Western Regional Air Partnership Emissions Database Management System CERR Workshop San Francisco May 11-12 2004

1. Western Regional Air PartnershipEmissions Database Management SystemCERR WorkshopSan FranciscoMay 11-12 2004 E.H. Pechan & Associates, Inc.

2. Strawman Processes/Procedures for EDMS Implementation

3. QA Plan Overview

4. Quality Control/Quality Assurance • Quality Control (QC) • Quality Assurance (QA) • Gap Filling

5. Quality Control • Quality Control (QC) • QC is the process of inspecting the data and diagnosing errors • Mandatory fields, code lookups, referential integrity, duplicates, range checks • No data is changed

6. Quality Assurance • Quality Assurance (QA) • The process of remediating basic errors in the data • May generate parents or eliminate duplicate records • Structurally compliant with EPA NIF 3.0 standards • May be defined to null out incorrect non-mandatory fields, or fill in mandatory values with defaults

7. Gap Filling • Gap Filling • The addition or revision of data in order to fill in missing information in the following areas (for example): • Geographic • Pollutant • Major Sources • Revision or addition of data based on default information • Seasonal Throughputs • Latitude/Longitude County Centroids

8. QA vs. Gap Filling • Some activities could be defined as equally appropriate for QA or Gap Filling • Stack parameters • Default coordinates

9. EDMS Inventory Definition • EDMS Inventory An EDMS inventory is uniquely identified by the following criteria: • Inventory Version Label • User defined – should be sufficient to identify for the user a specific Inventory – for example, “WRAP V1.0 All Sector” • Inventory Year • 1999, 2000, 2001, 2002, etc. • Inventory Type • Actual, Remediated, Modeling, Planning, Sensitivity, Forecast

10. Inventory Content • EDMS Inventory • One or more Sectors • It is expected that in Phase I the inventory identification includes all sectors • One or more States/Local/Tribal Entities • It is expected that in Phase I the inventory identification includes all submitted inventories • One Emission Inventory Year • One Emission Inventory Type

11. Inventory Status • Inventory Status • Locked • No further changes/additions can be made • All inventories in Production are locked • Unlocked • Changes/additions can be made • Data Administrator Functionality

12. Inventory Versioning • Inventory Versioning • A new inventory can be created (“cloned”) from an existing inventory • Receives a new inventory identification , a new label, and possibly a new inventory type designation (as appropriate) • Inventories can only be cloned from locked inventories • Data Administrator Functionality

13. Inventory Type • Inventory Type • Actual (QC) • Remediated (QA) • Modeling (Gap Filled) • Planning • Sensitivity Run • Forecast

14. Inventory Type Definition • Inventory Type Definition • Actual • The actual inventory provided by the submitting agencies with errors diagnosed but not changed (Quality Control -QC). • Remediated • The actual inventory with certain basic data issues remediated (Quality Assurance - QA). • Modeling • The remediated inventory with gap-filling corrections • Sensitivity Run, Planning, Forecast • Related to later stages of inventory development and not defined here

15. Actual Inventory • Actual Inventory • Preserves the submission as it was received • Diagnosis of Errors provided to submitting agency (QC) • No changes, additions, or deletions to the data

16. Actual Inventory Process Data Provider 1 WRAP Actual V1.0 2002 TRANSFER Data Provider 2 Data Provider 3 TRANSACTION STAGING Quality Control, DiagnoseOnly PRODUCTION No Changes

17. Remediated Inventory • Remediated Inventory • Cloned from the Actual Inventory • Basic changes made to the data (QA), for example : • Uppercasing character data • Standardize pollutant codes from NO2 to NOX • Set record types appropriately • Conversion of units to standards units (TONS to TON)

18. Remediated Inventory Process WRAP Remediated V1.0 2002 TRANSFER WRAP Actual V1.0 2002 TRANSACTION STAGING PRODUCTION Cloning Quality Assurance, Basic Changes

19. Modeling Inventory • Modeling Inventory • Cloned from Remediated Inventory • Gap-Filled • Generating PM records • Bringing forward from previous inventories, missing data • Generating Daily records from Annual records • Replacing submitted data with modeled data

20. Modeling Inventory Process WRAP Remediated V1.0 2002 WRAP Modeling V1.0 2002 TRANSFER TRANSACTION STAGING PRODUCTION Cloning Gap Filling

21. CERR • Consolidated Emissions Reporting Rule • Consolidates emission inventory reporting requirements to a single rule • Purpose • Simplify emissions reporting • Offer options for data submittal • Unify reporting dates for various types of inventories • Final rule published June 10, 2002 FR Volume 67, Number 111, pp 39602-39616 http://www.epa.gov/ttn/chief/cerr/index.html

22. Data Submission • Data Providers • Access or ASCII format • Compressed/Uncompressed • EDMS input format/NIF 3.0 format • Provide file, comments, and indications as necessary regarding tribal overlap

