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Emission Inventory Quality Assurance/Quality Control (QA/QC) Melinda Ronca-Battista ITEP/TAMS Center Emission Inventory Quality Assurance/Quality Control (QA/QC) Melinda Ronca-Battista ITEP/TAMS Center

Homework Discussion • Are there any questions on entering nonpoint data or point data Homework Discussion • Are there any questions on entering nonpoint data or point data into TEISS? 2

Definitions • Quality Control (QC) • • Documenting data sources Rechecking calculations Accuracy checks Definitions • Quality Control (QC) • • Documenting data sources Rechecking calculations Accuracy checks Use of approved standardized procedures for emissions calculations • Quality Assurance (QA) • External review and audit procedures by a third party 3

QA/QC: Where to Start? • Prepare QAPP that answers • What are you going QA/QC: Where to Start? • Prepare QAPP that answers • What are you going to report in EI? • What will you use the EI data for? • How are you going to review the data? See template QAPP • Potential uses of EI data will define minimum level of QA/QC 4

QA/QC Levels From US EPA’s Emission Inventory Improvement Program (EIIP) Vol. 6, page 2. QA/QC Levels From US EPA’s Emission Inventory Improvement Program (EIIP) Vol. 6, page 2. 1 -5 • Level 1 – supports enforcement, compliance, or litigation • Level 2 – supports strategic decision making • Level 3 – general assessment or research • Level 4 – Inventory compiled entirely from previously published data or other inventories 5

Data Quality Objectives (DQOs) • DQOs • Broad statement on how “good” or “true” Data Quality Objectives (DQOs) • DQOs • Broad statement on how “good” or “true” your EI results will be • EI ESTIMATES emissions. You can’t know exact “truth” about quantity or type of pollutants from a given source 6

DQOs: Examples • EI DQO for Accuracy • 100% of data transcribed from paper DQOs: Examples • EI DQO for Accuracy • 100% of data transcribed from paper forms to TEISS will be verified • EPA methods used to estimate emissions, ensure estimates as close to “truth” as possible • Track Accuracy Checks with TEISS QA/QC functions 7

DQOs: Examples • DQO for Completeness • 100% of largest point sources of PM DQOs: Examples • DQO for Completeness • 100% of largest point sources of PM included in EI • DQO for Comparability: • Emissions calculated represent “truth” on your reservation • Emissions comparable to similar sources or areas 8

DQOs are set, now what’s the plan? • QC should be included in each DQOs are set, now what’s the plan? • QC should be included in each EI task • QC for data collection • QC for calculations • QC for choosing estimation methods • Allocate at least 10% of resources for QA activities • Don’t wait until the end! 9

QC: What is included? • Check transcription of data during inventory preparation and reporting QC: What is included? • Check transcription of data during inventory preparation and reporting • Transcription of data from raw data collection sheets into electronic spreadsheets or TEISS calculators • Transcription of data results from TEISS summary tables to EI report 10

QC: What is included? (cont. ) • Check calculations • Including calculation of throughput, QC: What is included? (cont. ) • Check calculations • Including calculation of throughput, if necessary • If not calculating emissions with TEISS calculator, check that throughput multiplied by EF equals emissions • Verify that unit conversions are correct • Verify that units of your data match units TEISS or equation asks for 11

Unit Example Asks for data in units of 1000 gallons 12 Unit Example Asks for data in units of 1000 gallons 12

QC: What is included? (cont. ) • Verify you’ve documented all data sources • QC: What is included? (cont. ) • Verify you’ve documented all data sources • Completeness checks • Consistency checks • Double counting • Reasonableness 13

QC: How to track it • Keep a file for each source • Use QC: How to track it • Keep a file for each source • Use checklist to monitor person and date for • • • Data collection Data calculations Evaluation of data reasonableness Evaluation of data completeness Data coding and recording Data tracking 14

QC Methods: Reality Checks • Most commonly used • Is this number reasonable? Does QC Methods: Reality Checks • Most commonly used • Is this number reasonable? Does it make sense? • Never use the reality check as the sole criterion of quality • Find data for similar sources on EPA’s EIS Gateway system 15

QC Methods: Peer Review • Independent review of calculations, assumptions, and/or documentation by person QC Methods: Peer Review • Independent review of calculations, assumptions, and/or documentation by person with moderate to high level of technical experience • QA is a form of peer review • Can also be included as part of QC 16

QC Methods: Replication of Calculations • Most reliable way to detect computational errors • QC Methods: Replication of Calculations • Most reliable way to detect computational errors • General rule, minimum of 10% of calculations checked, depending on • Complexity of calculations • Inventory DQOs • Rate of errors encountered 17

QC Methods: Computerized Checks • Automated data checks can be • Built-in functions of QC Methods: Computerized Checks • Automated data checks can be • Built-in functions of databases, models, or spreadsheets, or stand-alone programs • Automate to • Check for data format errors (like Export to NEI component of TEISS) • Conduct range checks • Provide look-up tables to define permissible entries (like TEISS selection boxes) 18

TEISS needs a Human Touch • TEISS is an excellent tool; however, it needs TEISS needs a Human Touch • TEISS is an excellent tool; however, it needs your guidance • Be familiar with emission methodologies on which TEISS calculators are based 19

Finding Calculator Methodology • Scroll down on summary screen to get to Reference and Finding Calculator Methodology • Scroll down on summary screen to get to Reference and Online Link 20

Why Review the Methodology? • What do I select here? 21 Why Review the Methodology? • What do I select here? 21

Methodology Has Answers • Methodology: used to calculate emissions for 4 different “station operations” Methodology Has Answers • Methodology: used to calculate emissions for 4 different “station operations” (in most cases) • Underground tank filling • Underground tank breathing • Vehicle refueling displacement losses • Vehicle refueling spillage • Each operation should be included as a different Process in TEISS • If using an EPA model to calculate onroad emissions, make sure vehicle refueling emissions are not double counted 22

Typical Errors in EIs • • Missing or duplicate facilities Improper facility locations Missing Typical Errors in EIs • • Missing or duplicate facilities Improper facility locations Missing operating or technical data Erroneous technical data Double counting Errors in calculations Data entry and transposition errors; data coding errors 23

Most Typical QC Error Letting it slide • Make sure to include time for Most Typical QC Error Letting it slide • Make sure to include time for QA/QC • Pressure to gather data and “get it done” can harm documentation & verification • Putting it off to project’s end 24

QC Documentation • Ensure final written compilation of data accurately reflects inventory effort • QC Documentation • Ensure final written compilation of data accurately reflects inventory effort • Support QA assessments of inventory • Ensure reproducibility of inventory estimates • Enable inventory user or reviewer to assess quality of emission estimates and identify data references • Foundation for future inventories 25

What about QA? • Independent review by third party, ITEP for example • Checks What about QA? • Independent review by third party, ITEP for example • Checks effectiveness of your QC • Allocate 10% of project resources to QA • Again, don’t wait until the end • QA person checks a fraction of data entry, calculations, documentation, etc. 26

Are You Hungry For More? • Excellent resource and source for some of this Are You Hungry For More? • Excellent resource and source for some of this presentation material • EIIP Volume 6: Quality Assurance/Quality Control http: //www. epa. gov/ttn/chief/eiip/techrep ort/volume 06/index. html 27

Homework due in 5 days: • Read EIIP Volume 3, Chapter 1: Introduction to Homework due in 5 days: • Read EIIP Volume 3, Chapter 1: Introduction to Area Source Emission Inventory Development, Sections 6. 1 and 6. 2 (pages 1. 6 -1 through 1. 6 -7) • Answer questions in exercise • Email answers to instructors 28