## 2002 Fire Emission Inventory for the WRAP Region

– Phase II

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EXECUTIVE SUMMARY .............................................................................................................. ....................................vi
1 INTRODUCTION................................................................................................................. ........................................... 1 1.1 Basic Concepts of the 2002 WRAP Fire Emission Inventory .................................................................... ............. 1 1.2 Fire Emission Inventory Phases ............................................................................................. ................................ 2 1.3 Comments & Revisions Incorporated in the Final Report...................................................................... ................. 3 1.4 Partners and Contributors in the Project................................................................................... .............................. 3 2 THE 2002 WILDLAND FIRE EMISSION INVENTORY.................................................................................... .............. 5 2.1 Activity Data.............................................................................................................. .............................................. 5 2.1.1 Geo-Referencing Fire Location by Township/Range/Section and County...................................................... 6 2.1.2 GIS-Based NFDRS Fuel Loading Assignment.................................................................................. .............. 7 2.1.3 Final Activity Data Quality Control...................................................................................... ............................. 8 2.1.4 Wildland Fire Use........................................................................................................ .................................... 8 2.1.5 Natural and Anthropogenic Assignments (For All Fire Sources)............................................................. ........ 9 2.2 Fuel Loading and Emission Factors .......................................................................................... ........................... 13 2.2.1 Pollutant Speciation..................................................................................................... .................................. 15 2.3 Emission Ca lculations...................................................................................................... ..................................... 17 2.3.1 Daily Fire Growth Allocation............................................................................................. ............................. 18 2.4 Plume Profile .............................................................................................................. .......................................... 19 2.4.1 Virtual Acres............................................................................................................ ...................................... 19 2.4.2 Diurnal Consumption...................................................................................................... ............................... 19 2.4.3 Fire Size Classes and Plume Profile Calculations ......................................................................... ............... 20 2.5 Approach for Technical Refinements of Large Fires and Fire Complexes for WRAP Phase I Fire Emission Inventory............................................................................................................... ............................................... 29 2.5.1 Complex Fire Identification.............................................................................................. .............................. 31 2.5.2 Blackened Versus Perimeter Fire Acres .................................................................................... ................... 34 2.5.3 Spatial, Temporal, and Fuel Model Refinements ............................................................................ .............. 36 2.5.4 Overall Assessment of Refinements ........................................................................................ ..................... 41 2.6 Wildland Fire Quality Control Process...................................................................................... ............................ 42 2.6.1 QC Binder Summary ........................................................................................................ ............................. 42 2.6.2 Feedback Response Summary................................................................................................ ..................... 42 3 THE 2002 AGRICULTURAL BURNING EMISSION INVENTORY ............................................................................. . 46 3.1 Agricultural Burning Activity Data ......................................................................................... ................................ 46 3.1.1 Data Sources............................................................................................................. .................................... 46 3.1.2 Agricultural Burning on Tribal Lands ..................................................................................... ........................ 46 3.1.3 Time Periods of the Actual Agricultural Burning Data ..................................................................... .............. 47 3.1.4 Data Quality Requirements ................................................................................................ ........................... 47 3.2 Fuel Loading and Emission Factors for Agricultural Burning................................................................. ............... 47 3.3 Temporal Refinement of Agricultural Emissions Data ......................................................................... ................. 49 3.3.1 Blackout Dates ........................................................................................................... ................................... 50 3.4 Spatial Refinement of Agricultural Emissions Data .......................................................................... .................... 50 3.5 Assigning Plume Characteristics to Agricultural Burning Events............................................................. ............. 51 3.5.1 Diurnal Consumption Template............................................................................................. ........................ 51 3.5.2 Physical Plume Characteristics ........................................................................................... .......................... 52 3.6 Agricultural Burning Quality Control Process............................................................................... ......................... 53 3.6.1 QC Binder Summary ........................................................................................................ ............................. 53 3.6.2 QC Response Summary ...................................................................................................... ......................... 53WRAP 2002 PhII EI Report_20050722.doc iii 

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4 THE 2002 NON-FEDERAL PRESCRIBED RANGELAND BURNING EMISSION INVENTORY ................................ 55 4.1 Rangeland Burning Activity Data............................................................................................ .............................. 55 4.2 Temporal Allocation of Burn Activity....................................................................................... .............................. 56 4.3 Emission Ca lculations...................................................................................................... ..................................... 56 4.4 Allocation of Emissions to Rea listic Event Size and Day of Year............................................................ ............. 57 4.5 Allocation of Emission s to Coordinate Location............................................................................. ....................... 57 5 RESULTS...................................................................................................................... ............................................... 60 5.1 Summary of 2002 Phase II Fire Emission Inventory........................................................................... .................. 60 6 DELIVERABLES AND END USER DATA SUPPORT....................................................................................... .......... 68
7 REFERENCES................................................................................................................... .......................................... 70



### Tables Table 1: Executive Summary of Fire Activity and Emissions from Wildfires, Prescribed Fires, Wildland Fire Use, Agricultural Burning, and Non-Federal Prescribed Rangeland Burning in 2002 ..........................................vii Table 2: Summary of Wildland Fire Use Data in Phase I EI....................................................................... ................. 9 Table 3: SCCs and Their Fire Type and Natural/Anthropogenic Classification..................................................... .... 10 Table 4: Prescribed Fire NFDRS Fuel Model Categorization as Natural or Anthropogenic...................................... 12 Table 5: Summary of Fuel Loading and Consumption by NFDRS Model ................................................................ . 14 Table 6: Summary of Emission Factors ........................................................................................... ......................... 15 Table 7: Pollutant Species’ Mathematical Relationships Currently in use by RMC................................................. .. 16 Table 8: Pollutant Species’ Mathematical Relationships Currently in use in Air Sciences Emission Inventory System ......................................................................................................................... ............................... 17 Table 9: Standard Diurnal Consumption Template Used to Distribute Fire-Total Heat Production and Emissions .. 19 Table 10: Fire-Related Parameters as Function of Fire Size Classes ............................................................. ........... 20 Table 11: Buoyant Efficiency as Function of Hour of Day........................................................................ ................... 20 Table 12: Summary of Available Data for Large Wildland Fires in Phase I EI ..................................................... ....... 30 Table 13: Summary of Complex Fire Check Based on Duplicate Names Only .......................................................... 32 Table 14: Summary of Blackened Versus Perime ter Fire Acres for Large Wildfire Events......................................... 35 Table 15: Summary of Unburned Versus Blackened Acres for Six Fires............................................................. ....... 35 Table 16: Relative Distribution of Black ened Acres by Fire Severity Category................................................... ........ 36 Table 17: Sensitivity of Estimated Fuel Consumption to Adjustment for Blackened Acres in Combination With Fuel Loading Based on GIS-Derived NFDRS and FCC Fuel Layers .................................................................. 38 Table 18: Sensitivity of Estimated Fuel Consumption to Adjustment for Blackened Acres in Combination With Fuel Loading Based on GIS-Derived NFDRS and FCC Fuel Layers .................................................................. 39 Table 19: Summary of Fuel Consumption Percentages App lied to Model Variable Consumption by Fire Severity Class, NFDRS Fuel Models ....................................................................................................... ................. 40WRAP 2002 PhII EI Report_20050722.doc iv 

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Table 20: Summary of Fuel Consumption Percentages Appli ed to Variable Consumption by Fire Severity Class, FCC Fuel Models ................................................................................................................ ........................ 40 Table 21: Summary of Estimated Adjustments to the Phase II EI (Wildfire and Wildland Fire Use) Based on Described Quality Control and Data Refinement Procedures ..................................................................... 41 Table 22: Summary of Wildland Fire QC Binders Sent and QC Feedback Received................................................. 42 Table 23: Detail of Wildland Fire QC Binder Feedback Received.................................................................. ............. 44 Table 24: Agricultural Burning ................................................................................................. .................................... 48 Table 25: Plume Class Sizes .................................................................................................... .................................. 49 Table 26: Distributions of Da ily Events by Plume Class......................................................................... ..................... 49 Table 27: Blackout Days for Agricultural Burning............................................................................... ......................... 50 Table 28: Diurnal Consumption Template Used to Di stribute Emissions From Agricultural Burning .......................... 51 Table 29: Fire-Related Parameters as a Function of Fire Emission Classes....................................................... ....... 52 Table 30: Detail of Agricultural Burning QC Binder Feedback Received ........................................................... ......... 54 Table 31: Non-Federal Prescribed Rangeland Burning Activity by State........................................................... ......... 55 Table 32: Percent Activity per Mont h for Non-Federal Rangeland Burning ......................................................... ....... 56 Table 33: Rangeland Fuel Loading and Emission Factors.......................................................................... ................ 56 Table 34: Rangeland Burning Fire Size Packet Statistics ........................................................................ ................... 57 Table 35: USGS Land Cover Characteristics Flagged as Rangeland................................................................. ........ 58 Table 36: 2002 Phase II EI Fire Activity and PM 2.5 Emissions by State – All Fire Types............................................ 61 Table B-1: WRAP NIF 3.0 for Fire - Transmittal Record.......................................................................... ....................B-1 Table B-2: WRAP NIF 3.0 for Fire - Site Record ................................................................................. ........................B-2 Table B-3: WRAP NIF 3.0 for Fire – Emission Unit Record........................................................................ .................B-3 Table B-4: WRAP NIF 3.0 for Fire - Emission Process Record ..................................................................... ..............B-4 Table B-5: WRAP NIF 3.0 for Fire - Emission Release Point Record............................................................... ...........B-5 Table B-6: WRAP NIF 3.0 for Fire - Emission Period Record...................................................................... ................B-6 Table B-7: WRAP NIF 3.0 for Fire - Control Record .............................................................................. ......................B-7 Table B-8: WRAP NIF 3.0 for Fire - Emission Record ............................................................................. ....................B-8WRAP 2002 PhII EI Report_20050722.doc v 

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### Figures Figure 1: Buoyant Efficiency .................................................................................................. ........................................ 21 Figure 2: Projected Top of Plume .............................................................................................. .................................... 22 Figure 3: Projected Bottom of Plume ........................................................................................... .................................. 23 Figure 4: Proportion of Plume in Surface Layer................................................................................ ............................. 24 Figure 5: Fire Size Class 1 Plume Characteristics............................................................................. ............................ 25 Figure 6: Fire Size Class 2 Plume Characteristics............................................................................. ............................ 26 Figure 7: Fire Size Class 3 Plume Characteristics............................................................................. ............................ 27 Figure 8: Fire Size Class 4 Plume Characteristics............................................................................. ............................ 28 Figure 9: Fire Size Class 5 Plume Characteristics............................................................................. ............................ 29 Figure 10: Diurnal Emissions/Consumption Profiles fo r Agricultural Burning and Wildfire/Prescribed Fire................... 52 Figure 11: USGS Land Cover Characteristics Mapped as Rangeland ................................................................ .......... 59 Figure 12: Annual Acres Burned by Fire Type................................................................................... ............................ 62 Figure 13: Annual PM 2.5 Emissions by Fire Type (tons)................................................................................................. 62 Figure 14: Annual Region-Wide Emissions (tons) ................................................................................ ......................... 63 Figure 15: State Totals for All Fire Sour ces as a Percentage of Regional Total (Annual) ....................................... ...... 63 Figure 16: Acres Burned Temporal Distribution (month)......................................................................... ....................... 64 Figure 17: PM 2.5 Emissions (tons) Temporal Distribution (month)................................................................................. . 64 Figure 18: Annual Acres Burned Spatial Distribution (state)................................................................... ....................... 65 Figure 19: Annual PM 2.5 Emissions (tons) Spatial Distribution (state)............................................................................ 65 Figure 20: Annual Natural and Anthropogenic PM 2.5 Emissions by State (tons)............................................................ 66 Figure 21: Annual Anthropogenic PM 2.5 Emissions by State and Fire Type (tons) ........................................................ 66 Figure 22: Anthropogenic PM 2.5 Emissions by Month and State (tons).......................................................................... 67



### Appendices Appendix A: Data Gathering and Compilation Appendix B: WRAP NIF 3.0 for Fire Format SpecificationWRAP 2002 PhII EI Report_20050722.doc vi 

# EXECUTIVE SUMMARY

The Fire Emissions Joint Forum (FEJF) of the Western Regional Air Partnership (WRAP) has completed an air emission inventory for fire in 14 of the 15 states in the WRAP region. (Hawaii is not in the inventory.) The inventory includes emission estimates and activity data for wildfire, prescribed fire, wildland fire use (WFU), agri cultural burning, and non-federal prescribed rangeland (NF rangeland) burning for the calendar year 2002. The FEJF collected fire activity data from federal, tribal, and state agencies; arri ved at data quality objectives; culled data from the database that did not meet the data quality objectives; allocated summary data to realistic fire events where necessary; devised emission calculat ion routines; estimated emissions for all fire events; and published an emission inventory databa se and dispersion model-ready digital files.
The purpose of the fire emission inventories is to further the WRAP’s charge of supporting member states’ and Tribes’ Regional Haze State Implementation Plans and Tribal Implementation Plans. Along with emission inventories from other types of sources, the 2002 fire emission inventories will be used by the Emi ssions and Air Quality Modeling Forums of the WRAP to execute, evaluate, and enhance th e performance of the WRAP-wide air quality dispersion models. Also, the 2002 fire emission inventories will be used to support the WRAP’s, States’, and Tribes’ efforts to allocate re gional haze impacts to specific sources.
Building the emission inventory involved many te chnical steps shaped by extensive stakeholder and expert discussion. Many of the techniques utilized for this emission inventory are based on the WRAP technical report entitled “1996 Fire Emission Inventory.” Driven by the WRAP’s targets for a highly resolved (t emporally and spatially) dispersion model, the FEJF produced an event-based emission inventory, placing all fire emission s at coordinate locations on specific days. Federal and state records of individual fire ev ents were collected. For agricultural and nonfederal rangeland burning, county level data on a monthly basis was collected and allocated to the coordinate level on a daily basis for jurisdicti ons where event level data was not available. In general, burning activity data was not available directly from tribal agencies. Federal land manager (especially Department of Interior – Bure au of Indian Affairs) data included in the federal databases as well as state data may includ e burning in Indian Country. Quality Control Packets where sent to states, Tribes, and federa l land management agencies (FLMs) to solicit corrections to the 2002 activity data for w ildland burning and agricultural burning.
Activity records were checked for completeness for fire size, fuel loading, date, and location. Activity records deemed incomplete and therefor e not useable in an emission calculation were culled from the database (and retained in a co mpanion database for documentation purposes). Fuel loading and emission factor tables along with diurnal consumption and plume profiles were developed from the literature, expert and prof essional judgment, and stakeholder input. Spreadsheet and geographic info rmation system software was us ed to store the data, performWRAP 2002 PhII EI Report_20050722.doc vii data augmentation and quality control functions, calculate emissions, and produce the strictly formatted National Emission Inventory Format (NIF) 3.0 and SMOKE/IDA text export files of the inventories. The methods developed for this study may be refined and utilized for future air emissions analyses. Table 1 presents an abbreviated summary of the 2002 wildfire, prescribed fire, and WFU inventories.

