WORK PLANS - Laserfiche WebLink

Home Browse Search

Programmatic Sampling and Analysis Plan Project Number:60657245 RPD (percent, %) = 100 x I S-D (S+D)/2 Where: S = concentration of an analyte in a sample D = concentration of an analyte in a duplicate sample See Table 2.3 for accuracy limits. Accuracy: Accuracy is a measure of bias in a measurement system. The closer the value of the measurement agrees with the true value, the more accurate the measurement. This will be expressed as the percent recovery(%R)of a surrogate, laboratory control sample (LCS), or matrix spike (MS)analyte or of a standard reference sample, and is defined as follows: %R =A-B x 100 C Where: A= measured concentration of analyte in a spiked sample B = concentration of analyte in an unspiked sample C = known concentration of spike added See Table 2.3 for accuracy limits. Representativeness: Representativeness is a qualitative parameter, which expresses the degree to which sample data accurately and precisely represents a characteristic of a population, parameter variations at a sampling point, or an environmental condition. The design of and rationale for the sampling program (in terms of the purpose for sampling, selecting the sampling locations, the number of samples to be collected, the ambient conditions for sample collection, the frequencies and timing for sampling, and the sampling techniques) ensures that the environmental condition has been sufficiently represented. Completeness: Completeness is a measure of the number of valid measurements obtained in relation to the total number of measurements planned. The closer the numbers are, the more complete the measurement process. Completeness will be expressed as the percentage of valid to planned measurements and will be calculated as follows: Completeness (%) = V x 100 P Where: V = number of valid measurements P = number of planned measurements The objective is to establish the quantity of data needed to support the investigation. This will be achieved by obtaining samples for the types of analyses required at each individual location, a sufficient volume of sample material to complete the analyses, samples that represent possible contaminant situations under investigation, and samples at critical data locations. Completeness will take into consideration environmental conditions and the potential for change with respect to time and location. The overall completeness goal is 90% for each sampling event. The effect of any rejected data on project objectives will be evaluated in order to assess the need for recollection or reanalysis of these samples. Comparability: Comparability is a qualitative parameter expressing the confidence with which one data set can be compared to another. Data sets will be considered comparable only when precision and accuracy are considered acceptable during data validation. Sample data will be collected and reported in order to be comparable with other measurement data for similar samples and sample conditions. This goal will be achieved through using the applicable laboratory, field, and/or contractor standard operating procedures (SOPs) to collect and then analyze representative samples and through reporting analytical results in appropriate and consistent AECOM 5