Training and consultancy for testing laboratories.

Why uncertainty is important in analytical chemistry?

Why measurement uncertainty is important in analytical chemistry?

Conducting a laboratory analysis is to make informed decisions on the samples drawn.  The result of an analytical measurement can be deemed incomplete without a statement (or at least an implicit knowledge) of its uncertainty.  This is because we cannot make a valid decision based on the result alone, and nearly all analysis is conducted to inform a decision.

We know that the uncertainty of a result is a parameter that describes a range within which the value of the quantity being measured is expected to lie, taking into account all sources of error, with a stated degree of confidence (usually 95%).  It characterizes the extent to which the unknown value of the targeted analyte is known after measurement, taking account of the given information from the measurement.

With a knowledge of uncertainty in hand, we can make the following typical decisions based on analysis:

• Does this particular laboratory have the capacity to perform analyses of legal and statutory significance?
• Does this batch of pesticide formulation contain less than the maximum allowed concentration of an impurity?
• Does this batch of animal feed contain at least the minimum required concentration of profit (protein + fat)?
• How pure is this batch of precious metal?

The figure below shows a variety of instances affecting decisions about compliance with externally imposed limits or specifications.  The error bars can be taken as expanded uncertainties, effectively intervals containing the true value of the concentration of the analyte with 95% confidence.

We can make the following observations from the above illustration:

1. Result A clearly indicates the test result is below the limit, as even the extremity of the uncertainty interval is below the limit,
2. Result B is below the limit but the upper end of the uncertainty is above the limit, so we not sure if the true value is below the limit.
3. Result C is above the limit but the lower end of the uncertainty is below the limit, so we are not sure that the true value is above.
4. What conclusions can we draw from the equal results D and E? Both results are above the limit but, while D is clearly above the limit, E is not so because the greater uncertainty interval extends below the limit.

In short, we have to make decisions on how to act upon results B, C and E.  What is the level of risk that can be afforded to assume the test result is in conformity with the stated specification or in compliance with the regulatory limit?

By making such a decision rule, we must be serious in the evaluation of measurement uncertainty, making sure that the uncertainty obtained is reasonable.  If not, any decision made on conformity or compliance will be meaningless.

This site uses Akismet to reduce spam. Learn how your comment data is processed.