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A1.4.3 Sensitivity - Detection Limits <br /> The method detection limit (MDL) is the minimum concentration of an analyte that can <br /> be identified using a specific method. The laboratory usually determines the MDL by <br /> calculating the standard deviation of the results of seven replicate spike sample <br /> analyses and multiplying by three, using reagent water as a sample. The MDL is an ideal <br /> detection limit when there is no background laboratory contamination and the sample to <br /> be analyzed is a clean sample free of matrix effects. MDLs, also known as the method <br /> quantitation limit, are determined using reagent water as the sample. MDLs are not field <br /> sample specific and do not vary with the sample preparation or dilutions required for <br /> each field sample analyzed. The MDL is the instrument detection limit (IDL) plus <br /> adjustments for typical sample preparation techniques. <br /> Sensitivity for this project will be evaluated against the specific project MDLs and internal <br /> standard recoveries. Quantitation limits may be affected by matrix interferences. If a <br /> dilution is required, the lowest dilution necessary to bring the compound within range <br /> should be performed in all cases. In cases where the specified detection limits (or project- <br /> specific reporting limits) are not achieved, the usability of the data will be evaluated by <br /> LFR. <br /> A1.4.4 Representativeness <br /> Representativeness expresses the degree to which the sample data accurately and <br /> precisely represent the media being sampled at a specific location at a specific time. <br /> One measure of representativeness is field duplicate precision. If field duplicate <br /> precision criteria are not met, LFR will determine usability of the associated results and <br /> qualify the data based upon best professional judgment. Poor field duplicate precision <br /> may be an indication of sample heterogeneity or poor sampling. <br /> A1.4.5 Comparability <br /> Comparability is the confidence with which one data set can be compared to other data. <br /> The objectives for this program are to produce data with the greatest degree of <br /> comparability possible. Comparability will be achieved using standard methods for <br /> sampling and analysis, reporting data in standard units, and using standard and <br /> comprehensive reporting formats. <br /> A1.4.6 Completeness <br /> Measurements of completeness (C) can be defined as the ratio of usable measurements <br /> obtained to the total number of planned measurements for an activity. Completeness <br /> can be defined as: <br /> (Number of usable data points) <br /> C = x100 <br /> (Total number of planned data points) <br /> Sampling Plan for Small Waste Disposal Areas(final).doc A-6 <br />