Limitations of this emission invent ory include the omission of fire events (e.g., tribal burning, in general, not accounted for in non-tribal data sets and individual fire activity records deemed to be incomplete) and variable data quality due to the variety of data sources used. Furthermore, estimating emissions from vegetative burning in volves considerable scientific uncertainty.
Table 1: Executive Summary of Fire Activity and Emissions from Wildfires, Prescribed Fires, Wildland Fire Use, Agricultural Burning, and Non-Federal Prescribed Rangeland Burning in 2002

Source Fire Days Acres Burned Tons Fuel Consumed Tons PM 2.5 Emitted Wildfire 5,835 5,276,485 123,642,024 1,489,886 WFU 369 201,548 6,763,940 81,505 Prescribed 16,445 649,044 7,195,489 71,420 Agricultural 105,991 2,163,478 6,061,792 34,578 NF Rangeland 4128 1,042,003 1,823,507 15,454 Total 132,768 9,332,559 145,486,752 1,692,845WRAP 2002 PhII EI Report_20050722.doc 1 SECTION 1 

# INTRODUCTION

This documentation is a summary of the activity data, calculations, and results of the historical fire emission inventory for 2002 prepared for the Emissions Task Team (ETT) of the FEJF. For consistency, many of the technical methods used to build the 2002 inventory are intentionally the same as the WRAP 1996 fire emission inventory. Technical improvements were made by the FEJF to this 2002 process including refining the daily fire spread algorithm and updating plume profile parameters. Details of the 2002 fire activity data collection and processing are bulleted for each data set received in Appendix A.
Significant improvements to the fire emission inventories have been made on the activity data side. For example, the results of the wildfire , prescribed burning, and agricultural burning quality control review efforts have been incorporated in the Phase II activity data. Also, for the first time, estimates of non-federal rangeland burning activity and emissions are included in the WRAP’s 2002 fire inventory. 

## 1.1 Basic Concepts of the 2002 WRAP Fire Emission Inventory The FEJF inventoried fire emissions for calendar year 2002 for the states in the continental WRAP region plus Alaska. The term “fire” refers in clusively to wildfire, wildland fire use (WFU, formerly prescribed natural fire), prescribed fire, agricultural burning, and non-federal prescribed rangeland burning. The term “wildla nd fire” refers only to wildfire, WFU, and prescribed fire which have many data sources and calculation parameters in common. This emission inventory was based on data collected by state and federal agencies. Agricultural burning was inventoried based on a combination of event-level and monthly summary data submitted to represent 2002. State-level estimates of activity of non-federal prescribed rangeland burning were supplied by the ETT and allocated to events for modeling.
The WRAP Air Quality Modeling and Emissions Foru ms provided the FEJF with specific data resolution requirements for the fire emission inve ntory. For spatial resolution, each fire event needed a specific latitude and longitude in orde r to satisfy the spatial resolution goal of one minute of latitude and longitude. For temporal resolution, hourly emission estimates for each fire event were required.
Estimating emissions from fire events involves cons iderable scientific uncertainty. Historic data are of varying quality and for some areas unavaila ble. Activity records were not ground-truthed and, other than quality control steps described in this report, were generally accepted “as is.”Parameters such as the vegetation type of a burn, the vegetation-specific fuel loading, pollutantspecific emission factors, and combustion efficiencies, to name a few, all have uncertainties associated with them which may influence emissi on estimates and regional modeling results.WRAP 2002 PhII EI Report_20050722.doc 2 The efforts of the ETT were dedicated to using professional judgment to select the best available or most representative parameters or methods to estimate emissions. However, other parameters and methods could have been chosen and could al so be considered “reasonable” for estimating emissions from fire.
The specifications required by the Emissions and Air Quality Modeling Forums combined with the limitations of existing data and emission estimation methods shaped the emission inventory development. Fire, traditionally considered an “ar ea” source, is treated as a “point” source in the WRAP’s regional dispersion model. Ther efore, fire emissions were placed at a latitude/longitude coordinate location for eachday. From the daily and spatially resolved emission inventory, hourly consumptio n and plume rise were estimated.
The 2002 emission inventory was made available to the WRAP Modeling Forum digitally as database files and text files formatted for input to the Sparse Matrix Operator Kernel Emissions (SMOKE) Modeling System (PTINV, PTDAY, and PTHO UR files in IDA format). Also under this contract, the National Emission Inventory Format (NIF) 3.0 for point sources was adapted to accommodate this emission inventory. NIF 3.0 formatted text files were provided to the WRAP. 

## 1.2 Fire Emission Inventory Phases The FEJF has identified a number of phases of emission inventory development to supply the WRAP with appropriate emission inventories for it s regional haze dispersion modeling efforts. These phases are:

• Phase I – Modeling Evaluation Emission Inve ntory (Phase I EI): Actual 2002 wildland fire and prescribed fire emission inventories and use of the 2018 Agricultural Burning Base Smoke Management Program emission in ventory as a placeholder. Primary use of the Phase I inventories is to verify an d enhance dispersion model performance and to test geographic source apportionment (modeling estimates of contribution at each Class I area from each upwind source jurisdiction).

• Phase II – Initial Modeling Apportionment Emi ssion Inventory (Phase II EI): Actual 2002 wildland fire and prescribed fire emissi ons (split into natural and anthropogenic events) emission inventories, actual 2002 agri cultural burning emission inventory, and estimated 2002 non-federal rangeland burning. Primary use of the Phase II inventories is to complete the WRAP’s geographic source apportionment for the Attribution of Haze Project (per the WRAP’s Strategic Plan 2003 – 2008).

• Phase III – Planning Baseline Period Emissi on Inventory (Phase III EI): Emission inventories for wildland fire, prescribed fire , and agricultural burning that are based on 2000 through 2004 (or longer) fire activity data that is assessed to be representative of regional haze baseline period. The emission inventory format used for Phase II will be used for Phase III for consistency.WRAP 2002 PhII EI Report_20050722.doc 3 • Phase IV – Planning 2018 Projection Year Emission Inventory (Phase IV EI): Projected emission inventories for wildland fire, pres cribed fire, and agricultural burning. Projections will be based on predictable vari ables and may be in the form of emission scenarios or ranges of emissions. The emi ssion inventory format used for the Phase III baseline planning inventory will be used for Phase IV for consistency.

The fire emission inventories delivered with an d described in this document are the Phase II emission inventories. Calculation methods and data quality standards were devised with the FEJF’s stated objectives for the Phase II invent ories in mind. The FEJF emission inventory reflected consistent methods and specific fire event data. Data quality standards were set for the historic activity data collected. Consistent ca lculation methods and calculation parameters (such as literature-based fuel load ings) were implemented. 

## 1.3 Comments & Revisions Incorporated in the Final ReportThe draft report for this project was distributed in an e-mail sent on April 4, 2004, by the FEJF cochairs to the Emissions Task Team and other in terested members of the FEJF. Reviewers were given two weeks to provide comments on the draft report. Seven comments were received. Commenters included:

• Neva Sotolongo, California Air Resources Board

• Lee Alter, Western Regional Air Partnership

• Doug G. Fox, Ph.D., Cooperat ive Institute for Research in the Atmosphere, Colorado State University

• Lisa Bye, US DOI Bureau of Land Management, New Mexico

• Christi Gordon, USDA Forest Service, Southwest Region

• Darla Potter, Wyoming Department of Envi ronmental Quality, Air Quality Division

• Ron King, Alaska Department of Environmental Conservation
Comments were primarily editorial in nature were integrated into the document. One commenter requested a comparison of the Phase II EI with the CEIDARS database for California. Such a comparison is beyond the scope of this project, but the Phase II data is ce rtainly available for use by the commenting agency to perform its own comparison. 

## 1.4 Partners and Contributors in the Project Air Sciences acknowledges the contributors to the development of the Phase II EI database and this report. Contributors include:WRAP 2002 PhII EI Report_20050722.doc 4 • Members of the Emissions Task Team of the FEJF.

• Members of the FEJF.

• Peter Lahm, USDA Forest Service, former co-chair of the FEJF.

• Darla Potter, Wyoming DEQ, co-chair of the FEJF.

• Mark Fitch, USDA Forest Service, co-chair of the FEJF.

• Tom Moore, Western Regional Air Partnership.

• Pat Shaver, USDA Natural Resources Conservation Service.

• Staff of the National Tribal Environmental Council (NTEC).

• Participants in the BETA testing group fo r the Agricultural Burning and Wildland Burning Quality Control Binders, including:

o Peter Lahm, USDA Forest Service

o Mark Fitch, USDA Forest Service

o Darla Potter, WY DEQ

o Mike Ziolko, Oregon Department of Forestry

o Jim Russel, USDA Forest Service

o Paul Schlobohm, US DOI Bu reau of Land Management

o Aaron Worstel, US DOI National Park Service

o Cathy Messerschmitt (formerly with NTEC)

o Neva Sotolongo, California ARB

• State and tribal air quality agency personnel that provided QC review on the fire emissions inventory data.

• State and federal land management agency pe rsonnel that provided QC review on the fire emissions inventory data.WRAP 2002 PhII EI Report_20050722.doc 5 SECTION 2 

# THE 2002 WILDLAND FIRE EMISSION INVENTORY

The ETT established a number of fire event data ob jectives that were used to identify and utilize wildfire, WFU, and prescribed burning event data suitable for the 2002 fire emission inventory. Each individual entry in the “raw” fire activity database was analyzed to determine if all of the fire event data objectives were met in order for the record to be included in the fire emission inventory. For wildland fire, all activity data collected was at the event level, and summary data was rejected. The data objectives were:

• A specific location for each fire event.

• A specific calendar day in 2002 for each fire event.

• A specific size for each fire event.

• Sufficient information to assign a fu el loading for each fire event.
The wildfire, prescribed burning, and WFU emi ssion inventories were developed with parallel data gathering and emission calculation techni ques. The same basic inventory process was utilized with a few specific variations implem ented. A summary of the technical methods follows.
The wildland fire use events were originally classi fied as wildfire events in the database. They were processed as wildfire events and were identi fied as WFU events and treated separately from wildfire only after spatial and temporal allocati on, fuel loading and emi ssion calculations, and plume characterization had been completed. Therefor e, in this report, the term wildfire includes WFU data unless otherwise specified. 

## 2.1 Activity Data Wildfire activity data including WFU data were collected by the FEJF using a tiered process. Wildfires greater than 10 acres in size were so ught, but any fire record collected was used. Detailed activity data with sufficient spatial and temporal resolution were contained in the National Interagency Fire Center’s (NIFC) daily National Situation Report publication and ICS209 wildfire forms. The National Situation Repo rt database and ICS-209 databases were merged. Procedures were implemented to avoid includin g duplicate records in the merged data set.
In a companion effort, 2002 records from the Department of the Interior's Wildland Fire Management Data and the Departme nt of Agriculture’s Forest Serv ice National Interagency Fire Management Integrated Database were appended to form an independent “federal database” of fire events. Fire events in the National Situat ion Report/ICS-209 database were then paired with fire events in the “federal database.” The National Situation Report/ICS-209 database wasWRAP 2002 PhII EI Report_20050722.doc 6 supplemented on a record-by-record basis with lo cation, fire size, and fuel loading information from the “federal database” where necessary.
For prescribed fire activity, the FEJF set no de mi nimus activity level for burns. Air Sciences Inc., under the authority of the FEJF, made requests of air quality and/or department of forestry officials of each state in the WRAP region to prov ide wildland prescribed fire activity within their jurisdiction for 2002. Individual fire records were needed to satisfy precise temporal, spatial, and activity criteria for WRAP modeling purposes. Therefore, the FEJF requested:
1. Any information that could be used to asce rtain a prescribed fire’s location (i.e., legal location, latitude/longitude coordinates, and county). 2. Timing information (burn date or season) and/or fire duration. 3. Such fuels information as vegetation type , acres burned, tons burned, and burn type (piles or broadcast).
2002 prescribed fire information was received from each of the WRAP states. Generally, information received from interagency or st ate-facilitated smoke management programs encompassed prescribed fire data for multiple fe deral and state land management jurisdictions. DOI-1202 (Department of Interior), NIFPORS (Natio nal Fire Plan Operation Reporting System), and FASTRACS (Fuel Analysis, Smoke Tracking, and Report Access Computer System) data were received independently from federal agenci es. State data not closely matching federal prescribed fire totals reported by NIFC were augmented with prescribed fire records from the federal databases. Fire records having sufficient spatial, temporal, and activity components were formatted into a single region-wide prescribed fire activity inventory.
See Appendix A for a more detailed description of data gathering methods, results, and assumptions for each state and agency. 

### 2.1.1 Geo-Referencing Fire Location by Township/Range/Section and County Many of the records in the prescribed fire activity data set did not have latitude and longitude coordinates but did have location information in the form of a Township, Range and Section (TRS) or county identifier.
A geographic information system (GIS) algorithm was developed to convert, or geo-reference, TRS codes to a latitude and longitude coordinate pair using the National Atlas Public Land Survey System (PLSS) map of Township and Ra nge. Meridian was not available in the raw activity data and was assigned to each fire ba sed on state name. The fundamental steps of the TRS geo-referencing were:

1. Convert the fire record’s PLSS informat ion to Meridian Township Range (MTR) and Section code.WRAP 2002 PhII EI Report_20050722.doc 7 2. Locate that MTR on the PLSS map. 3. Within the MTR, estimate the location of the center of the Section. 4. Identify the latitude and longitude of this point. 5. Record the estimated geographic coordinates in the activity record.
In addition to this GIS-based method, legal location was geo-referenced using the “Wefald” TRSconversion software (TRS file v1.2, available at: http://members.cox.net/azregion/trs file/trsfile.htm). This software attempts to geo-reference TRS locations that are not technically part of the PLSS (for instance land grants and tribal lands) and hence do not appear in the official PLSS ma p relied upon in the GIS-based method. Legal description and state name for all wildland fire s were exported from the activity data to a comma-separated file specified by the Wefald so ftware. The Wefald software was run, and the output file with latitude and longitude was imported back to the emission inventory.
Thirdly, fires were geo-referenced by county identifier. If the county and state name matched the National Atlas county layer, the centroid coordinates of the county shape were written to the activity record.
In lieu of latitude and longitude coordinates be ing supplied in the raw data, fire events were located by (1) GIS-based TRS geo-referencing, (2 ) Wefald-based TRS geo-referencing, and, lastly, (3) county centroid. After geo-referencing the w ildland fire data, 17 fire records, corresponding to 16 individual prescribed fire events, had loca tions that were outside of the WRAP region. These records were dropped from the Phase II EI database but retained in a separate file for documentation purposes. 

