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An Overview of EPA’s Quality Assurance Guidance for Ambient Air Quality Monitoring Data Data Analysis and Interpretation February 12 – 14, 2008, Tempe, AZ Catherine Brown, EPA Region 9 What are the QA elements for ambient monitoring data? Monitoring Objectives PQAO defined Network Design DQO process EPA’s MQO’s for ambient monitoring (some new) Data Quality Assessments Tools EPA’s Ambient Air Quality Monitoring Program Objectives Provide air pollution data to general public in a timely manner Support compliance with air quality standards & emissions strategy development Support air pollution research studies Primary Quality Assurance Organizations To aggregate monitoring data and assess DQO’s, should have common SOPs, QAPPs – Team of operators with common training – Calibration facilities and standards – QA oversight – Management, lab or HQ Design of Ambient Monitoring Networks Highest concentration areas Population exposure Source-oriented sampling General background Pollutant transport Visibility and welfare effects * * Note: Appendix A requirements now apply to PSD monitoring EPA’s Quality System Now fully based on DQO process (December 2006) Decision makers must understand probability of incorrect NAAQS decision (data uncertainty) Data Quality Assessments determine DQOs are achieved

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An Overview of EPA’s QualityAssurance Guidance for Ambient Air

Quality Monitoring Data

Data Analysis and InterpretationFebruary 12 – 14, 2008, Tempe, AZ

Catherine Brown, EPA Region 9

What are the QA elements forambient monitoring data?

Monitoring Objectives PQAO defined Network Design DQO process EPA’s MQO’s for ambient monitoring

(some new) Data Quality Assessments Tools

EPA’s Ambient Air QualityMonitoring Program Objectives

Provide air pollution data to general public in atimely manner

Support compliance with air quality standards &emissions strategy development

Support air pollution research studies

Primary Quality AssuranceOrganizations

To aggregate monitoring data and assessDQO’s, should have common– SOPs, QAPPs– Team of operators with common training– Calibration facilities and standards– QA oversight– Management, lab or HQ

Design of AmbientMonitoring Networks

Highest concentration areas Population exposure Source-oriented sampling General background Pollutant transport Visibility and welfare effects *

* Note: Appendix A requirements now apply to PSD monitoring

EPA’s Quality System

Now fully based on DQO process(December 2006)

Decision makers must understandprobability of incorrect NAAQS decision(data uncertainty)

Data Quality Assessments determine DQOsare achieved

Measurement Quality Objectives

Table A-2 in 40 CFR 58 Appendix A Note: Some statistics are new

–Defines measurement quality samplesrequired for manual and automated methodsfor each criteria pollutant

Data Quality Assessments

Evaluate each monitoring program or project forthese indicators

Representativeness Precision Bias Detectability Completeness Comparability

Summary

QA requirements apply to environmentalmeasurements used in decision-making

Data quality assessments help organize andunderstand complex datasets

Statistical tools available from EPA

EPA References

Guidance on Systematic Planning Using theData Quality Objectives ProcessEPA/240/B-06/001 Feb. 2006http://www.epa.gov/quality/qa_docs.html

Guideline on the Meaning and Use ofPrecision and Bias Data Required by 40CFR Part 58 Appendix A – Version 1.1

http://www.epa.gov/ttn/amtic/parslist.html

EPA References (cont.)

EPA Quality Assurance Handbook http://www.epa.gov/ttn/amtic/qabook.html Data Assessment Statistical Calculator

(DASC) Software for calculating newprecision and bias statistics

http://www.epa.gov/ttn/amtic/parslist.html

EPA References (cont.)

2006 Criteria Pollutant Quality IndicatorSummary Report for AQS Data

http://www.epa.gov/ttn/amtic/parslist.html