23. NEI and CERR • National Emissions Inventory (NEI) and CERR • NEI Input Format (NIF) and NEI XML • NIF and XML are acceptable formats for agencies to submit data satisfying CERR • NIF includes data beyond CERR’s requirements • NIF Mandatory/Necessary vs. CERR • NIF requires more fields than CERR • NIF ‘Mandatory’ fields are required • NIF ‘Necessary’ fields are required for modeling • http://www.epa.gov/ttn/chief/nif/nif30/nifv3_cerr_compare.pdf

24. NIF and EDMS • EDMS input format • Identical to NIF 3.0 for those sectors and tables that are common to both • Additional EDMS input formats are for the collection of detailed activity data • NIF 3.0 =EDMS input formats for the purposes of general discussion

25. Screen Shots

26. NIF and CERR • Observations on NIF and CERR • Start date/End date for the winter season • NEI/NIF works best when the start and end dates for a particular emission type are continuous (December 1998 to February 1999) • CERR identifies winter throughput % as being from the same calendar year (January 1999-February 1999, December 1999)

27. RPO and EPA • Data Submittal Coordination • Due to EPA on June 1, 2004 • Submission to EPA for the development of NEI • Submission to RPO for development of RPO inventory • The goal of coordination is to reduce duplicate contacts with submitting agencies • Communications methods – potentially Bugzilla • More detail from David Misenheimer on Day 2

28. RPO and EPA

29. QA Methodsfor input emissions files from

30. QA Methodsfor input emissions files from • Biogenics including Ammonia • Windblown Dust Data modeled and provided by the WRAP Regional Modeling Center Data can be overwritten by Data Providers

31. QA Methodsfor input emissions files from • Point/Area Data Overlaps Sources that may appear in both sectors, such as dry cleaners, gas stations, etc. • Data Providers will communicate any known issues to EDMS • EDMS will inquire with Data Providers regarding suspected anomalies detected

32. QA Methodsfor input emissions files from • Fire • Assess data reporting capabilities in initial data year • Integrate data from sources such as Top-Down Inventories (Air Sciences), Annual Totals by Air District, Department of Interior

33. QA Methodsfor input emissions files from agencies providing data State/ county/ tribal data overlaps

34. QA Methodsfor input emissions files from agencies providing data • Speciation of PMx into EC/OC • NMHC Speciation • Filterable vs. Primary PM Data will be housed as reported. If EC/OC/NMHCs/PM absent at modeling time, modelers may infer missing pollutants using algorithms (such as speciation) of their choosing.

35. QA Methodsfor input emissions files from agencies providing data • Road Dust • Reported as an Area Source • Can be isolated for analysis and reporting by SCC • Gap – filling data from Top Down Inventories Road Dust is reported as an Area Source. It can be isolated for analysis and reporting by SCC.

36. QA Methodsfor input emissions files from agencies providing data • Missing Data • SCCs • Pollutants • Counties • Inconsistencies between Jurisdictions • Automated/manual detection Action on Missing Data per preference of data provider. Data providers will be surveyed on potential inconsistencies.

37. Data Access/Display/Security

38. Data Access/Display/Security • Data Access Levels • Who in your organization needs what level? • General User • Data Analyst • Data Provider • Reports • Standard • Ad Hoc

39. Training

40. Training

41. Training

42. Draft EDMS Phase II Task List

43. Draft EDMS Phase II Task List • EI Projections • Oil and Gas Production/Distribution Hereafter, not in priority order • Point Source Auxiliary Data • Emission control device, efficiency, additional control information • Year on-line • SCC verification • Low Graphics version - provide users without high-speed Internet connections an attractive and intuitive interface to view, query, and report EDMS data

44. Draft EDMS Phase II Task List • Biogenic emission tracking at the hourly, daily, or seasonal temporal resolutions. • Capability of geo-coding certain traditional area source categories • Include facility, stack shape files for point sources for detailed GIS rendering.

45. Draft EDMS Phase II Task List • Fire - Wildfires: Explore. As another possible daily wildfire data source . MODIS Satellite data from Remote Sensing and Control (RSAC) • This source may still be very R&D oriented • Good results for fires >800 acres • May provide shape files, daily data, and have archived perimeter (location, size, etc.) data

46. Draft EDMS Phase II Task List • Fire - Considerations for data obtained from NIFC ICS 209 forms • This data should be linked to other data in this category in order to provide a more detailed fire analysis (esp. daily) • May need to overlay data on GIS fuels map since fuel type often not provided • Ways to link data may include some type of proximity determining capability, crosschecking with emission date. QA/QC will be essential.

47. Draft EDMS Phase II Task List • Fire - Other Considerations • How do we build in profile info that is not in NIF? • How do we apply plume height and distribution of pollutants? • Interfaces already developed by Air Sciences • Automated CEMS data comparison between EDMS and CAMD databases. • Automated cloning of databases • Feedback loop from EDMS to biogenic/dust modeling, or housing modeling inputs in EDMS

48. Draft EDMS Phase II Task List • Permit tracking capability • Acceptance of XML data submittals • Use of the Exchange Network for file transfer • XML output • Capability to store and retrieve Mobile and Non-road input files, as well as non-default data files, in the EDMS database

49. Screen Shots

50. Screen Shots