1. Quality Assurance/ Quality Control
Nate Herbst
Southern Ute Indian Tribe

2. Intro to QA/QC Getting good data requires many different steps
Data quality objectives (DQOs) developed
DQOs for ozone being developed
Measurement quality objectives (MQOs) for ozone exist
Analysis begun (after correct calibration)
QC checks performed
QA conducted

3. Data Quality Objectives (7 steps)
State problem
Define why monitoring is needed
Create team and purpose
Identify decision
What decision will be made with data?
Identify decision inputs
What data necessary to make decision?
Define boundaries
What are study area boundaries?

4. Data Quality Objectives (cont.)
Develop decision rule
What conditions will require action (action level)?
Specify decision error limits
What margin of error is allowable
Optimize monitoring design
Develop most cost-effective method of reaching DQOs
EPA hasn’t yet defined DQOs for ozone analysis

5. DQOs (cont.) Diagram of DQO steps
(Diagram courtesy of U.S. Department of Energy – DQO homepage)

6. Measurement Quality Objectives (MQOs)
Thanks to Melinda Ronca-Batista (ITEP)
EPA has ozone analysis MQOs
Use these in element 7 of your QAPP
MQOs in a nutshell
Shelter temperature kept between 20-30oC ± 2oC
Analyzer must be reference or equivalent method
Lower detectable limit 0.01ppm, noise 0.005ppm
Data completeness 75% of hourly values between 9:01am and 9:00pm (for the ozone season)
Transfer standard certification ±4% or 4ppb (whichever is greater)

7. MQOs (cont.)
Transfer standard re-certification to primary std.dev 1.5%
Local primary standard certification ±5% of reference
EPA reference photometer regression slope 1.00 ± 0.01
Zero air free of O3 and anything that might react with O3

8. MQOs (cont.) Ozone analyzer calibration
Z/S check zero ±10ppb, span ± 15%
5pt calibration linearity error ±5%
Performance (NPAP) mean absolute difference ± 15%
Precision (quarterly) 95% CI < ±15%
Audits (annually) 95% CI < ±20%

9. Quality Assurance Project Plans (QAPPs)
Contain 24 “elements”
Element 7 is where MQOs go
Cut and paste from red book
Ensure data quality
Required by EPA
Developed by program approved by EPA
They must be followed!
No good if not followed

10. Documentation Document everything!!! Documentation in
Logbooks
Site folders
QA/QC field forms
Anywhere else you think is appropriate
QA/QC – document standard values and response

11. Documentation (cont.) Document repairs, checks, fine tunes
Document site conditions
Document everything that could ever be important
Write only in pen (black if possible)
Cross out errors with a single line

12. Linearity Slope = rise over run m = slope
b = intercept (where the trend-line crosses the Y axis)
r2 close to 1 shows correlation

13. Instrument Calibration
Measurements require point of reference
Measurement without standard is impossible
Calibration involves setting instrument to known level
Calibrations performed fairly regularly
When monitoring is begun
When repairs or maintenance are performed
When precision checks or audits show need
Calibrations must be done correctly

14. monitoring without calibration
Calibrations (cont.)
Calibration = setting analyzer to standard
Data only good within linear range (~ ppm)
Calibration followed by a 5-pt check
Analyzer must agree with standard at all 5 pts
Linearity error < 5%
See next slide on linearity
Monitoring begins after calibration
Note: Never initiate
monitoring without calibration

15. Pre-Calibration Check
Not always necessary
Can do 5-pt check
Analyzer must be calibrated
The r2 value and % differences for each point are unacceptable

16. Instrument Calibration
Calibrate instrument to the standard
Use calibration point near URL
Setting low produces large error at URL
Set standard to ~0.400 ppm
Let analyzer stabilize
Calibrate analyzer
Do new 5-pt check

17. Post-Calibration 5-pt Check
Is analyzer response within 7% at each point?
Would you put this analyzer online?

18. Quality Control (QC) QC involves “in-house” verifications
Also referred to as precision checks
Verifications are comparisons between transfer standard and analyzer
Relative % difference within allowable margin?
Verifications determine monitoring repeatability
Standard deviation
Different types of verifications

19. QC (cont.)
Level 1: 40 CFR, Pt. 58, App. A, Table A-1 defines ozone verification requirements (for SLAMS)
Biweekly response check between 0.08 and 0.1 ppm
Comparison between analyzer and standard
Determines repeatability
Level 2: “extra” precision checks
Weekly “span level” (~80% URL) checks
Quarterly 5-pt checks
Determines analyzer performance trends

20. Quality Assurance (QA)
QA involves “external” checks
Referred to as “audits”
Audits involve comparison between transfer standard and analyzer
Accuracy levels must be within ±10%
Audits determine how close monitoring gets to actual values
Different types of audits

21. QA (cont.)
40 CFR, Pt. 58, App. A, Table A-1 defines ozone audit requirements (for SLAMS)
Annual (and other) response checks at multiple points
ppm
ppm
ppm
Comparison between analyzer and external standard
Audits should include zero check

22. QA (cont.) Different types of audits
By reporting organization (RO) certified by RO
By RO certified by other than RO
By other than RO certified by other than RO

23. Precision & Accuracy (P&A) Data
Precision data come from biweekly precision checks
Accuracy data come from annual and other audits
P&A data validate ambient data
P&A data must be included in AQS data submittals

24. Siting Criteria
Data quality depends on correct siting of all instrumentation
Specific instrument siting guidelines
Following guidelines is vital part of quality assurance and control
We’ll learn more about these guidelines in the next presentation

25. Summary Establish DQOs Develop QAPP Follow your QAPP
Get it approved by EPA
Follow your QAPP
Conduct bi-weekly precision checks
Conduct level 2 checks to follow monitor trends
Participate in annual audits and others if possible
Data quality will be guaranteed