### 2.1.2 GIS-Based NFDRS Fuel Loading Assignment Fire events in the wildfire and prescribed burning activity databases that did not contain fuel type in the source data were assigned a fuel mo del using GIS techniques. The fire’s location was plotted on the National Fire Danger Rating System (NFDRS) fuel model map, and the corresponding fuel model code was recorded to th e activity record. This procedure was applied to each record in the activity data base. The specific steps are:
1. A mappable point for the fire is created from its latitude and longitude. (Activity records are geo-referenced ba sed on their latitude and longitude.) 2. The fire point is converted to the different map projection of the NFDRS map. (Geographic coordinates are projecte d to Lambert Equal Area Azimuthal.) 3. The fire point is “dropped” on the NFDRS Fuel Model map. (The intersected grid cell is identified.)WRAP 2002 PhII EI Report_20050722.doc 8 4. The fuel model at that point, as a coded number, is identified. (Numeric fuel model attribute valu e is extracted from the grid cell.) 5. The numeric fuel model name is saved to the fire activity record. (Numeric fuel model code is written to a newly created field in the activity database.)
6. The numeric code is translated to the standard NFDRS Fuel Model letter code. (For all records, the fuel letter is looked up by fuel number and saved in a new field.)
Records receiving the “ag” designation were pres umed to occur in a grassland environment and assigned the same fuel loading as NFDRS Fuel Model C, pine-grass savanna. Activity records intersecting “water” and “barren” did not receive a fuel model assignment from this process. 

### 2.1.3 Final Activity Data Quality Control The wildland fire activity data set was quality- controlled using geographic information science. Logical inconsistencies were identified and recorded in the activity data set. Certain flaws were considered “fatal” and resulted in the record remaining in the activity data set, but being “dropped” from the emission inventory. Only re cords with a valid start and end date, location (latitude and longitude coordinate), non-zero fire size in acres, and calculable fuel loading in tons were carried over to the final emission inventory. The wildfire activity data set was supplied with 3,243 records. In total, 86 activity record s (2.7 percent) totaling 18,447 acres were dropped due to insufficient or inconsistent data, and 3,157 wildfire records were carried over to the final emission inventory. This corresponds to 1,820 indi vidual fire events (many individual fire events were multi-day events). The prescribed fire activity data set was supplied with 10,963 records. In total, 963 activity records (8.8 percent) tota ling 51,723 acres were dropped due to insufficient or inconsistent data, and 10,000 prescribed fire events were carried over to the final emission inventory. The majority of prescribed fire reco rds (~890) were dropped due to an invalid location input in term of TRS coordinates that could not be filled in the absence of a county code or name.


### 2.1.4 Wildland Fire Use Wildland Fire Use (WFU) was included as a unique fire type in this emission inventory. WFU events were originally categorized as wildfire s and were treated as wildfires for spatial and temporal allocation as well as emission calculations . Therefore, some of the tables and charts in this report categorize data only as wildfire and prescribed fire. In these cases, WFU is combined with wildfire.

Table 2 summarizes the fire events classified as WF U. The majority of WFU fire activity in the 2002 emission inventory occurred in Alaska: 79 percent of the acreage, 89 percent of the fuel consumed, and 89 percent of the PM 2.5 emissions. Other states wi th reported or allocated WFU activity included California, Colorado, Idah o, Montana, New Mexico, Utah, and Wyoming.WRAP 2002 PhII EI Report_20050722.doc 9 Information on WFU events was found in two data sources:

1. The DOI-1202 data contain a subset of data with a numerical code indicating WFU for the FWS, NPS, BLM, and BIA lands. 2. NIFMID data contains a subset of data that contained the WFU events for the U.S. Forest Service in 2002.

All the WFU records from both the DOI-1202 and the NIFMID data sets were extracted and compared to the wildland fire activity data. This comparison was based on (1) fire name, (2) fire date, and (3) fire acreage. The results of this comparison indicated that the majority of the WFU activity in the DOI-1202 and the NIFMID database s were indeed included in the Phase I EI wildfire data. All WFU records were assigned a unique label to distinguish these events from wildfire events in the database.
Table 2: Summary of Wildland Fire Use Data in Phase I EI

Source Data WFU Acres In Phase I EI (acres) In Phase I EI (%) DOI 1202 168,055 167,708 99.7 NIFMID 36,208 33,934 93.7 Total 204,263 201,642 98.7
Some of these discrepancies stem from the fact that the Phase I EI includes fire records ≥ 10 acres only, while the DOI-1202 and NIFMID databases includ e all fire sizes. Moreover, in some cases there were minor discrepancies between the acres included in the Phase I EI and the other data set for the same fire event. For the Phase I EI, the records in the original database were retained, and the discrepancy between the DOI 1202/NIFMID records and the Phase I EI records was not resolved (approximately 2,600 acres).
As a result of the large fire refinements and the wildland fire quality control process (each described later in this section), WFU activity was reduced by approximately 100 additional acres in the final Phase II EI. 

### 2.1.5 Natural and Anthropogenic Assignments (For All Fire Sources) Each wildfire, prescribed burn, agricultural bu rn, and non-federal rangeland burn in the WRAP Phase II EI for fire was flagged as natural or an thropogenic in origin. This was done using the following approaches, based on the WRAP Fire Emissions Joint Forum’s 2001 WRAP Policy for Categorizing Fire Emissions and Guidance for Classifying Natural Versus Anthropogenic Fire Emissions (under development). Further approaches for ca tegorizing natural and anthropogenic fires may be developed by the FEJF for subsequent Phase III and IV emission inventories.WRAP 2002 PhII EI Report_20050722.doc 10 The FEJF database for fire was amended with a field to flag each fire event as natural or anthropogenic. Also, the Source Classification Code (SCC) assignment performed in the database was refined to assign custom SCCs, which accommo date specific fire types discussed in this document. Each SCC present in the emission invent ory identifies each event as either natural or anthropogenic. The SCC stays with the fire ev ent in the SMOKE model-ready files delivered to the WRAP Regional Modeling Center (RMC) as we ll as in the NIF 3.0 files. These SCCs are defined in Table 3.

Table 3: SCCs and Their Fire Type and Natural/A nthropogenic Classification.
SCC Fire Type Natural or Anthropogenic 2810001000 Wildfire Natural 2810001001 WFU Natural 2810001002 WFU Anthropogenic 2801500000 Agricultural Anthropogenic 2801500001 Agricultural (Native American) Natural 2810015000 Prescribed Anthropogenic 2810015001 Prescribed Natural 2810016000 Non-Federal Rangeland Anthropogenic 2810016001 Non-Federal Rangeland Natural



### Wildfire All wildfire was categorized as natural. The SCC for wildfire (2810001000) was considered exclusively natural.



### Wildland Fire Use All Wildland Fire Use (WFU) incidents identified in the Phase II EI were categorized as natural. A custom SCC of 2810001001 was used to identify WFU natural events. It is helpful to note that by definition WFU is a distinct fire source from both wildfire and prescribed burning. That is, a WFU incident cannot also be considered wildfire or prescribed burning. In the event that entities within the WRAP modify the categorization of WF U incidents to include anthropogenic events, a custom SCC of 2810001002 has been reserved as a placeholder..


### Agricultural Fire All agricultural burning in the Phase II EI was categorized as anthropogenic and given the standard SCC of 2801500000.

The 2001 WRAP Policy for Categorizing Fire Emissions states that “vegetativ e burning conducted by Native Americans for traditional, religious, and ceremonial purposes” is considered natural and all other vegetative burning conducted by Native Americans is classified as “prescribed,” with agricultural burning fitting the definition of prescr ibed fire. Some agricultural fire events in theWRAP 2002 PhII EI Report_20050722.doc 11 Phase II EI fell within the exterior boundaries of tribal lands, but the Phase II EI lacked an indication of “traditional, religious, or ceremonial ” purpose. Therefore agricultural events falling on tribal lands were still categorized as anth ropogenic. A custom SCC of 2801500001 will be used in the future to classify agricultural burn ing determined to be of a natural origin.



### Prescribed Fire Prescribed fire was categorized as either natu ral or anthropogenic. The standard SCC of 2810015000 represented anthropogenic prescribed burns, and a custom SCC of 2810015001 represented natural burns.
Because the raw activity data for prescribed fire do not include a natural or anthropogenic identifier, nor do the raw data contain burnin g objective information (e.g., “maintenance” or “restoration”), the ETT elected to base the categorization of prescribed fire as natural or anthropogenic on the National Fire Danger Rating System (NFDRS) fuel model for each incident (Table 4). An NFDRS fuel model exists for each wildfire and prescribed burn in the Phase II EI. Each incident in the Phase II EI had only one NFDRS assignment based on the observed fuel model reported in the activity database (prefe rred) or was assigned by overlaying the fire location on the national NFDRS fuel model map using GIS (see the WRAP 1996 Fire Emission Inventory documentation). The NFDRS categorizat ions as natural or anthropogenic were based on examining the text descriptions of the fuel models and identifying the buildup of “above normal” fuel loadings (for example, the short-n eedle conifer models G and H as anthropogenic and natural, respectively).
Regardless of NFDRS fuel model, all piled prescr ibed burns were categorized as anthropogenic.WRAP 2002 PhII EI Report_20050722.doc 12 Table 4: Prescribed Fire NFDRS Fuel Mode l Categorization as Natu ral or Anthropogenic

NFDRS Fuel Model Categorization Short Vegetation Description A Natural Western annual grasslands B Anthropogenic Tall dense older brush C Natural Open pine with grass understory D Natural Southeast fuel types E Natural Hardwood after leaf fall F Natural Mature closed Chamise with Oakbrush G Anthropogenic Dense Conifer with heavy downed duff H Natural Short-needled Conifer with thin litter I Anthropogenic Clearcut Conifer Slash <6" J Anthropogenic Clearcut heavily thinned Conifer Slash <6" K Anthropogenic Light conifer slash partial cuts L Natural Western perennial grasslands N Natural Southeast fuel types O Natural Southeast fuel types P Natural Southeast fuel types Q Natural Upland Alaska Black Spruce R Natural Hardwoods after leafout S Natural Alpine Tundra and grass T Natural Sagebrush and grasslands U Anthropogenic Closed Western Long-Needled Pine Piles Anthropogenic Piled activity fuels



### Non-Federal Prescribed Rangeland Burning The ETT elected to assign all non-federal rangeland burning events in the Phase II EI as natural. This decision was deemed to be consistent with the intent of the WRAP’s categorization policy. The decision is also based on the facts that fu el loading assignments for non-federal rangeland burning events are assigned generally (i.e., there are no event-specific fuel loading data for nonfederal rangeland fire events in the inventory) and fu el loading is low (1.75 tons of fuel per acre). All prescribed rangeland burning events on non-fe deral lands in the Phase II EI were categorized as natural and given a custom SCC of 2810016001. The SCC 281001600 will be reserved for anthropogenic non-federal rangeland burning in case the categorization technique changes for the FEJF’s Phase II and Phase IV emission inventory projects.
The ETT also acknowledged the following:

• Non-federal rangeland burning should be re garded similarly to wildland prescribed burning in that efforts to control emissi ons should be implemented when and where possible.WRAP 2002 PhII EI Report_20050722.doc 13 • The FEJF’s fire tracking system (to be developed) should accommodate data that indicates the stated objective(s) of non-federal rangeland burning events.

• The categorization technique for non-federa l rangeland burning may be modified for future inventories. 

