Question You see a trend or pattern in your environmental data that you didn’t expect. How might you explain this? 2

Blind Samples What is a “Blind” sample? A blind sample is a quality-control sample whose composition and origin is unknown except to those who are submitting the sample. It is disguised to appear like a regular environmental sample to the laboratory. Its purpose is to allow a realistic and uncensored measure of bias and variability of the entire laboratory process. 3

Blind Samples How do blind-samples results help data-users assess their environmental sample results from the NWQL? Blind samples are treated the same as environmental samples and are designed to capture the same sources of variability as environmental samples  Inorganic-from login through NWIS  Organic-from login through StarLIMS Blind samples and on-line QC samples are different 4

Blind Samples How do blind-samples results help data-users assess their environmental sample results from the NWQL? User accessible data sets  Blind-sample results are retrieved, posted, and available to the data-user Inorganic – Within 1-3 days of release from the NWQL Organic – Data reviewed when available. 5

Current products that help aid in data interpretation Time-series charts/box plots  To observe bias and variability over time Recovery versus concentration charts  To assess recovery and variability at different concentration ranges Blind-blank/false positive/false negative charts  To observe blank contamination and assess reporting levels 6

Current products that help aid in data interpretation Raw data Custom data packets Data-quality assessment reports 7

Time-series charts: IBSP 8

Question You see a trend or pattern in your environmental data that you didn’t expect. How might you explain this? 9

Time-series charts: IBSP 10

Time-series charts: IBSP 11

Time-series charts: OBSP 12

Time-series charts: OBSP 13

Box Plots: OBSP 14 BQS ORGANIC BLIND SAMPLES DETERMINATION: CYANAZINE, SCHEDULE: 2033 TESTIDCODE: 04041GCM35, MEASURED IN MICROGRAMS PER LITER 04/03/08 TO 12/22/11 Open Data Set

Recovery vs. Concentration: OBSP 15

Question You’re seeing unexpected results in your blank/low-level environmental sample data. How can you sort out these issues? 16

Blind-blank charts: IBSP ICPMS, Nickel, Water, Filtered, collision Test ID: 01065PLM10, Labcode: 3130 Open DataSet 17

Blind-blank charts: IBSP ICPMS, Aluminum, Water, Filtered Test ID: 01106PLM43, Labcode: 1784 Open DataSet 18

False positive charts: OBSP 19

False positive charts: OBSP 20 False Positives Listing for DIETHYL PHTHALATE

False positive charts: OBSP 21 False Positives Listing for 3-Chloropropene

Question You expected to see a certain compound in your sample and instead you received a < (less than) as your result. Are the concentrations in your samples too low to be quantified? 22

False negative charts: OBSP 23

False negative charts: OBSP 24 False Positives Listing for CHLORAMBEN, METHYL ESTER False Negatives Listing for CHLORAMBEN, METHYL ESTER

Question You think quality-control charts are OK, but you would really just like to have the data to work with it yourself. How can you easily obtain a subset of the QC data in a user-friendly format? 25

Raw data: IBSP/OBSP ICPMS, Nickel, Water, Filtered, collision Test ID: 01065PLM10, Labcode: 3130 Open DataSet 26

Raw data: IBSP/OBSP ICPMS, Nickel, Water, Filtered, collision Test ID: 01065PLM10, Labcode: 3130 Open DataSet 27

Raw data: IBSP/OBSP 28

Branch of Quality Systems bqs.usgs.gov Inorganic blind-sample project  Ted Struzeski Organic blind-sample project  Suranne Stineman 29

Question The website can be overwhelming with so many QC charts for so many parameters. Can you just have a summary of suspected data-quality issues? 30

