a comparison of techniques used to evaluate low level radiochemical data theresa l. parrotte, scott...
TRANSCRIPT
A Comparison of Techniques Used to Evaluate Low Level
Radiochemical Data
Theresa L. Parrotte, Scott C. Moreland,
J. Stan Morton Ph.D., James B. Westmoreland email: [email protected]
General Engineering Laboratories, LLCRadiochemistry Division, Charleston, SC 29407
• General Engineering Laboratories (GEL). Offers a complete range of environmental testing
•Organics
•Inorganics
•Radiological
•Bioassay
•Consulting
Introduction
• Radiochemistry laboratories provide data in the form:
result + uncertainty & detection limit
• Data users may need to make a “detection decision” based on this data
• The method used to make this decision must be carefully selected or the results can be misleading
Detection Limit PrincipleSignal to Noise
Image courtesy of the AccuNet/AP Photo Archives ©2000
How do we calculate the minimum signal distinguishable from the noise?
• “Math is the Language of Science” -unknown
• Statistical Models are useful to predict method sensitivity (signal to noise threshold)
• Why use Statistics?– Radiological measurements are random in nature
– We must make estimates based on a single measurement
Poisson Distribution
0.000
0.200
0.400
0.600
0.800
1.000
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
95% confidence level
tsKtbts
tsBDLC
*
)1)((*645.1
Decision Level Concentration (Critical Level)
Where: B = background count rate (cpm)
ts = sample count time (minutes)
tb = background count time (minutes)
K = constant used to convert to activity/unit
Poisson Distributions
0.000
0.200
0.400
0.600
0.800
1.000
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32
DLC
MDA
Minimum Detectable Activity
tsKtbts
tsBMDA
*
)1)((*29.33
Where: B = background count rate (cpm)
ts = sample count time (minutes)
tb = background count time (minutes)
K = constant used to convert to activity/unit
3 Approaches Evaluated
• Comparison of the Result with the Decision Level Threshold (DLC) (a.k.a critical level)
• Comparison of the result with the 2 sigma total propagated uncertainty (TPU)
• Comparison of the Result with the Minimum Detectable Activity (MDA)
Total Propagated Uncertainty
K
RERERENTPU
recalieff ...)(* 22222
Where: = variance of the net sample count rate (cpm)
N = net sample count rate
REeff = relative error of the detector efficiency
REali = relative error of the aliquot
RErec = relative error of the recovery
K = constant to convert to activity/unit
Sample Preparation: A Key to Low Level Detection
Sample Counting:Backgrounds, efficiencies and sample count
times are critical
Example DataResult 2*TPU DLC MDA
Am-241 0.023 0.061 0.035 0.161
Is the result less than the DLC? Yes
Is the result less than the MDA? Yes
Is the result less than 2*TPU? Yes
Example DataResult 2*TPU DLC MDA
Pu-239 0.008 0.011 0.006 0.023
Is the result less than the DLC? No
Is the result less than the MDA? Yes
Is the result less than 2*TPU? Yes
Example DataResult 2*TPU DLC MDA
Th-230 0.132 0.044 0.012 0.200
Is the result less than the DLC? No
Is the result less than the MDA? Yes
Is the result less than 2*TPU? No
Summary Data
1639 records were evaluated with result < MDA
• 1366 were also less than the TPU (83%)
• 927 were also less than the DLC (57%)
• 273 were less than the MDA but greater than the DLC and the 2*TPU level (17%)
Activity Summary
0
0.1
0.2
0.3
0.4
0.5
1 4 7 10 13 16 19 22 25 28 31 34 37 40
Replicates (increasing activity)
Act
ivit
y
DLC
MDA
Result
TPU
0.29
0.14
Result<DLC Result<TPU Result<MDA
Conclusions
• Comparing results to MDA alone is not
recommended for making a detection decision
• Comparing results to DLC is recommended
but can be problematic at low background
count rates (alpha spectrometry)
• Comparing the result to the 2*TPU can be
helpful in detection decision making