## 2.2 Fuel Loading and Emission Factors In the event that fire event-specif ic fuel loading values were not contained in the database record, fuel loading in tons per acre for the wildfire inventory were assigned using the NFDRS fuel model codes and a table of fuel loading values for NFDRS fuel model categories (Cohen and Deeming, 1985). In addition to the default NFDR S fuel loadings, additional fuel loading was added to each category to adjust for fuel pr esent as duff and tree crowns. Similarly, for prescribed fire events for which no fuel loadin g value was available, the prescribed fire fuel loading values were the same as those used for the wildfire inventory. “Adjusted” NFDRS fuel loading assignments for wildfire and prescribed burning differed by the percent consumption assumed for live fuels, duff, and crown components . Table 5 presents the adjusted NFDRS fuel loading assignments for wildfire and prescribed burning.
An emission factor suite was developed to apply to wildfire and prescribed fire activity data. The emission factor suite included one look-up ta ble for wildfire and prescribed broadcast burns and one table for prescribed pile burns. The twelve pollutants included were total suspended particulate matter (TSP), particulate matter less than 10 microns in diameter (PM 10 ), particulate matter less than 2.5 microns in diameter (PM 2.5 ), elemental carbon (EC), organic carbon (OC), non-methane volatile organic compounds (VOC), methane (CH 4 ), ammonia (NH 3 ), oxides of nitrogen (NO x ), carbon monoxide (CO), sulfur dioxide (SO 2 ), and coarse particulate matter– defined as the difference between PM 10 and PM 2.5 (PMC). The emission factor suite consists of two look-up tables. Two emission factor refere nces were drawn upon: the U.S. Environmental Protection Agency’s (U.S. EPA) AP-42 Section 13.1 and an emission inventory methods survey report (Battye, 2001) funded by the U.S. EPA Office of Air Quality Planning and Standards (OAQPS). The emission factor suite is a compila tion of emission factors and emission factor relationships (multipliers) from both documents. Table 6 lists the emission factors used for the Phase II EI.
In addition to smoldering consumption incorporat ed into the NFDRS fuel loading table, distinct smoldering emissions were added to the emission inventory on the day after certain wildland fire days. The FEJF applied day-after smoldering to each day of a wildfire and prescribed broadcast burn with fuel loadings greater than 5.0 tons per acres (personal communication, David Sandberg, FEJF). Seventeen percent of the emi ssions on a wildfire day and 8.5 percent of the emissions on a prescribed broadcast burn day were added to the emission inventory at the same location on the following day. Prescribed pile burns did not have addi tional smoldering days added.WRAP 2002 PhII EI Report_20050722.doc14Table 5: Summary of Fuel Loading and Consumption by NFDRS ModelDead and live fuel loadings were based on Cohen and Deeming (1985). Values in parentheses indicate total fuel loading for prescribed fire. Anasterisk (*) after the NFDRS model description indicates the wildfire emissions were augmented for smoldering consumption.Dead Fuels (tons/acre) Live Fuels(tons/acre) Additional (tons/acre)NFDRSAbbr. NFDRS Model DescriptionTotal(Rx fire)(tons/acre)1-hour10-hour100-hour1,000-hourFineWood Herbaceous Duff CrownA Western grasses (annual) 0.50 0.20 0.00 0.00 0.00 0.00 0.30 0.00 0.00B California chaparral 19.5 3.50 4.00 0.50 0.00 11.50 0.00 0.00 0.00C Pine-grass savanna 4.7 0.40 1.00 0.00 0.00 0.50 0.80 4.00 0.00D Southern rough * 15.6 (10.6) 2.00 1.00 0.00 0.00 3.00 0.75 7.70 8.00E Hardwood litter (winter) * 3.8 1.50 0.50 0.25 0.00 0.50 0.50 1.10 0.00F Intermediate brush 15.0 2.50 2.00 1.50 0.00 9.00 0.00 0.00 0.00G Short needle (heavy dead) * 43.5 (25.6) 2.50 2.00 5.00 12.00 0.50 0.50 18.20 19.20H Short needle (normal dead) * 27.5 (15.0) 1.50 1.00 2.00 2.00 0.50 0.50 16.90 18.70I Heavy slash * 55.1 (49.1) 12.00 12.00 10.00 12.00 0.00 0.00 18.20 0.00J Intermediate slash * 34.0 (31.2) 7.00 7.00 6.00 5.50 0.00 0.00 16.90 0.00K Light slash * 14.4 (13.1) 2.50 2.50 2.00 2.50 0.00 0.00 9.70 0.00L Western grasses (perennial) 0.75 0.25 0.00 0.00 0.00 0.00 0.50 0.00 0.00N Saw grass * 5.0 1.50 1.50 0.00 0.00 2.00 0.00 0.00 0.00O High pocosin * 46.1 (45.1) 2.00 3.00 3.00 2.00 7.00 0.00 58.20 0.00P Southern pine plantation * 16.4 (10.2) 1.00 1.00 0.50 0.00 0.50 0.50 13.30 10.00Q Alaskan Black Spruce 57.6 (48.8) 2.00 2.50 2.00 1.00 4.00 0.50 57.90 26.80R Hardwood litter (summer) * 3.1 0.50 0.50 0.50 0.00 0.50 0.50 1.10 0.00S Tundra * 19.3 (19.1) 0.50 0.50 0.50 0.50 0.50 0.50 32.60 0.00T Sagebrush grass * 4.5 1.00 0.50 0.00 0.00 2.50 0.50 0.00 0.00U Western pines * 19.1 (10.3) 1.50 1.50 1.00 0.00 0.50 0.50 10.60 14.20WRAP 2002 PhII EI Report_20050722.doc 15 Table 6: Summary of Emission Factors Summary of emission factors (EF) in pounds per to n for prescribed burning. In the case of piled fuels, when two sources are mentioned, the first source refers to the emission factor and the second to the empirical relationship used to derive that emission factor.

Prescribed Fire

Piled Fuels Prescribed Fire Non-Piled Pollutant EF Source EF Source TSP 12.0 AP42 1 34.1 AP42 PM 10 8.0 AP42 28.1 OAQPS PM 2.5 8.0 AP42 24.1 OAQPS Elemental Carbon 0.6 AP42, OAQPS PM 2.5 * 0.072 1.5 OAQPS Organic Carbon 4.3 AP42, OAQPS PM 2.5 * 0.54 11.6 OAQPS VOC 6.3 AP42, OAQPS CO * 0.085 13.6 OAQPS CH 4 7.7 OAQPS 2*(42.7-43.2*CE) 13.6 OAQPS NH 3 0.5 AP42, OAQPS CO * 0.0073 1.3 OAQPS NO x 6.2 OAQPS 6.2 OAQPS CO 74.3 AP42 289.0 OAQPS SO 2 1.7 OAQPS 1.7 OAQPS PM coarse 0.0 PM 10 – PM 2.5 4.0 PM 10 – PM 2.5



### 2.2.1 Pollutant Speciation In the development of all of the fire emissions inventories (1996, 2002, 2018) prepared for the FEJF, Air Sciences and the WRAP’s Regional Modeling Center (RMC) have relied upon mathematical relationships with other pollutants to derive estimates of varies species of pollutants, including, elemental carbon (EC), organic carbon (OC), ammonia (NH 3 ), and methane (CH 4 ). While the emission inventory system has included calculated estimates for several of these pollutant species, in general, the RMC has derived emission quantities for these pollutants as part of the pre-modeling data processing step s (i.e., the RMC has not used the values for EC, OC, NH 3 , and CH 4 included in the emission inventory f iles provided by Air Sciences). This section simply documents the current mathematic al relationships being utilized to represent emissions of EC, OC, NH 3 , and CH 4 in the fire emissions inve ntory and modeling systems.
Table 7 includes the mathematical relationships currently utilized by the RMC to prepare estimates of several pollutant species.

1 AP-42, Section 13.1, Table 13.1-3, Logging Slash Debris, No Mineral Soil, weighted aver age of flaming and smoldering.WRAP 2002 PhII EI Report_20050722.doc 16 Table 7: Pollutant Species’ Mathematical Relationships Currently in use by RMC

Pollutant Species Agricultural & Prescribed

Multiplier Pollutant Relationship Wildfire Multiplier Pollutant Relationship EC 0.075 X PM 2.5 0.09 X PM 2.5 OC 0.6389 X PM 2.5 0.636 X PM 2.5 Nitrates (PN03) (particulate) 0.0063 X PM 2.5 0.0 X PM 2.5 Sulfates (PS04) (particulate) 0.0154 X PM 2.5 0.0 X PM 2.5 Fine particulate 0.2644 PM 2.5 -EC-OCPN03-PS04 0.274 PM 2.5 -EC-OCPN03-PS04 Aldehydes 0.205 X VOC 0.205 X VOC Ethanes 0.1911 X VOC 0.1911 X VOC Non-reactive hydrocarbons 0.2247 X VOC 0.2247 X VOC

Olefins 0.0310 X VOC 0.0310 X VOC Paraffins 0.5511 X VOC 0.5511 X VOC

Air Sciences’ emission inventory systems have no t included estimates for all of the pollutant species identified in Table 7 (above). Table 8 includes the mathematical relationships currently utilized in Air Sciences’ emission inventory syst em to prepare estimates of several pollutant species. For species for which the emission factor s were taken directly from the literature, Table 8 shows the calculated relationship between the po llutant species and the parent pollutant. For agricultural burning, emission factors as provid ed by Bryan Jenkins, Ph.D., UC Davis, are cropspecific and the derivation of each pollutant’s em ission factor is not provided. Therefore, Table 8 shows the range, average (avg), and median (med ) of the mathematical relationship between the pollutant species and the parent pollutant.WRAP 2002 PhII EI Report_20050722.doc 17 Table 8: Pollutant Species’ Mathematical Relati onships Currently in use in Air Sciences Emission Inventory System
Wildland Fire (wildfire and Rx broadcast burns) Prescribed Fire - Piled Fuels Agricultural Burning

Pollutant EF Source/ Relationship EF Source/ Relationship EF Source/ Relationship AP42, OAQPS Elemental Carbon 1.5 OAQPS/ 0.6224 x PM 2.5 0.6 PM 2.5 * 0.072 Varies by crop. 0.15 to 0.31 x PM 2.5 avg = 0.25 med = 0.26 AP42, OAQPS Organic Carbon 11.6 OAQPS/ 0.4813 x PM 2.5 4.3 PM 2.5 * 0.54 Varies by crop. 0.21 to 0.5 x PM 2.5 avg = .44 med = .45 AP42, OAQPS VOC 13.6 OAQPS/ 0.047 x CO 6.3 CO * 0.085 Varies by crop. 0.04 to 0.18 x CO avg = 0.10 med = 0.09 OAQPS CH 4 13.6 OAQPS 7.7 2*(42.7-43.2*CE) CE=0.9 Varies by crop. 0.82 to 19.76 avg = 7.78 med = 8.60 AP42, OAQPS NH 3 1.3 OAQPS/ .0045 x CO 0.5 CO * 0.0073 Varies by crop. 0.02 x CO

PM coarse 4.0 PM 10 – PM 2.5 0 PM 10 – PM 2.5 Varies by crop. PM 10 – PM 2.5

Reference: PM 10 28.1 OAQPS 8.0 AP42 Varies. UC Davis PM 2.5 24.1 OAQPS 8 AP42 Varies. UC Davis CO 289 OAQPS 74.3 AP42 Varies. UC Davis



## 2.3 Emission Calculations For wildfire and prescribed burning, daily emissi ons were calculated as fuel consumed (tons of fuel) multiplied by each emission factor (pound s of pollutant per ton of fuel). Total fuel consumed was either extracted directly from the activity data (more often the case with prescribed fire) or was calculated as the size of the fire (acres burned) multiplied by the “adjusted” NFDRS fuel loading value (tons of fuel per acre burned). For wildfires and prescribed broadcast burns of fuel model types with a fuel loading greater than 5 tons per acre, additional smoldering emissions were assigned to the sa me location on the following calendar day.WRAP 2002 PhII EI Report_20050722.doc 18 

### 2.3.1 Daily Fire Growth Allocation The wildfire and prescribed burn emission inventor ies were required to be resolved to the day, but wildfires and prescribed burns were reported both as individual fire days and as single records spanning a number of days. Therefore, the acres burned, total fuel loading consumed, and emissions per pollutant of multi-day records we re allocated to individual days to indicate their “fire growth.” In the emission inventory database, new records were appended to add new daily fire events where before there was only a single multi-day record. The final date for all records was coded in “mm/dd/yy” format. The or iginal multi-day record was overwritten with the first day’s allocation.
Records that only indicated one day’s reporting of activity (i.e., the end date was the same as the start date) were skipped over by this daily allo cation step. A multi-day event was allocated to individual fire days only if its size was greater than 100 acres. Fires less than or equal to 100 acres were assigned in their entirety to the activity record’s start date. The growth rate for wildfires and prescribed fires was then allocated differently:



### Wildfire Wildfire and WFU events greater than 100 acres were allocated to the first two-thirds of the duration implied in the source data. The durati on of fire growth in days for wildfire was calculated as:
Wildfire Duration (Days n ) = Ceiling [2/3 (startdate – enddate + 1)] Equation 1
Beginning on the start date, values were allocated to the subsequent calendar days across this shortened duration. The FEPS “spreading oval” algorithm was used to emulate a geometric firegrowth (FEPS version 1.0 Jan-04 Eqn. 20). The fire growth of each day as a percent of the multiday total was calculated as: Percent Day i = (Day i 2 / Days n 2 )) - (Day i- 1 2 / Days n 2 ) Equation 2

Where: i = sequence number of day from the event’s start date, and
n is the total number of days in the shortened wildfire duration from Equation 1.
The daily allocation percent was applied to the mult i-day values to arrive at daily fire growth in acres burned, tons consumed, and tons emitted per pollutant. 2



### Prescribed Fire For multi-day prescribed fires greater than 100 acre s, size, loading, and emissions were allocated evenly across every day from reported start date to end date, inclusive.

2 The ETT recognizes that the spreading ov al technique may not accurately represent the daily growth rate of large multiday events in certain fuel types in Alaska. The FEJF may wish to revise the daily fire growth allocation for Alaska fire events in future emission inventories.WRAP 2002 PhII EI Report_20050722.doc 19 

## 2.4 Plume Profile A plume profile tailored for wildland fire was assign ed to each daily fire event. Normally, plume rise is predicted using hourly pyrotechnical and meteorological information. However, given the unique physical characteristics of wildland fire events and previous experience with dispersion models that indicated poor performance with regard to dispersing smoke plumes, the FEJF utilized expert opinion to assign plume characteristics to each fire event.


### 2.4.1 Virtual Acres
Fires were classified into size classes based on “virtual acreage.” The virtual acreage was calculated by multiplying the actual fire size by the square root of the normalized pre-burn fuel loading (Equation 3). This was done in order to relate fuel loading to the characteristic “stack” diameter of the plume. Total fuel loading was no rmalized to 13.8 tons per acre for wildfire and 5.0 tons per acre for prescribed fire. The norma lizer for wildfire was equal to the total surface loading plus a portion of the crown biomass of NFDRS fuel model U (western pines). The prescribed fire normalizer is equal to the surface loading only of NFDRS fuel model U.



### Normalizer / Loading Fuel Acreage Acreage actual virtual 

### ⋅ = Equation 3

The plume profile for days added to model smolderi ng for the day after an original activity day was the same as for the original fire event. In the emission inventory, the smoldering events retained the virtual acreage of the fire even t they were created from, and thus the plume calculations were identical. 

### 2.4.2 Diurnal Consumption A diurnal fuel consumption table was created to a llocate daily wildland fire emissions by hour (Table 9). The table, consisting of a percent of fuel consumed for each hour of the day, summing to 100, was submitted to the Air Quality Modeling Forum (and the WRAP’s Regional Modeling Center [RMC]). The diurnal fuel consumption table was implemented by the RMC within the SMOKE emissions processor to allocate daily emission estimates to hourly emissions.
Table 9: Standard Diurnal Consumption Template Used to Distribute Fire-Total Heat Production and Emissions

Hour 1 2 3 4 5 6 7 8 9 10 11 12 % Per Hour 0.57 0.57 0.57 0.57 0.57 0.57 0.57 0.57 0.57 2.00 4.00 7.00

Hour 13 14 15 16 17 18 19 20 21 22 23 24 % Per Hour 10.00 13.00 16.00 17.00 12.00 7.00 4.00 0.57 0.57 0.57 0.57 0.57WRAP 2002 PhII EI Report_20050722.doc 20 

### 2.4.3 Fire Size Classes and Plume Profile Calculations Plume values include the top and bottom of the plume (Ptop and Pbot, respectively; both expressed in meters above ground elevation) an d the percent of emissions entrained within the surface layer of the atmosphere (Lay1F), defined by the ETT of the FEJF as the first 38 meters above the ground. 3 These three plume parameters are esta blished and assigned for each of the 24 hours of each daily fire event. All of the pl ume values were assigned based on the limited information available for each fire event, including fire size (fire area grown per day) and either a reported fuel loading or the NFDRS fuel model.
Five plume classes were defined with increasing potential plume heights to reflect the range of “heat release” possible in wildland fires (Table 10). Plume bottom heights and percent of the plume fumigated to the first layer of the atmosphere were also developed for the five plume classes. Using expert opinion and anecdotal eviden ce, a table of hourly buoyant efficiency values was derived (Table 11).

