic emission spectra. The chemist checks for correct identification and quantitation of analytes, and confirms non-detected or tentatively identified compounds. A Stage 4 data validation may be warranted to evaluate the validity of anomalous results (e.g. new contaminants identified far from potential sources, outliers in long term monitoring), but is rarely performed for all sample results. Stage 4 data validation is somewhat more qualitative than the other stages of data validation, involves significant professional judgement, and should only be conducted by a chemist with significant experience with the method in question.

This the most popular data quality report we offer and is appropriate for most projects. It provides thorough documentation of data verification, data validation, and data usability assessment findings, including attached data validation checklists (or ADEC laboratory data review checklists) for each sample delivery group. The data quality assessment (DQA) includes all elements of the DVR, plus a more in-depth data usability assessment with respect to PARCCS.

The chemical data quality review (CDQR) report is the most detailed data quality report we offer. It includes thorough documentation of the data verification, data validation, and data usability assessment process. It includes all elements of the DQA, plus additional summary tables as appropriate for different QC elements. It is appropriate for large datasets and higher stages of validation (Stage 2B and above), and is often requested for DoD projects.