Grab sampling validation

Few populations, however, meet the conditions for a true binomial distribution. Real populations normally contain more than two types of particles, with the analyte present at several levels of concentration. Nevertheless, many well-mixed populations, in which the population s composition is homogeneous on the scale at which we sample, approximate binomial sampling statistics. Under these conditions the following relationship between the mass of a randomly collected grab sample, m, and the percent relative standard deviation for sampling, R, is often valid. ... 

The basis for assessment of river quality is valid data, but the question of data validity is secondary to the fundamental question What is the purpose of the river quality assessment activity What questions are being asked In short the means are determined by the ends. If, for example, the intent of an assessment program is to ascertain compliance with law, then a fixed interval "grab sampling program could be established at various river system sites selected on the basis of established guidelines which are consistent with the... 

An extensive benchmark stndy has been carried ont in order to identify the optimal mass redaction principle(s) [6], This was achieved by assessing and validating the almost nniversally nsed mass redaction approach, grab sampling, as opposed to a comprehensive series of more advanced techniqnes and methods, 17 in total. All techniqnes and methods were tested with regard to a fall snite of qnality parameters, some scientihcally important, others related to cost and minimizing practical operating conditions and expenses. The most important merit of any mass redaction method is the ability to deliver an unbiased split of material with the smallest possible variation in repeated rnns snbject to the best possible accnracy. These two featnres are summed up in the TOS qnantitative measnre of representativeness. 

Occasionally attempts to justify a process analyzer are made on the basis that it will reduce the number of grab samples that need to be taken from the process to be analyzed, and therefore reduce the sample load on the QC lab. This is not usually a good justification for an on-line analyzer for two reasons (1) The reduction in lab analyses rarely offsets the cost of analyzer installation and operation (2) An on-line analyzer relies on high quality lab data for calibration, validation, and long-term model maintenance, so the reference method can never be eliminated entirely. 

Ideally, an on-line analyzer will be calibrated before it is installed in the process. It may be possible to accomplish this by calibrating it off-line with process grab samples and/or synthetic samples. It may be possible to install the analyzer in a lab-scale reactor, or in a semi-works or pilot plant. It may be possible to transfer to the on-line analyzer a method developed on an off-line analyzer or on another on-line analyzer (e.g. at a different plant site). However, sometimes none of these are possible and the analyzer will need to be calibrated on-line. The challenges of on-line model development (calibration) and validation, as well as approaches to dealing with them, are discussed below. For information related to calibration transfer issues, please see Chapter 12 of this book. 

Calibration models were developed using process grab samples. Each sample set was split in half randomly to give independent calibration and validation sample sets. The results for the best models are shown in Table 15.5. The real-time monitoring results as seen by the process engineers and operators are shown in Eigure 15.9. 

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