Table 10: Fire-Related Paramete rs as Function of Fire Size Classes

Class 1 2 3 4 5 Size (virtual acres) 0 – 10 >= 10 – 100 >= 100 – 1,000 >= 1,000 – 5,000 >= 5,000 BE size 0.40 0.60 0.75 0.85 0.90 Ptop max (m) 160 2,400 6,400 7,200 8,000 Pbot max (m) 0 900 2,200 3,000 3,000

Table 11: Buoyant Efficiency as Function of Hour of Day

Hour 1 2 3 4 5 6 7 8 9 10 11 12 BE hour 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.06 0.10 0.2 0.4

Hour 13 14 15 16 17 18 19 20 21 22 23 24 BE hour 0.7 0.8 0.9 0.95 0.99 0.8 0.7 0.4 0.06 0.03 0.03 0.03
Equations were used to calculate Pt op and Pbot as a function of time of day and size of the fire (expressed in terms of virtual acre s). Note that the calculations used an hourly value for buoyant efficiency (Table 11) and heat release value based on fire size, also referred to as normalized fire growth.

3 The height of the first (lowest) vert ical layer is 38 m in the WRAP’s Regional Modeling Center’s model setup. The calculation methodology for the Lay1F va lues have been reviewed (by Air Sciences and the USDA Pacific Wildland Fire Sciences Lab) and assessed to be reasonabl e with no additional scaling. The ma ximum bottom of plume values was revised downward for the three largest fire size classes (a lso based on discussions with the USDA Pacific Wildland Fire Sciences Lab).WRAP 2002 PhII EI Report_20050722.doc 21 

### 0.0 0.2 0.4 0.6 0.8 1.0

0 2 4 6 8 10 12 14 16 18 20 22 HourBuoyant efficiency The hourly top of the plume was calculated as follows: 

# ( )( )

max 2 size 2 hour hour 

### Ptop * BE * BE Ptop = Equation 4 Where: BE is the buoyant efficiency looked up from the hourly or size class tables. The hourly bottom of plume was similarly calculated as: 

# ( )( )

max 2 size 2 hour hour 

### Pbot * BE * BE Pbot = Equation 5 Lastly, an equation was used to calculate Lay1F, the proportion of emissions fumigated into the first atmospheric layer. Lay1F was calculated as the arithmetic inverse of the hour-specific buoyant efficiency multiplied by th e size-specific buoyant efficiency. 

# ( ) size hour hour 

### BE * BE

- 1 

### Lay1F = Equation 6 Using Equations 3 through 6, the bottom and top of the atmospheric plume as well as the proportion of the plume fumigated into the first atmospheric surface layer were all scaled to fire size, fuel loading (incorporated in virtual acres calculation), and hour of the day. Figures 1 through 4 illustrate the relationships described above.
Figures 1 through 9 illustrate the hourly plume ch aracteristics (Ptop, Pbot, and Lay1F) assigned to each of the five fire size classes into whic h daily fire events in the Phase II EI have been assigned (Class 1 - less than 10 acres; Class 2 – 10 to 100 acres; Class 3 – 100 to 1,000 acres; Class 4 – 1,000 to 5,000 acres; Class 5 – greater than 5,000 acres). Also shown on Figures 5 through 9 is the height (38 m) of the first vertical atmosp heric layer (as designated by the WRAP’s RMC).

Figure 1: Buoyant Efficiency The relationship between buoyant efficiency and time of day.WRAP 2002 PhII EI Report_20050722.doc 22 

### Projected Top of Plume

1.0 10.0 100.0 1000.0 10000.0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
HourPlume height (m) [log-scale] >5000 1000-5000 100-1000 10-100 <10 Figure 2: Projected Top of Plume The projected top of the atmospheric plume (meters) as a function of time of day and fire size. Fire sizes represent the upper cutoff of the fire si ze categories. The lowest line represents the 10- acre cutoff. Note the logarithmic scale on the Y-axis.WRAP 2002 PhII EI Report_20050722.doc 23 

### Projected Bottom of Plume

1.0 10.0 100.0 1000.0 10000.0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
HourPlume height (m) [log-scale] >5000 1000-5000 100-1000 10-100 <10 Figure 3: Projected Bottom of Plume The projected bottom of the atmospheric plume (meters) as a function of time of day and fire size. Fire sizes represent the upper cutoff of the fire si ze categories. The line representing the 10-acre cutoff is constant at a value of zero.WRAP 2002 PhII EI Report_20050722.doc 24 Figure 4: Proportion of Plume in Surface Layer The proportion of the plume fumigation to the at mospheric surface layer (<38 m) as a function of time of day and fire size. Fire sizes represent the upper cutoff of the fire size categories. The highest line represents the 10-acre cutoff.


### Percent Entrained Lowest Vertical Layer

0% 25% 50% 75% 100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
HourPlume height (m) [log-scale] >5000 1000-5000 100-1000 10-100 <10WRAP 2002 PhII EI Report_20050722.doc 25 Figure 5: Fire Size Class 1 Plume Characteristics This figure shows plume characteristics (Ptop, Bb ot, and Lay1F) for Class 1 fires for each hour. Plume height in meters is shown on the left Y-ax is (in log-scale), and Lay1F in percent entrained into the lowest vertical layer is shown on the righ t Y-axis. For reference, the height of the lowest vertical layer (38 m) is shown in red.

WRAP Plume Rise Class 1: Virtual Acres <10

1 10 100 1000 10000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
HourPlume height (m)

0% 25% 50% 75% 100%% entrained in lowest vertical layer P_top P_bot Reference Lay1FWRAP 2002 PhII EI Report_20050722.doc 26 WRAP Plume Rise Class 2: Virtual Acres 10-100

1 10 100 1000 10000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
HourPlume height (m)

0% 25% 50% 75% 100%% entrained in lowest vertical layer P_top P_bot Reference Lay1F Figure 6: Fire Size Class 2 Plume Characteristics This figure shows plume characteristics (Ptop, Bb ot, and Lay1F) for Class 2 fires for each hour. Plume height in meters is shown on the left Y-ax is (in log-scale), and Lay1F in percent entrained into the lowest vertical layer is shown on the righ t Y-axis. For reference, the height of the lowest vertical layer (38 m) is shown in red.WRAP 2002 PhII EI Report_20050722.doc 27 Figure 7: Fire Size Class 3 Plume Characteristics This figure shows plume characteristics (Ptop, Bb ot, and Lay1F) for Class 3 fires for each hour. Plume height in meters is shown on the left Y-ax is (in log-scale), and Lay1F in percent entrained into the lowest vertical layer is shown on the righ t Y-axis. For reference, the height of the lowest vertical layer (38 m) is shown in red.

WRAP Plume Rise Class 3: Virtual Acres 100-1000

1 10 100 1000 10000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
HourPlume height (m)

0% 25% 50% 75% 100%% entrained in lowest vertical layer P_top P_bot Reference Lay1FWRAP 2002 PhII EI Report_20050722.doc 28 Figure 8: Fire Size Class 4 Plume Characteristics This figure shows plume characteristics (Ptop, Bb ot, and Lay1F) for Class 4 fires for each hour. Plume height in meters is shown on the left Y-ax is (in log-scale), and Lay1F in percent entrained into the lowest vertical layer is shown on the righ t Y-axis. For reference, the height of the lowest vertical layer (38 m) is shown in red.

WRAP Plume Rise Class 4: Virtual Acres 1000-5000

1 10 100 1000 10000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
HourPlume height (m)

0% 25% 50% 75% 100%% entrained in lowest vertical layer P_top P_bot Reference Lay1FWRAP 2002 PhII EI Report_20050722.doc 29 WRAP Plume Rise Class 5: Virtual Acres >5000

1 10 100 1000 10000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
HourPlume height (m)

0% 25% 50% 75% 100%% entrained in lowest vertical layer P_top P_bot Reference Lay1F Figure 9: Fire Size Class 5 Plume Characteristics This figure shows plume characteristics (Ptop, Bb ot, and Lay1F) for Class 5 fires for each hour. Plume height in meters is shown on the left Y-ax is (in log-scale), and Lay1F in percent entrained into the lowest vertical layer is shown on the righ t Y-axis. For reference, the height of the lowest vertical layer (38 m) is shown in red.



## 2.5 Approach for Technical Refinements of Large Fires and Fire Complexes for WRAP Phase I Fire Emission Inventory This section summarizes the proposed technical approaches to refine the wildfire activity data represented in the Western Regional Air Part nership (WRAP) Phase I EI. The technical approaches for the three following tasks are discussed in this section.

• Complex fire identification.

• Identification of blackened versus perimeter acres.

• Refinements of spatial, temporal, and fuel loading data for large fires.
In order to address these tasks, the largest 28 wildfires in the Phase I EI (all near or above 50,000 acres) were examined for availab ility of more refined spatial data. This information was obtained through Internet searches combined with follo w-up phone calls with the appropriate Federal Land Manager (FLM). The type of fire-event -specific information included Burned Area Emergency Response reports (BAER reports), Environmental Impact Statements, GIS-files provided by the national forests or obtained through the internet, as well as other web-based fire event information. Availability of these resources varied from fire to fire. Table 12 presents theWRAP 2002 PhII EI Report_20050722.doc 30 list of large fires for which the availability of fire -specific digital information was researched. The list of fire complexes researched includes thos e in Table 12, as well as several smaller fire complexes.
Table 12: Summary of Available Data for Large Wildland Fires in Phase I EI “---“ indicates no data available or located.

Fire Name State Perimeter Acres Fuels Information Fire Severity Information GIS-based Fire Perimeter Biscuit OR 499,570 Tabular 1 /GIS Tabular GIS 4 Rodeo/Chediski AZ 468,638 Tabular 1 /GIS Tabular/GIS 3 GIS 3 Geskamina Lake AK 257,258 GIS --- Fire history GIS Reindeer AK 227,800 GIS --- Fire history GIS Minunchima Group AK 196,584 GIS --- Fire history GIS Yetna River AK 152,962 GIS --- Fire history GIS McNalley CA 150,696 Tabular 1 /GIS Tabular/GIS 3 GIS 3 Hayman CO 137,760 Tabular 2 /GIS Tabular/GIS 3 GIS 3 Sischu AK 128,983 GIS --- Fire history GIS Tool Box OR 120,085 Tabular 1 /GIS GIS 4 GIS 4 Moose Lake AK 117,648 GIS --- Fire history&GIS 3 MP 78 AK 115,328 GIS --- Fire history GIS Rattle UT 94,519 GIS Tabular/GIS 4 GIS 4 Ponil Complex NM 92,194 GIS GIS 4 GIS 4 Vinasale AK 92,000 GIS --- Fire history GIS Long Creek AK 74,931 GIS --- Fire history GIS Galatea Creek AK 74,511 GIS --- Fire history GIS Kraft Springs MT 69,900 Tabular 1 Tabular --- Windy AK 69,523 GIS --- Fire history GIS Tiller Complex OR 68,775 GIS GIS 4 GIS 4 Missionary Ridge CO 66,534 GIS Tabular/GIS 3 GIS 3 Sanford UT 64,972 Tabular 1 /GIS Tabular/GIS 4 GIS 4 Spurs AK 64,834 GIS --- Fire history GIS Bear Creek AK 63,634 GIS --- Fire history GIS Pines CA 61,705 --- --- --- Khotol Riv AK 50,811 GIS --- Fire history GIS Boulder OR 48,080 --- --- --- Kraft Complex ND 48,000 --- --- --- **Acres Researched** 3,678,235 (58 % of Phase I WF EI) **GIS Acres (potential)**  3,512,255 (55 % of Phase I WF EI)

Notes: 1 Tabular fuel model distribution derived from vegetation descriptions (hardcopy).
2 Tabular fuel model provided by source (hardcopy). Digital GIS fire perimeter data was either downloaded from the internet (GIS 3 ) or obtained from the U.S. Forest Service (GIS 4 ).WRAP 2002 PhII EI Report_20050722.doc 31 

### 2.5.1 Complex Fire Identification 2.5.1.1 Analysis and Results The goal of this analysis was to identify potentia l duplicate fire entries that might be present in the database. A fire event could occur more than once in the emission inventory database if, for example, the fire name was changed over the course of time. This can occur when multiple fires are merged into a single fire complex. In this situation, the initial fire names are generally dropped, and all fires get assigned a common name . The Alaska fires could not be checked for the potential of duplicates since information on individual fires that might make up the larger complexes was not available (personal communication , Sue Christensen, Alaska Fire Service). Of the fire complexes in the WRAP states in th e lower 48 the following fires were examined:
1. Wildfires (including WFU) above approximately 50,000 acres, regardless of fire name. 2. Wildfires (including WFU) between 6,000 and 50,000 acres with names ending in “Complex.”
Although all fires with names ending in “Compl ex” were identified, only those above 6,000 acres (cumulative acres) were researched in the (online) National Fire Incident Situation Reports for 2002. The portion of fire complexes not included in the analysis contained 23 fire complexes sized from 100 to ~4,000 acres, and totaling ~26,000 acres. The fire complexes were examined for (1) the individual fires that made up the complex and (2) the potential duplicate presence of these individual fires in the Phase I EI based on fire name and fire event date(s).
Table 13 summarizes the results for the fire complexe s included in this research. For the total of 24 large fires and fire complexes that were researched , 18 were identified as actual fire complexes. Out of these 18 fire complexes, 13 complexes had potential duplicate entries in the Phase I EI, based on 26 potential duplicate fires. A total of approximately 260,000 acres that might have been double-counted in the Phase I EI was identified. In the second step of this quality control procedure, these potential duplicates were compared by fire location. Specifically, the distance from the fire complex coordinates to the coordina tes of its comprising fires was calculated. The distances varied from zero (identical coordinates) to approximately 57 miles. Most of the calculated distances were short enough to fall with in a reasonable fire perimeter based on the size of the fire.WRAP 2002 PhII EI Report_20050722.doc 32 Table 13: Summary of Complex Fire Check Based on Duplicate Names Only “---“ indicates no duplicates found by checking fire names; “NA” indicates not applicable.

