1. UCRL-VG-137402 This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract W-7405-Eng-48. DOE Analytical Services Program 2014 Workshop

2. Lawrence Livermore National Laboratory UCRL-VG-134702 2  There was a site  At which three organizations decided to collect some samples for a radiological assessment  And split them  But the results didn’t come out quite as well as they had hoped...

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4. Lawrence Livermore National Laboratory UCRL-VG-134702 4  Split in the field between three organizations

5. Lawrence Livermore National Laboratory UCRL-VG-134702 5 Key questions for 239+240 Pu:  Is it above 2.5 pCi/g? i.e., above a derived-from-risk screening level?  Is it above 0.01 pCi/g? i.e., is it above “fallout background”? More precisely, is it above a value being used to represent an upper limit for fallout background?  How did the Pu reach the site?

6. Lawrence Livermore National Laboratory UCRL-VG-134702 6  Total dissolution  Chemical separation  Alpha spectroscopy  Lab A and B results were surprisingly different  Lab A and C good agreement

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10. Lawrence Livermore National Laboratory UCRL-VG-134702 10  Data are obviously of different quality  Organization A didn’t really understand why Noted that counting times were different Speculated about particulate nature of radionuclides in soil  Noted that some Lab B QC showed large variation  Organization A wrote a report, used uncertainty- weighted average of Lab A and B results

11. Lawrence Livermore National Laboratory UCRL-VG-134702 11  Was not involved in any way in 1995  Reviewed data, released a draft report for public comment  Used only Lab B results Counted number of samples above 0.01 pCi/g  Reached a very different conclusion about how the Pu reached the site

12. Lawrence Livermore National Laboratory UCRL-VG-134702 12  Based on Lab B results 13 of 19 above 0.01 pCi/g, ignoring uncertainty 6 of 19 above 0.01 pCi/g, considering uncertainty 13/19 = 68% = “throughout the site” = “air pathway”  Based on Lab A results 6 of 19 above 0.01 pCi/g, ignoring uncertainty 6 of 19 above 0.01 pCi/g, considering uncertainty 5 of the 6 located consistent with “sludge pathway”

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16. Lawrence Livermore National Laboratory UCRL-VG-134702 16  In order to exceed 0.01 pCi/g (the so-called “background”) Lab A needed 20 to 30 net counts Lab B needed 2 to 4 net counts  Is it valid to use Lab B results to make above/below background inferences? Not always Lab B results are much more variable at low levels Example: 0.0105 ± 0.0189 with MDC = 0.0438 was considered evidence of being above 0.01 pCi/g by Organization D

17. Lawrence Livermore National Laboratory UCRL-VG-134702 17  Instructions to Lab A: MDC should be 0.005 pCi/g or less This is a surrogate for “good performance at low levels”  Instructions to Lab B: “Tell us if it is above 2.5 pCi/g” This implies that large variability at low levels is acceptable

18. Lawrence Livermore National Laboratory UCRL-VG-134702 18  Lab A 5 gram aliquot 24 hour counting time  Lab B 0.5 gram aliquot 16 2/3 hours counting time  This explains why the two labs have such different results on many samples, and why Lab B results are so variable  Aliquot size is the more crucial of these

19. Lawrence Livermore National Laboratory UCRL-VG-134702 19 From Pitard, F., 1993 as reproduced in Myers, J., 1997 Don MacQueen: Note, demonstrate concept visually here using bag of granola, with raisins as the ‘contaminant’ Don MacQueen: Note, demonstrate concept visually here using bag of granola, with raisins as the ‘contaminant’

20. Lawrence Livermore National Laboratory UCRL-VG-134702 20  Lab B’s results do not measure small differences near “background” precisely, but this was not well understood Most especially, by Organization D! — Based on their draft report, Organization D did not attempt to understand DQOs, or differences between data sets Organization A did not understand well enough soon enough to effectively discuss D’s interpretation  Organizations A, B, and C had little or no discussion of DQOs Organizations B and C did not raise the DQO issue when it would have helped  Organization A’s 1995 report would have been better if they had understood the DQOs more thoroughly

21. Lawrence Livermore National Laboratory UCRL-VG-134702 21  All of the labs met their clients’ requirements  It is the client’s responsibility to understand and share DQOs  But, Lab B could have helped Lab B was aware that comparisons with 0.01 pCi/g were of interest Lab B project manager did make comparisons with 0.01 pCi/g in the analytical report cover letter

22. Lawrence Livermore National Laboratory UCRL-VG-134702 22  When splitting samples, clients should insist on the same data quality objectives. Organization A did not do this.  If the DQOs are not the same, make sure everyone understands the limitations (and document them).

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24. Lawrence Livermore National Laboratory UCRL-VG-134702 24  Data users were not sufficiently aware of the 1995 data quality objectives  Data users did not understand the limitations of Lab B’s 1995 results (limits that were specified by Organization B and met their needs)  Misuse of Lab B’s results enabled Organization D to introduce a huge “red herring” into the site assessment process Because of failure to consider the data quality objectives

25. Lawrence Livermore National Laboratory UCRL-VG-134702 25  The client’s responsibility does not end at the lab’s front door  Good scientific interpretation of a number requires full knowledge of how the number was generated  Coordinate, Cooperate, COMMUNICATE!