Importance of Quality Assurance Documentation and Coordination with Your Certified Laboratory Amy Yersavich and Susan Netzly-Watkins

VAP Rule OAC (C ) The volunteer must develop and implement data quality objectives (DQOs) Clarify performance and acceptance/rejection criteria for the data. Develop a conceptual site model that illustrates the relationships between contaminants, transport media and receptors Share these documents with your Certified Laboratory as you plan DQOs !

Next Phase of the Project Life Cycle 1.PLANNING: 2.SAMPLING: 3.ASSESSMENT: 4.EVALUATION: Plan for data collection using the DQO process Collect data using a SAP and FSOPs Verify that data meets DQOs Make data-based project decisions

DQO: Strategic Planning Meeting Important for a laboratory to know the type of media you plan to sample and the constituents; Important to understand the detection limits you may need (include Risk Assessor); Understand the site and concerns that could cause interference with analysis; Understand if the samples may need “clean up” steps in the analysis; Communicate the level of quality needed for your evaluation of the data (e.g. Certified or Not).

Systematic Planning = Data Quality Objectives Team Approach – Samplers – understand equipment and field issues. Analysts – explain effect of field collection methods on analysis. Field parameters that may help determine issues (pH, Cl, visual, etc.) QA Manager – require QA on collected samples and sample amounts for QA? Risk Assessor – level of data quality needed – screening or confirmation; detection limits; qualifiers; what is acceptable variability in sample set.

Systematic Planning = Data Quality Objectives Contribution from Lab: Sufficient sample amount for intended analysis, type of containers required, and QA requirements. Analytical concerns with method – detection limits per sample size; Methodology – 5035 for regulatory needs (RCRA vs. VAP); VAP certifying methods.

What are Data Quality Objectives? DQOs are quantitative and qualitative criteria that: Clearly state project objectives – investigation/screening vs. meeting applicable standards. VAP vs. other program Define appropriate types of data to collect – what are the QA requirements, qualifier use, matrices Specify the tolerable levels of potential decision errors – what do you need to ensure QA meets needs (what helps you to understand QA narrative). Define the sufficient quality and quantity of data for its intended use– how do you handle breakage; lack of sample volume and types of errors; outlier data and interaction with lab

DQO Process- Underlying Principles 1.All collected data have error. 2.Nobody can afford absolute certainty. 3.The DQO process defines tolerable error rates. Need to define the types of errors and what your tolerance is: Sampling errors – limited sample size; not homogenous; sample locations; matrix; field cross contamination Lab errors – limited sample to analyze; equipment failure; cross contamination; dilutions; matrix interference Reporting errors – field transcribing; transposition; calculations errors Who is responsible and how does your team deal with this?

Team Planning Coordination Conceptual Site Models Identify inputs for the decision Conceptual site model – Lab needs to understand sample matrix issues for analysis. Exposure scenarios – Define potential RSLs, including the likely number of COCs (for MCA) so the lab can get a good approximation of the detection limits that need to be met. (Risk Assessor is helpful) Identifies resources and constraints Define specific methods, if needed for detection limits Identify concerns of sample size and preservation and holding times Identifies special analytical considerations, potential matrix issues, suspected high concentrations

Putting It Together- DQO Process Output A well thought out and defensible work plan for the study which includes: – Defined DQOs for planning and addressing error – Defined QA considerations necessary to document data quality (CL use, risk needs, use of past data) – Documented team members and coordination (CL, Risk Assessor, Geologist, CP, Field Crew). Helps Define the Quality Assurance Project Plan: – Need for blanks, duplicates and other QA required. – Acceptable QA levels and when corrective action is necessary. – What type of corrective action needed and how to document in QA narratives. – Qualifiers and their use

Quality Assurance Documents Project-specific QA (cited in VAP rules) – Field collection methods – Field personnel – Field QA parameters and samples – Field ‘Analytics’ (pH, Filtering, Cl) – Timeframes – Error/heterogeniety in sampling – Pack and ship SOP Laboratory QA (Required under VAP) – Analysis specific – Lab defined QA per analysis – Analytical SOP – Corrective actions – Sample preparations (prep and analysis) – Sample receipt and holding time – Certifications and special procedures

Do Your QA Expectations Match? It is recommended that a project have a QAPP or similar documentation to provide consistency between CP and CL. Your field team should make sure the QA requirements are consistent in the field and in the laboratory so no QA issues occur. The QAPP and SOP’s for the laboratory should meet the needs of the project and your DQOs. The laboratory should be certified for all parameters and methods you need under the VAP demonstrations. Make sure the affidavits document those analysis methods not certified in the affidavit.

Clear Expectations Laboratory – Appropriate certifications for requested analysis – Good QA for analysis – QA narrative or qualifiers contained in report – Lab should provide clear guidance on their expectations for samples – Communicate shipping needs – hours lab will receive samples and any holding time issues. Field Staff – Understand how to pack and ship all samples for all media – Use appropriate field methods for analysis – Identify issues seen in field to lab (heterogeneity, matrix; high concentrations) – Complete chain of custody correctly (note VAP samples) – Communicate delivery schedule to ensure holding times met.

Conclusions Ensure QA is a team approach with both CP and CL participating. Use QA documents, Chain of Custody, DQOs, and Conceptual Site Models to document the project needs and responsibilities for the entire team. Make sure everyone is on the same page to ensure success!