Fire Name State Perimeter Acres Fires Included in Phase I EI Event Potential Duplicate Events Identified (acres) Distance (mi)

Biscuit OR 499,570 Biscuit fire Florence fire Sourdough fire Sour Biscuit (41,897 acres)

---

--- 25

---

--- Rodeo/Chediski AZ 468,638 Chediski fire Rodeo fire ---

--- ---

--- McNalley CA 150,696 One fire name only NA --- Hayman CO 137,760 One fire name only NA ---

Tool Box OR 120,085 Toolbox fire Silver fire Winter fire --- Silver (24,565) Winter (69,673; 2 duplicate sets) --- 8 21
Rattle UT 94,519 Black Canyon fire Diamond Creek fire Black Canyon (5,970) Diamond Creek (1,300) 0 14

Ponil Complex NM 92,194 Middle Ponil Fire Medcalf Fire

Office Fire

Turkey ---

---

--- Turkey (1,295) ---

---

--- 13 Kraft Springs MT 69,900 One fire name only NA ---

Tiller Complex OR 68,775 Tallow Acker Boulder fire

Buckeye Big Bend Ruby Red Buster Springs Digger Anderson Wilderness Tallow (1,132) Acker (4,114) Boulder (48,080) Buckeye (2,212) Big Bend (10,063)

---

---

--- Anderson (457)

--- 7 3 3 5 6

---

---

--- 12

--- Missionary Ridge CO 66,534 One fire name only NA ---
Sanford UT 64,972 Sanford Rx burn Adams Rx burn ---

--- ---

---

Kraft ND 48,000 Kraft Bale II Twin II Kenel Again --- Bale II (1,076) Twin II (450)

--- --- 28 23

---WRAP 2002 PhII EI Report_20050722.doc 33 Table 13: Summary of Complex Fire Check Based on Duplicate Names Only - continued “---“ indicates no duplicates found by checking fire names; “NA” indicates not applicable.

Fire Name State Perimeter Acres Fires Included in Phase I EI Event Potential Duplicate Events Identified (acres) Distance (mi)MonumentMalheur OR 44,062 Roberts Easy Monument ---

---

--- ---

---

--- Daley WY 42,000 Daley Draw Hairy --- Hairy (13,000) --- 1 Mahogany OR 41,328 Atkins Mahogany Mountain Atkins (800)

--- 12

---

--- Trinidad CO 33,000 Spring James John ---

--- ---

--- Mt. Zirkel CO 31,016 Burn Ridge Hinman Burn Ridge (8,260) Hinman (10,176) 0 7 Quartz Mt. WA 12,144 Quartz Mountain Middle Mountain Lake Beauty Peak Action #344 --- Middle Mountain (7,858)

---

--- --- 5

---

--- Lincoln County CO 10,000 One fire name only NA NA Canyons UT 9,800 Hang Dog Hammond ---

--- ---

--- Inyo CA 6,550 Fuller Piper Fuller (6,400) Piper (150) 7 1 Frank Church ID 6,341 Parker Mountain Little Horse Little Soldier Bobtail Waterfall Big Hill Parker Mountain (301)

--- Little Soldier (303)

--- Waterfall (36)

--- 32

--- 57

--- 23

--- Grizzly OR 6,050 Grizzly Bare Logan --- Bare (35)

--- --- 16

--- El Paso County CO 6,000 One fire name only NA NA Acres Researched 2,129,934 (33% of Phase I WF EI) 259,603 (4% of Phase I WF EI)WRAP 2002 PhII EI Report_20050722.doc 34 

### 2.5.1.2 Results of Complex Fire Identification Analyses

• The potential duplicate fires were identified by (1) the same name as reported in the individual daily fire reports, (2) overla pping fire date, and, (3) similarity of geographical coordinates. Based on these similarities, all potential duplicate fires recorded in Table 13 were removed from the emission inventory. The data for these deleted records will be retained in a companion database. 

### 2.5.2 Blackened Versus Perimeter Fire Acres Based on the fire event-specific information obtained for the larges t 28 wildfires in the Phase I EI, the percentage of the acreage within the fire perimeter that did not burn was extracted. A range of 4 to 54 percent of the acreage within the anal yzed fire perimeters reportedly did not burn. Table 14 presents a summary of the results of the blackened area analysis. 4 A grand total of approximately 343,000 acres of wildfire activity were removed from the fire activity database (a reduction of 5 percent of the total wildfire acres burned in the Phase I EI). Blackened acres could not be calculated for the Alaska fires since burn severity data were not collected for these fire events (personal communication, Sue Christensen, Alaska Fire Service). In this case it was assumed that the blackened acres and the perimeter acreage were the same for the large Alaska fire events. This is a reasonable assumption, given that most of these fires occurred in the interior of Alaska, and generally were characterized as intense, stand replacing wildfires (personal communication, Sue Christensen, Alaska Fire Service).
As a follow-up to these blackened acres refinement s, selected fires were analyzed to detect any trends in this data based on NFDRS fuel model. Th e goal of this analysis was to see if there was a relationship between the proportion of blac kened acres and the NFDRS fuel model, which potentially could be used to estimate blackened ac res for smaller fires in the Phase II EI, as well as for fires in future emission inventories. Th e data were summarized as the proportions of unburned acreage and blackened acres (low, modera te, and high fire severity combined) for six fires and fire complexes (Table 13). Fire severity data were available in the form of GIS layers (Ponil and Sanford) or (hardcopy) reported fire in tensities by vegetation type or NFDRS (Biscuit, Kraft, McNally, Rodeo-Chediski). The results indicated that the blackened acres within a perimeter varied considerably between NFDRS fuel models (average blackened acres 25 to almost 100 percent of perimeter). Moreover, blackened acres within a perimeter varied considerably within NFDRS fuel models as well, as indicated by the fairly high standard deviation in some cases (Table 13).

4 Air Sciences Inc. has discovered that blackened versus fire perimeter info rmation may also be available for two additional wildfire events (the Tool Box [120,000 acres] and Tiller Complex [68,775 acres] fires). To date, this information (in GIS format) has not been analyzed, and any potential reduction in acres burned for these events has not been accounted for in the Phase II EI.WRAP 2002 PhII EI Report_20050722.doc 35 Table 14: Summary of Blackened Versus Perimeter Fire Acres for Large Wildfire Events “SD” stands for standard deviation.

Fire Name State Perimeter Acres Unburned Acres (%) Blacked Acres Reduction of Acres in EI Biscuit OR 499,570 23 384,669 114,901 Rodeo/Chediski AZ 468,638 15 398,342 70,296 McNalley CA 150,696 10 135,626 15,070 Hayman CO 137,760 20 110,208 27,552 Rattle UT 94,519 54 43,479 51,040 Ponil Complex NM 92,194 16 77,443 14,751 Kraft Springs MT 69,900 4 67,104 2,796 Missionary Ridge CO 66,534 20 53,227 13,307 Sanford UT 64,972 50 32,486 32,486 **Overall Acres 1,644,783**  24 ± 17 (SD) **1,302,584 342,199 % WF EI Acres**  **26% 21%**  **5%**

A further refinement could consist of expressi ng the blacked acreage as their proportion distributed over three fire severity categories ty pically used in BAER reporting, low, moderate and high fire severity, respectively. For the six fi res in this analysis the distribution of blackened acres over the three fire severity classes did va ry considerably, both between NFDRS fuel models as well as within each NFDRS fuel model (Table 14). The latter is demonstrated by the high standard deviation in comparison with the mean pe rcentages. This variation makes it difficult to generalize this categorization to other fires in the WRAP region.
Table 15: Summary of Unburned Ve rsus Blackened Acr es for Six Fires “SD” indicates one standard deviation, and “---“ means not calculated due to a sample size of one. “*” indicates a statistically significant difference between unburned and blackened acres (Kruskal-Wallis test; P<0.05).

NFDRS Sample Size Percent of Perimeter Unburned Percent of Perimeter Blackened SD A 3 7 93 6 B 2 3 97 4 C* 5 23 77 20 F* 4 26 74 27 G 1 75 25 --- H 5 29 71 26 L 1 0 100 --- R 3 34 66 53 T 1 60 40 --- U* 4 4 96 3 **Overall* 29 23 77 27**WRAP 2002 PhII EI Report_20050722.doc 36 

### 2.5.2.1 Results of Blackened Vers us Perimeter Refinement Analyses Accounting for the unburned sections within fire perimeters decreased fire acreage between 4 to over 50 percent for a subset of large fires. Ad justments for blackened acres for these large fires were implemented in the Phase II EI. The proportion of blackened acres relative to the perimeter acres did vary considerably, was based on a very small number of fires, and did not represent all NFDRS fuel models present in the Phase I EI. Therefore, these proportions were not applied to adjust acreage of other fires in the Phase II EI. The variation in fire severity by NFDRS fuel mode l was too high to derive a general approach to adjust other fires in the Phase II EI.

Table 16: Relative Distribution of Bl ackened Acres by Fire Severity Category “SD” indicates one standard deviation, and “---“ means not calculated due to a sample size of

one. Severity Class (Percent of Blackened Acres ± SD)

NFDRS Sample Size Low Moderate High A 3 21 ± 18 36 ± 31 43 ± 49 B 2 26 ± 29 31 ± 14 43 ± 43 C 5 25 ± 22 31 ± 29 44 ± 31 F 4 36 ± 27 34 ± 25 30 ± 19 G 1 15 ± --- 74 ± --- 11 ± --- H 5 33 ± 24 38 ± 21 29 ± 16 L 1 2 ± --- 17 ± --- 81 ± --- R 3 14 ± 25 18 ± 15 68 ± 36 T 1 14 ± --- 68 ± --- 18 ± --- U 4 27 ± 18 36 ± 12 37 ± 28 **ALL 29 25 ± 21 35 ± 22 40 ± 29**



### 2.5.3 Spatial, Temporal, and Fuel Model Refinements 2.5.3.1 Spatial Refinements Based on the information gathered on the large fire events, as summarized in Table 16, several refinements were applied. A spatial check was pe rformed for the largest fires and fire complexes for which digital, GIS-based, fire perimeters were av ailable. The fire locations of these fires in the Phase I EI (Table 16) were plotted on the same map as the GIS-based final fire perimeters and checked for accuracy. The Phase I EI fire location s were consistent with the GIS perimeters for all events, and no changes in the location da ta for these files were implemented.WRAP 2002 PhII EI Report_20050722.doc 37 

### 2.5.3.2 Temporal Refinements The data gathered in the form of reports genera lly only provided the total (perimeter) acreage and the start and end date for each fire, while the GIS data only provided the final fire perimeters. Generally, the data already present in Phase I EI had a higher temporal resolution than either the reports or the GIS data. Thus, no temporal adjustments were made to the data.



### 2.5.3.3 Fuel Model Refinements For a selection of the larger fires in the lower 48 states, the GIS-based final fire perimeters were used to extract the distribution of fuel models within the final perimeters. The fuel consumption was then recalculated based on the blackened ac res, thereby taking into account the unburned portion within the fire perimeter. The fire pe rimeters were intersected with two fuel model maps, the NFDRS fuel model layer (using the WRAP’s NFDRS fuel loading table) and a more detailed fuel characteristics class (FCC) layer (personal communication, Donald McKenzie, USFS, 6/25/04).
The comparison results presented in Table 17 indi cate that adjusting the total consumption using a more refined GIS-based methodology can produc e mixed results (resulting consumption can be either higher or lower than the consumption in the Phase I EI). Generally, the more spatially resolved fuel consumption technology yielded lowe r total consumption than the method used for the Phase I EI. An exception was fires with fuel model C (open ponderosa pine), coinciding with a fairly low fuel model loading in the Phase I EI. The higher spatial resolution method increased consumption for these fires by in corporating acreage with higher fuel loadings within the fire perimeter.
A separate, new (draft) default set of consumption percentages was developed for the FCC categories. Note that the FCC estimates did not include the consumption of duff, since the duff variable in the FCC data set was provided in terms of thickness (inches) rather than loading (tons per acre). Also, it was not clear from the FCC da ta if the crown mass was included in the loading, and if so, how to account for the specific cr own consumptions as was done for the WRAP’s NFDRS fuel consumption tables. The FCC analysis also produced mixed results. In all cases analyzed, the direction of fuel consumption ch anges was identical to the more refined NFDRS method. In general, the FCC analysis indicated slightly higher decreases in fuel consumption than the NFDRS method and considerably lower increases. Both fuel consumption refinement techniques that were analyzed (refined spatial NFDRS and FCC data) produced consistent results (i.e., both methods indicate a fuel consumption de crease for the same fires.) The decision was made to implement the final consumption refineme nt based on NFDRS data layer in the interest of maintaining the technical consistency of the Phase II EI system.WRAP 2002 PhII EI Report_20050722.doc 38 Table 17: Sensitivity of Estimated Fuel Consumption to Adjustment for Blackened Acres in Combination With Fuel Loading Based on GIS-Derived NFDRS and FCC Fuel Layers Fuel consumption was based on default (WRAP) co nsumption percentages by fuel size class and held constant for each fire severity class.
Phase I Total Fuel Consumption (10 6 tons) Delta Consumption (%) Fire Name NFDRS Phase I EI NFDRS FCC NFDRS FCC Biscuit G 21.73 11.07 7.68 -49 -65 Hayman C 0.65 2.23 1.34 +244 +107 McNalley B 2.94 2.67 0.72 -9 -75 Sanford K 0.93 0.41 0.51 -56 -45 Ponil Complex H 2.54 0.45 0.17 -82 -93 Missionary Ridge C 0.31 0.97 0.40 +211 +28 Rattle G 4.11 0.95 0.34 -77 -9



### 2.5.3.4 Additional Fuel C onsumption Refinements In addition to fire perimeter information, fire severity information was available for a subset of wildfire and fire complexes (either based on report s or GIS-layers). This information was used to further refine fuel consumption estimates by defi ning variable fuel consumption percentages by fuel size class for each reported fire severity ca tegory (low, moderate, and high severity: Tables 19 and 20). Based on the FCC overlay, this a dditional refinement decreased the total fuel consumption somewhat compared to the proce ss where all burned acres received a default consumption percentage (Table 18). Based on th e NFDRS overlay this additional refinement had variable effects, varying from a decrease to an increase of the estimated consumption compared to application of default consumption percentages. However, overall the additional refinement of adding fire severity levels did not lead to st atistically different changes in consumption (Paired T-test, t 13 =0.465, P =0.650). No changes in the fuel consumption data were made based on fire severity information.WRAP 2002 PhII EI Report_20050722.doc 39 Table 18: Sensitivity of Estimated Fuel Consumption to Adjustment for Blackened Acres in Combination With Fuel Loading Based on GIS-Derived NFDRS and FCC Fuel Layers Fuel consumption was based on variable consumpt ion percentages by fuel size class and fire severity class.
Phase I Total Fuel Consumption (10 6 tons) Delta Consumption (%) Fire Name NFDRS Phase I EI NFDRS FCC NFDRS FCC Biscuit G 21.73 6.22 4.78 -71 -78 Hayman C 0.65 1.82 1.07 +181 +65 McNalley B 2.94 2.26 0.60 +23 -80 Sanford K 0.93 0.35 0.39 +62 -58 Ponil Complex H 2.54 0.29 0.09 -89 -96 Missionary Ridge C 0.31 0.82 0.39 +163 +25 Rattle G 4.11 0.82 0.26 -80 -94



### 2.5.3.5 Results of Spatial, Tempora l, and Fuel Model Refinements Analyses

• The data available did not allow for spatial improvement over the temporal course of the fire, nor for data quality improvements of daily acres. The spatial accuracy of the Phase II EI data was checked for those wild fires for which GIS-based fire perimeters were available.

