1.
Do ball-mill (BM) and <100 mesh (sieved) soil fractions contain
equal plutonium concentrations?
2.
If the answer to Question 1 is no,
then what is the error in
estimating inventory by using concentrations from sieved aliquots
in place of those from BM fractions?
3.
If additional information on the weights and concentrations of
the <100 mesh and >100 mesh fractions is available, can they be
used to "correct" the <100 mesh and >100 mesh concentrations to
what would be expected if BM fractions had been analyzed?
Throughout this discussion, it is assumed that BM fractions are the
preferred fraction to be analyzed for plutonium and if differences in
plutonium concentrations between BM and sieved aliquots are found,
then the proper approach is to try and adjust the results on sieved
aliquots to those obtained on BM fraction aliquots.
The largest single body of data available to investigate Question 1
is given in its entirety in Table 4.
These are 239-2405,, concentra-
tions (nCi/g dry) in BM and sieved soil fractions from profile samples
collected on the TTR.
The library number in Column 1 defines a soil
sample from which LFE was sent a 10-gram aliquot from the BM fraction,
and LASL a 50-gram or larger aliquot from the sieved fraction.
The
data are tabulated by depth of soil sample and ordered from largest
to smallest LASL plutonium concentrations within each depth.
The
most striking feature of these data are given by the ratio of LASL to
LFE mean concentrations in the last columm.
For each soil depth,
this ratio is seen to decrease as the LASL average concentration
decreases.
That is, the relationship between BM and sieved Pu concen-
trations is not a constant over all levels of contamination.
LASL
results are up to 20 or 25 times greater than reported by LFE for the
highest sieved concentrations.
Note, however, that the ratio is less
than 1 for the lower LASL (sieved) concentrations, so that for these
low-level samples, LFE is reporting higher concentrations than LASL.
The logs of the mean data (Columms A and B in Table 4) are plotted in
Fig. 9 and a linear regression equation is fitted.
It is clear
that the fitted line is not coincident with the line that should
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