Quality Control for Regulators and Consultants: Laboratory Methods
Miller, William P.
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Measurements made as part of environmental assessment and monitoring activities are subject to both random and systematic errors (bias) that can reduce data quality and influence sound project conclusions. Federal quality assurance standards are seldom applied to smaller state and private environmental projects. Many of the potential errors in such projects arise from poor quality control (QC) during sample preparation and analysis in the lab, and from failure of project managers to request and evaluate QC data. Basic sample set preparation can detect the presence of systematic error, and can be used to quantify the level of random error in a set of measure- ments. Recommendations are given for types of QC samples to include with data sets, and kinds of information to request from in-house or contract analytical laboratories.