A METHOD TO ASSESS ANALYTICAL UNCERTAINTIES OVER LARGE CONCENTRATION RANGES WITH REFERENCE TO VOLATILE ORGANICS IN WATER

The uncertainty associated with a volatile organic concentration measu rement is a function of variability and bias introduced at the various levels of sampling handling: collection, storage, and analysis. Durin g the past decade, sampling materials and the development and/or impro vement of sampling protocols have been the subject of considerable res earch activity. As a result, in cases of samples properly handled, the analytical variability can be the dominant source of uncertainty in a given concentration value. Here analytical variability refers to any error that might arise during analysis, including the detector respons e error and any sample handling errors common to both standards and sa mples. This can be a particular concern for field analyses by gas chro matography (GC). Well-established statistical methods are available to estimate analytical uncertainty from linear calibration curves, but t hese methods are poorly suited for the analysis of volatile organics b ecause organic samples frequently require instrument calibration (usua lly GC) over several orders of magnitude in concentration. If a single linear calibration curve is used to determine sample concentrations a nd uncertainties, then unrealistically large uncertainties may be assi gned to low concentration samples. However, the methods can be adopted for extended concentration range calibration curves by breaking the o verall calibration line down into smaller sub-calibration lines that s pan smaller ranges. These can then be examined and used selectively to determine concentrations with more appropriate uncertainties attached . The method of multiple calibration line analysis described here is s uitable for programming with any high-level computer language. It can be used to calculate meaningful analytical uncertainty values for any substance analyzed over a wide range in concentrations (i.e., an order of magnitude or more).