Data-quality assessment reports Inorganic: Every-other-month Organic: Data reviewed when available Data Quality Assessment Report - August Analyte NameOBSP NotesNWQL CommentCorrective Action Chloramben methyl ester The most recent two points are recovering slightly higher than the recoveries seen prior to these samples. The two samples are from two different OBSP spike mixes. Chloramben methyl ester has an interference peak which can cause it to be more difficult to quantitate at lower concentrations. The calculated LTMDL FY2012 has increased from 0.05 to 0.10 µg/L due to the presence of the interference. The LT-MDL was raised in FY12 for this compound. Also mentioned in the November 2010 report this analyte showed some false negatives all coming from one vendor. Since then, there have been multiple false negatives from 3 more different vendors. This is likely due to the problems in quantitation of this compound at low levels due to the presence of the interference. 31

Data-quality assessment reports 32

Moving Forward… Inorganic Blind Sample Project Method-to-method charts  To assess data-quality between methods Method A versus method B Filtered versus unfiltered Old method versus new method Concentration-dependent charts  To assess concentration-dependent bias and variability Percent RSD charts  To assess variability at a given concentration  To characterize overall method variability 33

Inorganic Blind Sample Project Potential Future Products  Analyte by different methods: ICP versus DA 34

Inorganic Blind Sample Project Potential Future Products  Analyte in different phases: filtered versus unfiltered – Example 1 35

Inorganic Blind Sample Project Potential Future Products  Analyte in different phases: filtered versus unfiltered – Example 2 36

Inorganic Blind Sample Project Potential Future Products  Analyte by different methods: old method versus new method 37

Inorganic Blind Sample Project Potential Future Products  Concentration-dependent recovery charts 38

Inorganic Blind Sample Project Potential Future Products  % Relative Standard Deviation chart 39

Math! %RSD = (SD/mean)*100 SD = %RSD(mean)/100 Let %RSD = 3 and concentration = 20 mg/L SD = 3(20)/100 SD =

41 Analyte in multiple methods To assess data-quality performance across multiple methods Old method versus new method Chart of expected and reported concentration versus time To assess concentration-dependent bias over time Annual false positive and false negative summaries To assess potential contamination issues or interferences To assess confidence in low-concentration results Plot some “user defined limits” on the various charts To assess how blind-sample results compare to these limits Moving Forward… Organic Blind Sample Projects

Got Caffeine… 42

43 Potential Future Products  Analyte by several different methods Organic Blind Sample Project

44 Potential Future Products  Analyte by several different methods Organic Blind Sample Project

Potential Future Products  Expected and reported concentration versus time 45

April 08, 2010 to Jan 19, 2012 LS 1383TestIDCAS## spikedFalse negative# not spikedFalse positives Acenaphthylene34200GCM Acenaphthene34205GCM Anthracene34220GCM Benzo[b]fluoranthene34230GCM Benzo[k]fluoranthene34242GCM Benzo[a]pyrene34247GCM bis(2-Chloroethyl)ether34273GCM bis(2-Chloroethoxy)methane34278GCM bis(2-chloroisopropyl) ether34283GCM Butylbenzyl phthalate34292GCM Chrysene34320GCM Diethyl phthalate34336GCM Dimethyl phthalate34341GCM Organic Blind Sample Project Potential Future Products  False positives and false negatives summary table

= Recovery range (50% to 150%) Organic Blind Sample Project 47 Potential Future Products  User defined limits on an existing time series chart

Moving Forward… Inorganic & Organic Blind Sample Projects Modification to format of existing data-quality assessment reports Look into NWIS toolbox for IBSP and OBSP data analysis QA upcoming organic tissue and sediment methods Use more different types of matrices for the inorganic blind samples Provide information about the matrix for the inorganic blind samples 48

Moving Forward… Inorganic & Organic Blind Sample Projects Requesting input from the data users  What do you want to see?  What would be useful to you? 49

Branch of Quality Systems bqs.usgs.gov Inorganic blind-sample project  Ted Struzeski  bqs.usgs.gov/ibsp/   Organic blind-sample project  Suranne Stineman  bqs.usgs.gov/obsp/  