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E Data i • y.As ses sm. t sNot J J6ust Pushing Paper Rigorous quality assurance is the best way to guarantee the reliability of data from laboratory analysis. By Taryn G. Scholz,. Louise McGinley and Donald A. Flory ecently, the environmental arena has expanded dramati- LAcally, pushing technology to new limits and encouraging innovation in an ever-changing regulato- ry atmosphere. One environmental issue dominates the science of identifying and quantitating regulated chemicals or lab- oratory analysis. Data from laboratory analysis is essen- dal to risk assessments, extent of contam- ination studies, feasibility studies and compliance monitoring. A tremendous amount of resources is expended, based on laboratory analytical results. This, plus the legal aspects surrounding environ- mental issues, makes it imperative that the laboratory results be "of known and acceptable quality for the intended use. Quality Assurance Quality assurance (QA) is the total inte- grated process for assuring the reliability and defensibility of decisions based on analytical data. The process is extremely rigorous due to the complexity of labo- ratory analyses; the number of different analytical methods, each with different criteria; various agency standards for val- idating results; the abundance of labora- tories, each with varying strengths and weaknesses; and the diverse scope of measurement purposes. In other words, it takes a lot of paper pushing. Few will argue that it is a necessary evil to ensure laboratory data is legally defensible. However, it is also necessary 30 1 Environmental PROTECnON to ensure data is technically valid -2 de- termination that is interpretive and re- quires a thorough understanding of ana- lytical chemistry. Many data users do not realize that it is the norm, rather than the exception, for laboratory data to have some bias. If not accounted for, the bias can lead to disastrous decisions. It doesdt necessarily take a laboratory failure to introduce bias. In many cases, bias is introduced solely by the sample matrix, even when the laboratory follows the analytical method exactly. Of course, compliance monitoring_ laboratory data should never be blindly accepted—laboratories today are more automated, which means less reliance on experienced analytical chemists. Laboratory QA reviews are generic for all clients and often inadequate and not suited to a particular use. The U.S. Environmental Protection Agency guide- lines make it clear the data user has the final responsibility for the dare quality: "If the data are collected by a contract laboratory, it is the permittee's responsi- bility to see that all of the requirements in the method are met by the contract labo- ratory and that all (associated) data are provided."—EPA Guidance on Eval- uation, Resolution, and Documentation of Analytical Problems Associated with Compliance Monitoring. Data Quality Assessment The fundamental principle of quality as- surance is data quality assessment. Third -parry data quality assessment is the best way to ensure laboratory data is legally defensible and technically valid. It eliminates potential conflicts of inter- est and is more efficiently and reliably performed by specialists. A complete data quality assessment includes: • Data validation, • Data qualificarion/review (flagging), • Suitability determination, • Data rescue and • Data validation. Quality control (QC) is a set of mea- sures within a sample analysis merhodol- September 1996