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OBSP home Data Tables Time Series Charts Reports Glossary

SCOPE
The Organic Blind Sample Project (OBSP) of the Branch of Quality Systems (BQS) assesses the operational performance of organic analytical methods used for determining water-quality parameters for the USGS - National Water Quality Laboratory (NWQL) by means of blind submissions of Quality Assurance (QA) samples. The assessments identify not only the baseline performance capabilities of the methods in the Organic Chemistry Program, but also identify strengths and weaknesses in the current system of bench-level quality and process control. The information provided by the OBSP assists the NWQL in detecting and correcting problems in the analytical processes. The information also can aid the NWQL data user in interpreting their environmental data over time.

IMPLEMENTATION
The OBSP submits blind QA samples of known chemical composition to the Organic Chemistry Program at the NWQL to evaluate analytical methods used at the laboratory. These samples are termed "blind" because the chemical composition is unknown to the NWQL analyst. Results of the blind QA samples reflect the actual performance of the laboratory processes because the blind QA samples are treated the same as environmental samples through the entire process from login (receipt of samples) to data output (sample results).
The annual blind QA blind sample submission rate is based on the environmental sample load of the previous year. Generally, the OBSP submits blind QA samples to the NWQL at a rate of 3-5% of the environmental samples in a water year with a minimum of 24 samples and a maximum of 100 samples submitted in a water year. OBSP submits blind QA samples for analysis for approximately 20 different organic analytical methods.
Once the number of blind QA samples to be submitted for a method is determined, then a plan for obtaining variability data is initiated and named as the precision plan. The precision plan outlines the randomized sample submissions throughout the year. The certified reference materials used to prepare the blind QA samples are randomized as well preventing the NWQL analyst from becoming familiar with a particular certified reference material. The precision plan also describes the submission of blind QA samples in terms of different concentration levels. Up to four concentration levels may be used to cover the entire analytical range of a method. The lowest concentration level approximates the long-term method detection level (LT-MDL) of the analyte in the method and is used to monitor for false negatives in low-level methods. Some of the OBSP blind QA samples do not contain all of the analytes in a method; this enables OBSP to monitor for false positive occurrences.

ASSESSMENT
The results of the blind sample submissions are assessed annually and quarterly. On an annual basis OBSP will post time series charts for every method and analyte OBSP reviews. The time series charts will show the recoveries of the blind QA samples over time and are to evaluate method performance over time. Variations in method performance may be reflected in the environmental samples analyzed by this method, so the charts should provide valuable information to projects that interpret organic analytical data. A report describing the changes in the method performance for a period of time will be posted as the cumulative summary report and will be updated annually. On a quarterly basis OBSP will update the time series charts to include the most recent data and provide a quarterly report that will document only the most recent changes in the blind QA results.

PRODUCTS
Statistical Data Tables - The statistical data tables provide cumulative blind QA data information for all concentration ranges combined for every analyte for every method OBSP assesses since January 1996.
Charts
Time Series Charts The time series charts provide OBSP recovery information for every analyte at different concentrations for every method OBSP assesses since January 1999. The charts also exhibit a Locally Weighted Scatterplot Smoothing (LOWESS) line. This line is used to help observe patterns and trends of the data over time. The time series charts also show bias and variability of the OSBP data.
Box Plots The box plots show the distribution of the blind organic QA data for different concentration ranges. The plots also show outliers and quartile ranges of the recovery data. The box plots show individual analytes in every method that OBSP assesses and also displays some descriptive statistics since January 1996.
False Positive and False Negative Charts The false positive and false negative charts provide OBSP result concentration and expected concentration information respectively for every analyte for every method OBSP assesses since 2005. The charts exhibit a reporting level line. All data is provisional and may change if the OBSP deems necessary.
Recovery vs Concentration Charts The recovery versus concentration charts provide OBSP recovery inforamtion for every analyte at different concentrations for every method OBSP assesses since January 2001. The charts exhibit a median line. All data is provisional and may change if the OBSP deems necessary.
Summary Reports
Cumulative Method Reports
The cumulative method reports are primarily intended for the data users to aid in their interpretation of environmental data over time. All analytes listed in the cumulative method reports will have associated time series charts.
Quarterly Reports
The quarterly reports address recent changes in the method performance and is provided to the NWQL for their review and comment. The quarterly reports will be posted in January, April, July and October of each year.
Corrective Action Reports
Prior to 2003 the reports were considered corrective action reports. The OBSP assessed method performance on a sample by sample basis. The corrective action reports were provided to the NWQL for their review and comment.


Contact Information

Branch of Quality Systems Chief, Terry Schertz, 
tschertz@usgs.gov
BQS Chemist, Suranne Horodyski,   horodyski@usgs.gov
BQS Chemist, Delicia Beaty,   dbeaty@usgs.gov

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