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The New MDL

Wednesday, Aug 16, 2017

What is the MDL?

The Method Detection Limit (MDL), as used in environmental analysis, is the lowest result from a test method that can reliably be distinguished from a blank. It can be thought of as the lowest result that really means that the analyte is actually present in the sample – lower results are potentially due to random noise or background contamination.

How was the old MDL determined?

The MDL procedure was originally established in 1984, and is calculated as the 99th percentile Students t distribution with a minimum of 7 replicates:

MDL = [Standard deviation of spike replicate results] x [Student’s t for n-1 replicates]

The 99th percentile Student’s t constant where n = 7 replicates is 3.14.

Why was a change needed?

The old MDL procedure makes the assumption that results from blanks are a normal distribution centered around zero. As instruments and methods become more sensitive, it becomes more likely that blank results have a positive bias relative to zero. If this is the case, the calculated MDL will be too low and many false positives will occur. The old MDL is also flawed since usually all the replicates are determined together resulting in a tighter variance than would be expected over time.

How does the new MDL fix these problems?

The new MDL is based on the same underlying principles, but includes a detection limit determined directly from blanks. This includes the mean of the blanks so that any persistent blank bias is addressed. The new MDL also requires that the replicates be determined over time, not all in one batch.

Where can I find out more about the new MDL?

The MDL procedure is included in the Methods update rule and is available on EPAs web site:


The rule is expected to be published in the Federal register around the start of September, after which there will be a 30 day implementation period. TestAmerica will provide a Webinar giving details of the procedure on September 19th.

For Further information on the New MDL, please contact Dr. Richard Burrows.


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