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Gross
versus Specific Analyses
Some
analyses are designed to detect specific radionuclides (specific
analyses) while other analyses are designed to measure
radiation from a large number of sources (gross analyses).
Specific
Analyses
Gamma emitting radionuclides are determined by specific
analyses using gamma spectroscopy, for example.
Gross
Analyses
Analyses for specific alpha and beta emitting radionuclides,
on the other hand, require more difficult and expensive
radiochemical analyses. In
environmental monitoring, low cost gross measurements can be
substituted for the more expensive specific analyses.
The gross analyses are generally made first to determine
the total amount of radioactivity, of a certain type, that is
present. The more
expensive specific analyses of beta- and alpha-emitting isotopes
are only made if the gross measurements are above background
levels. When gross
beta or gross alpha measurements are made, it simply means all
beta activity or all alpha activity is measured.
There is no distinction between which beta-emitting or
alpha-emitting isotopes are present, just how much beta or alpha
activity there is. Gross
measurements are used as a method to screen samples for relative
levels of radioactivity.
Uncertainty
in Detecting Radioactivity
All
measurements have associated uncertainties.
For radioactivity measurements, the uncertainty arises from
variations in detection equipment and analysis procedures, human
error, natural background radiation, counting uncertainty,
variances in the distribution of the compound targeted for
analysis in the media being analyzed, and other sources.
Counting
uncertainty is reported with radioactive analyses.
This uncertainty exists because radioactive atoms
disintegrate in a random way.
That is to say, not all of the particles/energy released
strike the detector. This
means that if
the
number of radioactive disintegrations from one sample are counted
multiple times, each for the same duration, that number will vary
around some average value. Background
radiation makes this true even for a sample that has no
radioactivity. If a
sample containing no radioactivity was analyzed multiple times,
the result should vary around an average of zero.
Therefore, samples with radioactivity levels very close to
zero will have results that are negative values
approximately 50% of the time.
In order to avoid censoring data, these negative values,
rather than “not detectable” or “zero,” are reported for
radionuclides of interest. This
provides more information than merely truncating to the detection
limits for results near background activities and allows for
improved statistical analyses and measures of trends in the data.
Confidence in Detections
There
are two main types of errors that may be made when reporting
levels of contaminants:
- Reporting
something as not present when it actually is, and;
- Reporting
something as present when it actually is not.
It
is the goal of the ESER program to minimize the error of saying
something is not present when it actually is.
To do this, a two standard
deviation (2s) reporting level
is used.
In a distribution of analysis results for one sample, the
average analysis result, plus or minus (±)
two standard deviations (2s) of that average, approximates the 95%
confidence interval for that average.
When a sample analysis result is greater than 2s from zero,
we have about 95% confidence the value came from a distribution
with an average greater than zero.
The uncertainty of measurements in this report are denoted
by following the result with a “±”
2s uncertainty term and all results that are greater than 2s from
zero are reported in the text.
By
using a 2s value as a reporting level (i.e. reporting results that
are greater than two times their uncertainty), we are controlling
the error rate for saying something is not there when it
is, to less than 5% (we have 95% confidence the value is greater
than zero).
However,
there is a relatively high error rate for false detections
(reporting something as present when it actually is not) for
results near their 2s uncertainty.
This is because there is variability around zero for
samples with no radioactivity which may substantially overlap the
variability around the sample result (see Figure 5).
Variability associated with current analysis techniques were used
to calculate the level at which we are 95% certain the sample
results is greater than the distribution of values for a sample
with no radioactivity. This level is known as the minimum detectable activity
(MDA). When sample net
results are greater than the MDA (Figure 6), we have 95%
confidence the results are not false detections. The
MDA per sample weight or volume is called the minimum detectable
concentration (MDC). All
results with measured levels greater than the MDC are highlighted
in ESER quarterly reports.
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