• Refinement of fuel model information for the large fires was performed for those fires with available GIS-based fire perimeters (Tab le 18) by overlaying the perimeters with the NFDRS fuel model layer. This is co nsistent with the use of NFDRS for fuel loadings generally in the 2002 emission inventory.

• Refinement of fuel model adjustments by distinguishing different fuel consumption levels by fire severity category was not implemented.WRAP 2002 PhII EI Report_20050722.doc 40 Table 19: Summary of Fuel Consumption Percenta ges Applied to Model Variable Consumption by Fire Severity Class, NFDRS Fuel Models Default percentages applied in Phase I EI.

Fuel Size Class Default Consumption Low Fire Severity Moderate Fire Severity High Fire Severity 1-hour 100% 100% 100% 100% 10-hour 100% 100% 100% 75% 100-hour 100% 100% 75% 25% 1,000-hour 100% 100% 50% 0% Wood 100% 100% 100% 50% Herb 100% 100% 100% 100% Duff 50% 100% 50% 0% Crown 62% 100% 40% 0%

Table 20: Summary of Fuel Consumption Percenta ges Applied to Variable Consumption by Fire Severity Class, FCC Fuel Models Default percentages serve as temporary placeholder.

Fuel Size Class Default Consumption Low Fire Severity Moderate Fire Severity High Fire Severity 1-hour 100% 100% 100% 100% 10-hour 100% 75% 100% 100% 100-hour 100% 25% 75% 100% 1,000-hour 100% 0% 50% 100% 10,000-hour 50% 0% 25% 100% >10,000-hour 25% 0% 10% 100% Grass 100% 100% 100% 100% Shrub 100% 50% 100% 100% Duff * 0% 0% 0% 0%
* Duff consumption was set to zero for all fire categor ies, since data were provided in terms duff depth and not in actual loading.WRAP 2002 PhII EI Report_20050722.doc 41 

### 2.5.4 Overall Assessment of Refinements Table 21 summarizes the potential changes to the data that have resulted from incorporating the refinements discussed in this section. The number of fire events, number of fire days, fire acres, and fuel consumption are shown in Table 21. The number of fire events and the number of fire days only changed based on the duplicate fire chec king in the fire complexes. While the change in numbers of fire events and fire days was rela tively small, the duplicate checking decreased the fire acres and the fuel consumption by 4 to 5 percent from the Phase I EI. An additional reduction in fire acres and fuel consumption was achieved by adjusting the acreage for the largest fire events from perimeter acres to blackened acre s. The combined removal of the duplicate fire entries and the blackened acreage adjustment reduced the fuel consumption by almost 10 percent. An additional 3 to 9 percent redu ction was achieved based on the fuel model refinements of those large fires for which GIS-based perimeter data were available.
Table 21: Summary of Estimated Adjustments to the Phase II EI (Wildfire and Wildland Fire Use) Based on Described Quality Control and Data Refinement Procedures The percentages in parentheses refer to the change as a percent of the Phase I EI.

Adjusted records by Refinement Step # of Fire Events # of Fire Days Fire Acres Fuel Consumption (10 6 tons) Phase I EI 1 1,899 3,243 6,366,532 178.1 Fire complex duplicates 26 (-1.4%) 74 (-2.2%) 259,603 (-4.1%) 8.1 (-4.5%)

Blackened acres As above As above 342,199 (-5.4%) 8.9 (-5.0%) NFDRS, default consumption 2 As above As above As above 15.2 (-8.5%) FCC, default consumption 2 As above As above As above 21.2 (-12.0%) NFDRS, severity class specific consumption 2 As above As above As above 19.9 (-11.2%) FCC, severity class specific consumption 2 As above As above As above 23.9 (-13.4%) **Overall Adjustments 26**  **(-1.4%) 74**  **(-2.2%) 601,802**  **(-9.5%) 23.3 to 32.0**  **(-13.0% to -18.0%)**

1 References values were based on data before incomplete records were dropped from EI, and did not include

smoldering. Hence, the data are somewhat di fferent from those in the final Phase II EI.
2 These adjustments and percentages did include the corre ction for blackened acres as well as the fuel models.WRAP 2002 PhII EI Report_20050722.doc 42 

## 2.6 Wildland Fire Quality Control Process After implementing the technical refinements desc ribed in Section 2.5, a quality control (QC) process was implemented to allow for review of wild fire and prescribed fire data by state, tribal, and federal agencies. The intent of the QC proc ess was to present wildland fire data to those presumed to be “closest” to the fire activity data, obtain a critical review of the activity data, and incorporate any recommended changes to the data. Through this process, the FEJF sought to increase the accuracy of the Phase II EI and to increase the confidence of the WRAP, States, Tribes, and Federal Land Managers (FLMs) in the use of the Phase II EI in regional haze modeling. 

### 2.6.1 QC Binder Summary Hardcopy binders were mailed to representative s of states, Tribes, and FLMs in the WRAPRegion to quality control the Phase II EI activity data. These binders featured wildfire and/or prescribed burning summaries and fire event leve l data specific to the jurisdiction of the recipient. The binders included tables and charts summarizing activity data, feedback forms to recommend changes to the fire events in the in ventory, and a documentation section including a previous version of this report. The binders also included instructions on how to download the entire emission inventory database to pe rform a more thorough QC if desired.

The binders sent to states and Tribes included wildfire, prescribed, and WFU burning activity data. GACC FLMs received data for wildfire an d WFU only, while all other FLMs received only prescribed fire and WFU data. Table 22 summarize s the binders sent and the responses received.
Table 22: Summary of Wildland Fire QC Binders Sent and QC Feedback Received

Agency % Response QC Binders Sent Out QC Feedback Received No Change New Data BLM 55 12 7 3 4 FWS 50 5 2 1 1 GACC 33 9 3 1 2 NPS 0 5 0 0 0 USFS 33 6 2 1 1 States 75 16 12 7 5 Tribes 0 5 0 0 0



### 2.6.2 Feedback Response Summary The overall response rate for FLMs was 37 percen t and for states was 75 percent. Table 23 shows the breakdown of responses by agency. Of the 26 QC responses received, 13 confirmed that the data was representative of actual burning activity and did not recommend any changes. Thirteen reviewers submitted new or revised data for the 2002 Emission Inventory. Overall, the QCWRAP 2002 PhII EI Report_20050722.doc 43 process resulted in a documented review by stat es of 92 percent of all Phase II EI acres and 24 percent by FLMs of all Phase II EI acres.
A summary of changes to the burning activity data due to QC responses are also presented in Table 23. Types of changes included adding ev ents, removal of events, and revision of event acres, fuel loading and/or revised location data.
The most significant QC changes to the data were from the submission of new data sets. Arizona and Wyoming submitted new data for prescribed fire for 2002. This new data replaced the existing prescribed fire data for those states . Another major new data set was a WRAP-wide prescribed fire database for BLM prescribed and WFU fires. Comparing this data with existing BLM fire data showed some similarities and some differences. In cases that a BLM regional office did not provide a response to a QC packet, da ta from the BLM’s WRAP-wide prescribed fire database was used.
Air Sciences Inc. implemented internal QC ch ecks when incorporating new data into the database. Reported new fires were checked against existing data to see if they were already in the database. Some of the existing fire events were updated with new information, while others were removed and replaced with new data.WRAP 2002 PhII EI Report_20050722.doc44Table 23: Detail of Wildland Fire QC Binder Feedback ReceivedWRAP 2002 PhII EI Report_20050722.doc45Table 23: Detail of Wildland Fire QC Binder Feedback Received – continuedWRAP 2002 PhII EI Report_20050722.doc 46 SECTION 3 

# THE 2002 AGRICULTURAL BURNING EMISSION INVENTORY

For the Phase II EI, an agricultural burning emission inventory representative of 2002 was created for the 13-states in the WRAP region (Hawaii is not included in the agricultural burning EI). 

## 3.1 Agricultural Burning Activity Data 3.1.1 Data Sources The agricultural burning activity data source for each state fell into two general categories:

• Raw activity data collected under this contract by soliciting state agencies.

• Activity data carried over from the WRAP 2018 Base Smoke Management Scenario emission inventory created for the 2018 projections.
All states supplied 2002 activity data under this co ntract except for Alaska, Arizona, Nevada, and North Dakota. Idaho submitted new activity data for ten counties and requested that 2018 Base Smoke Management Scenario figures be carri ed over for the remainder of the state.
For a complete description of the WRAP 2018 Base Smoke Management Scenario emission inventory, please see:

• The report entitled Non-Burning Management Alternatives on Agricultural Lands in the Western United States (Eastern Research Group, Inc. and Enviro-Tech Communications, 2002), prepared for the Fire Emissions Joint Forum of the WRAP. The report emission included an inventory of agricultural burn ing activity data for the 13 states in the modeling domain.

• The report entitled Integrated Assessment Update and 2018 Emissions Inventory for Prescribed Fire, Wildfire, and Agricultural Burning (Air Sciences Inc., Draft 2002), prepared for the Fire Emissions Joint Forum of the WRAP. This report describes the preparation of the model-ready emissi on inventory and creation of smoke management scenarios. 

### 3.1.2 Agricultural Burning on Tribal Lands No agricultural burning activity data was available from tribal governments. The agricultural burning activity database does not necessarily include quantification of burning on tribal lands, although data collected from states may include burn ing in Indian Country. In this section of the document, the term “state” refers to the entire geographic area within the exterior boundary of a
state.WRAP 2002 PhII EI Report_20050722.doc 47 When surveyed by ERG, nearly 60 percent of the Tribes that conducted prescribed burning reported the existence of agricultural burning. However, the data provided in the survey responses were not of sufficient detail to quantify burning activities. For a more complete description of the findings of the ERG data gathering efforts with regard to burning on tribal lands, please see the report entitled Non-Burning Management Alternatives on Agricultural Lands in the Western United States (Eastern Research Group, Inc. and Enviro-Tech Communications, 2002). 

### 3.1.3 Time Periods of the Actual Agricultural Burning Data Agricultural burning activity data in the databa se included data for 1996 through 2003. Priority was given to 2002 data because that is the year of the crop production data and the WRAP emission inventory base year. However, in order to provide data for as large a geographic area as possible, it was necessary to use other years if 2002 data did not exist or were known to be largely incomplete compared to later years. Importantly, each of the state-specific 13 data sets included in the database are believed to represent a single calendar year of agricultural burning data. Therefore, when combined, the data sets should represent a single year of agricultural burning activity. 

### 3.1.4 Data Quality Requirements Minimum data quality requirements were established for activity data to be eligible for use in the emission inventory. Specifically, to be eligible, a record had to have a valid date field (either a specific date [daily] or a specific month), a va lid state name, a valid county name, and a valid value in the residue-loading field. A record with either missing or invalid data in any of these fields was flagged as invalid and not used in the emission inventory. 

## 3.2 Fuel Loading and Emission Factors for Agricultural Burning Fuel loading and emission factors were provided by the FEJF and its Alternatives to Agricultural Burning Task Team. Fuel loading and emission factors are presented in Table 24 and originate from data peer-reviewed by the ETT. Severa l crops identified in the Phase II agricultural burning activity were not included in the fuel lo ading and emission factors provided by the FEJF (indicated with an asterisk in Table 24). In th ese instances, fuel load ing and emission factors were assigned from comparable crops.
The pollutant-specific emission factors (in pounds of pollutant per ton of residue burned) are multiplied by the residue loading values (tons residue burned) in the agricultural burning activity database to calculate emissions.WRAP 2002 PhII EI Report_20050722.doc 48 Table 24: Agricultural Burning

**Emission Factors by Pollutant (lbs pollutant/ton residue)**

**Crop Type Residue**  **Loading (ton/acre)**  **PM PM10 PM2.5 EC OC VOC CH4 NH3 NOx CO SO2 PMC** almonds 1 8.72 8.60 8.20 2.15 3.70 8.90 2.34 1.28 7.24 63.86 0.12 0.40 apples 2.3 8.55 8.39 7.96 2.10 3.61 4.95 3.73 1.81 11.18 90.32 0.22 0.43 apricots 1.8 9.07 8.90 8.45 2.22 3.83 6.94 5.24 1.48 7.84 73.91 0.15 0.45 asparagus 1.5 32.94 32.40 30.90 8.10 13.93 14.99 11.32 2.72 5.02 135.88 0.67 1.50 avocado 1.5 29.69 29.14 27.44 7.28 12.53 26.17 19.76 3.28 7.36 164.07 0.14 1.70 barley 1.7 15.52 15.36 14.86 2.46 6.14 23.34 4.94 3.95 5.44 197.34 0.08 0.50 beans; all dry edible 2.5 15.72 15.46 14.67 3.87 6.65 16.03 12.10 3.34 5.87 167.04 0.11 0.79 blueberries 1.7 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 bushberry 1.7 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 canola 1.3 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 cherries 1 12.62 12.38 11.60 3.10 5.32 9.40 7.10 1.38 8.15 68.97 0.16 0.78 citrus 1 8.50 8.35 7.92 2.09 3.59 9.62 7.26 2.29 7.36 114.57 0.14 0.42 coffee 1 11.16 10.96 10.25 2.74 4.71 8.85 6.68 1.85 7.30 92.70 0.14 0.70 corn; for grain* 4.2 12.62 12.42 11.96 1.86 4.35 9.12 3.50 1.55 3.64 77.56 0.40 0.46 corn; for silage 0 12.62 12.42 11.96 1.86 4.35 9.12 3.50 1.55 3.64 77.56 0.40 0.46 cotton; amer. pima 1 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 cotton; upland 1 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 CRP 2.6 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 dates 1.7 11.52 11.30 10.73 2.83 4.86 4.38 3.31 1.29 6.00 64.59 0.12 0.58 ditches and ditch banks 3.2 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 ditches and fenceline 1.6 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 figs 0.75 10.06 9.87 9.30 2.47 4.24 8.58 6.48 1.63 7.44 81.55 0.14 0.57 filberts* 1.7 11.16 10.96 10.25 2.74 4.71 8.85 6.68 1.85 7.30 92.70 0.14 0.70 flaxseed* 1.7 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 fruits and vegetables; other 2 11.16 10.96 10.25 2.74 4.71 8.85 6.68 1.85 7.30 92.70 0.14 0.70 grapes 1.47 7.29 7.15 6.72 1.79 3.08 5.55 4.19 1.49 7.59 74.45 0.15 0.44 hay; alfalfa 2.5 32.34 31.81 30.36 7.95 13.68 24.22 18.29 2.66 5.02 132.81 0.67 1.45 hay; all 0.8 32.34 31.81 30.36 7.95 13.68 24.22 18.29 2.66 5.02 132.81 0.67 1.45 hay; all other 0.8 32.34 31.81 30.36 7.95 13.68 24.22 18.29 2.66 5.02 132.81 0.67 1.45 hops 0.8 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 kiwi 1.9 11.16 10.96 10.25 2.74 4.71 8.85 6.68 1.85 7.30 92.70 0.14 0.70 lentils 1.7 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 macadamia nuts 2.5 11.16 10.96 10.25 2.74 4.71 8.85 6.68 1.85 7.30 92.70 0.14 0.70 mint 1.7 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 nectarines 0.5 5.84 5.74 5.44 1.43 2.47 3.38 2.55 0.97 7.65 48.53 0.15 0.29 oats 1.7 23.28 22.90 21.79 5.72 9.85 11.39 8.60 3.01 4.98 150.44 0.66 1.11 olives 1.6 18.08 17.74 16.69 4.44 7.63 15.49 11.69 3.43 7.82 171.43 0.15 1.05 onion seeds 1.7 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 orchard pruning; unspecified 1.7 11.16 10.96 10.25 2.74 4.71 8.85 6.68 1.85 7.30 92.70 0.14 0.70 orchard removal 15 11.16 10.96 10.25 2.74 4.71 8.85 6.68 1.85 7.30 92.70 0.14 0.70 peaches 2.5 7.13 7.00 6.64 1.75 3.01 3.56 2.69 1.00 6.17 49.82 0.12 0.36 peanuts 1.2 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 pears 2.6 13.65 13.39 12.63 3.35 5.76 7.76 5.86 1.74 7.91 86.76 0.15 0.76 peas; dry edible 2.5 15.72 15.46 14.67 3.87 6.65 16.03 12.10 3.34 5.87 167.04 0.11 0.79 pecans 1.7 11.16 10.96 10.25 2.74 4.71 8.85 6.68 1.85 7.30 92.70 0.14 0.70 persimmons 1.7 11.16 10.96 10.25 2.74 4.71 8.85 6.68 1.85 7.30 92.70 0.14 0.70 pistachio 1.7 11.16 10.96 10.25 2.74 4.71 8.85 6.68 1.85 7.30 92.70 0.14 0.70 plums and prunes 1.2 3.96 3.88 3.75 0.97 1.67 6.16 4.65 1.26 6.96 62.92 0.13 0.13 pomegranates* 1.7 11.16 10.96 10.25 2.74 4.71 8.85 6.68 1.85 7.30 92.70 0.14 0.70 potatoes 1.2 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 proso millet 1.9 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 quinces* 1.7 11.16 10.96 10.25 2.74 4.71 8.85 6.68 1.85 7.30 92.70 0.14 0.70 rice; all 3 6.98 6.92 6.44 1.25 1.38 6.74 1.44 1.26 5.68 62.78 1.24 0.48 rye 1.9 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 safflower 1.3 20.95 20.61 19.67 5.15 8.86 17.23 13.01 3.35 5.24 167.64 0.70 0.93 seeds; alfalfa* 0.8 32.34 31.81 30.36 7.95 13.68 24.22 18.29 2.66 5.02 132.81 0.67 1.45 seeds; KBG 2 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 seeds; other 2 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 seeds; unspecified* 2 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 sorghum* 2.9 21.74 21.38 20.41 5.34 9.19 6.16 4.65 1.86 5.43 93.00 0.72 0.97 soybeans* 1 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 sudan* 2 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 sugarbeets* 1 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 sugarcane 14 11.22 10.86 9.98 1.63 4.02 3.68 0.82 1.02 2.80 50.96 1.24 0.88 sunflower 1 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 various weeds and ditch banks* 1 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 walnuts* 1.2 6.44 6.30 5.92 1.83 2.96 9.30 3.28 2.00 6.78 100.08 0.28 0.38 wheat; all 1.9 11.64 11.48 10.88 1.61 4.36 10.84 3.64 2.67 4.66 133.38 0.94 0.60 wheat; durum 1.9 11.64 11.48 10.88 1.61 4.36 10.84 3.64 2.67 4.66 133.38 0.94 0.60 wheat; other spring 1.9 11.64 11.48 10.88 1.61 4.36 10.84 3.64 2.67 4.66 133.38 0.94 0.60 wheat; other spring (irrigated) 4 11.64 11.48 10.88 1.61 4.36 10.84 3.64 2.67 4.66 133.38 0.94 0.60 wheat; unspecified* 1.9 11.64 11.48 10.88 1.61 4.36 10.84 3.64 2.67 4.66 133.38 0.94 0.60 wheat; winter all* 1.9 11.64 11.48 10.88 1.61 4.36 10.84 3.64 2.67 4.66 133.38 0.94 0.60 unspecified -- 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 CARB average field crop 2.6 9.01 8.86 8.47 2.22 3.81 5.96 4.50 1.27 2.51 63.55 0.33 0.39 other ag burning* 2.6 9.01 8.86 8.47 2.22 3.81 5.96 4.50 1.27 2.51 63.55 0.33 0.39 CO average field crop* 4.2 12.62 12.42 11.96 1.86 4.35 9.12 3.50 1.55 3.64 77.56 0.40 0.46 Idaho Crop N/A* 2 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78 berries; other* 1.3 20.95 20.61 19.67 5.15 8.86 17.23 13.01 3.35 5.24 167.64 0.70 0.93
*These crops do not have unique emission factors but are associated with emission factors for other crops.WRAP 2002 PhII EI Report_20050722.doc 49 

## 3.3 Temporal Refinement of Agricultural Emissions Data Approximately 1,300 records in the agricultural database were temporally resolved to the month (i.e., total residue of a specific crop burned in a county in a month). The WRAP modeling requires that emissions data be temporally resolv ed to the day. The following techniques were employed to break the monthly data into daily data.
First, by the emission calculation methods desc ribed above, monthly emissions were calculated (i.e., tons of a specific pollutant due to the burnin g of a specific crop in a specific county in a specific month). Then, monthly emissions were broken into daily emissions in discrete “packets.” The PM 2.5 packet size ranges from the plume characteristic table derived for the prescribed fire emission inventory were used here to assign a plume class number to each of the daily records in the agricultural emissions database. The PM 2.5 packet ranges are shown in Table 25.

Table 25: Plume Class Sizes

Plume Class Low End of Range (tons PM 2.5 ) High End of Range (tons PM 2.5 ) 1 0 1 2 >1 10 3 >10 100 4 >100 500 5 >500 NA

Each daily agricultural fire event is assigned a plume category (1 through 5). The probability of occurrences for the plume classes for the daily agri cultural fires in the database was taken from the report entitled Integrated Assessment Update and 2018 Emi ssions Inventory for Prescribed Fire, Wildfire, and Agricultural Burning and were originally calibrated on daily data collected for that project. These probabilities were used to brea k the monthly agricultural burning emissions for each county into representative daily fire size packets. The statistics (number of events and probability of occurrence) for the final emissi on inventory are also shown in Table 26.
Table 26: Distributions of Daily Events by Plume Class

Plume Class Events in 2018 Daily Data Probability of Occurrence in 2018 Daily Data Packet Fire Size (tons PM 2.5 ) Events in Phase II EI Probability of Occurrence in

Phase II EI 1 47,056 0.975 0.064 99,485 .939 2 1,158 0.024 2.202 5,886 .056 3 35 0.0007 16.641 620 .006 4 0 0.0 NA 0 0.0 5 0 0.0 NA 0 0.0 Total 48,249 105,991WRAP 2002 PhII EI Report_20050722.doc 50 

### 3.3.1 Blackout Dates Each daily event is assigned to a specific day of the month. Blackout days on which daily packets would not be assigned were taken from the Integrated Assessment report. Under that contract, the daily agricultural activity data was analyzed to determine if patterns of temporal distribution within months exist. The daily frequencies of events appeared to be uniformly distributed throughout the month except for obvious “no-burn ” periods, primarily occurring before and/or on and/or after holiday periods and perhaps during brief periods of harvesting in late August. The daily events were randomly assigned to any day of the month that was not a “blackout” date, as identified in Table 27.
Table 27: Blackout Days for Agricultural Burning

Month Days(s) Holiday January 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 New Year’s Day July 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 Fourth of July August 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 Harvesting period November 29 Thanksgiving December 19, 20, 21, 22, 23, 24, 25, 26 Christmas
Upon the conclusion of the temporal allocation of the monthly emissions, the emission inventory included approximately 92,500 daily event records directly from the agricultural database and approximately 14,000 daily event records derived from the approximately 1,300 monthly activity records for a total of approximately 106,500 events in the inventory. Each produced daily fire event was entered in the emission inventory al ong with its emissions and associated plume characteristics. 

## 3.4 Spatial Refinement of Agricultural Emissions Data As described above, the emission inventory incl uded actual daily agricultural burning events from the database and realistically-sized daily burning events created from monthly records in the activity database. All daily events in the activity database were resolved to the county level. To spatially allocate the daily events that did no t have a source-supplied coordinate (including all the daily allocated events) to a 1-km resolution , the events were each assigned a coordinate location within the identified county on a stratified random basis.
The location of each agricultural burning even t in the inventory was expressed by state and county identifiers (state/county name and state/county FIP code). Each fire was allocated according to its state and county identifiers in sp ace. A map of counties was obtained from the National Atlas, and a LCC map showing agricultural cover types was used. Overlaying the two maps yielded a map of agricultural cover by coun ty. The eligible pixels (agricultural cover) within each county could be looked up on this overlap map. The overlap map was recorded at a 1-km resolution. The individual fire events reta ined the state and county identifiers from their source database entry. For each fire event, the eligible 1-km cells were selected based on state/county identifier and agricultural cover type. In the event the LCC map did not indicateWRAP 2002 PhII EI Report_20050722.doc 51 agricultural cover types occurring in the county, vegetated 1-km pixels in the county were selected. With the eligible 1-km cells selected, a single 1-km cell was then chosen at random. The coordinates of the 1-km grid cell were read and the latitude and longitude recorded to the fire event. In this fashion, every event in the daily agricultural burning emission inventory lacking a source-supplied location was given a coordinate. 

## 3.5 Assigning Plume Characteristics to Agricultural Burning Events The plume profile categories and calculations us ed for wildland fire (described above) were applied to agricultural burning events. The method to assign plume characteristics to agricultural burning events is very similar to th e method for wildland fire (see Section 2.4). A diurnal consumption template was cust omized for agricultural burning. 

### 3.5.1 Diurnal Consumption Template For the agricultural burning emission inventory, like the 2018 prescribed fire emission inventory, the plume characteristics are based on fire size as a function of PM 2.5 emissions.
The WRAP Emissions and Modeling Forums reques ted hourly values of fire emissions and plume characteristics. To satisfy this temporal requirement, daily emission s for each agricultural burning event in the inventory were broken into hourly emissions using the agricultural burning diurnal consumption template (based on expert opinion) presented in Table 28.
Table 28: Diurnal Consumption Template Used to Distribute Emissions From Agricultural Burning (Percent Of Fuel Consumed Each Hour)

Hour % Per Hour Hour % Per Hour 1 0.43 13 14.00 2 0.43 14 17.00 3 0.43 15 14.00 4 0.43 16 12.00 5 0.43 17 9.00 6 0.43 18 6.00 7 0.43 19 3.00 8 0.43 20 0.43 9 0.43 21 0.43 10 3.00 22 0.43 11 6.00 23 0.43 12 10.00 24 0.43
This diurnal consumption template varied from the template used for wildfire and prescribed fire in one important way: the daily emissions peak wa s moved to earlier in the day, largely due to the more consistent ignition times for agricultur al fires (personal communication, Bryan Jenkins, UC Davis). The diurnal profiles for agricultural burning and wildfire/prescribed fire are shown graphically in Figure 10.WRAP 2002 PhII EI Report_20050722.doc 52 Figure 10: Diurnal Emissi ons/Consumption Profiles for Agricultural Burning and Wildfire/Prescribed Fire



### 3.5.2 Physical Plume Characteristics Plume characteristics were assigned to each daily event using the same method employed for the wildland fire emission inventory. Table 29 presen ts the plume characteristics (buoyant efficiency [BE], height of the bottom of the plume [Pbot], and height of the top of the plume [Ptop]) to be assigned to each daily event according to the plum e class of each event. Note, because there were no Class 4 or Class 5 agricultural burning events , the plume characteristics for these fire classes were not included in Table 29.

Table 29: Fire-Related Parameters as a Function of Fire Emission Classes

Class 1 2 3 Emissions (tons PM 2.5 ) 0 – 1 >= 1 – 10 >= 10 – 100
BE size 0.40 0.60 0.75 Ptop max (m) 160 2,400 6,400 Pbot min (m) 0 900 2,200 Diurnal Emissions/Consumption Profiles - Fire Sources

0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14% 15% 16% 17% 18%

Hour% Emitted/Consumed per Hour

Ag Fire WF and Rx Ag Fire 0.43% 0.43% 0.43% 0.43% 0.43% 0.43% 0.43% 0.43% 0.43% 3.00% 6.00% 10.00% 14.00% 17.00% 14.00% 12.00% 9.00% 6.00% 3.00% 0.43% 0.43% 0.43% 0.43% 0.43%

WF and Rx 0.57% 0.57% 0.57% 0.57% 0.57% 0.57% 0.57% 0.57% 0.57% 2.00% 4.00% 7.00% 10.00% 13.00% 16.00% 17.00% 12.00% 7.00% 4.00% 0.57% 0.57% 0.57% 0.57% 0.57% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24WRAP 2002 PhII EI Report_20050722.doc 53 

## 3.6 Agricultural Burning Quality Control Process 3.6.1 QC Binder Summary States and Tribes were given the opportunity to review and comment on agricultural burning activity data in the Phase II EI that was within their state or tribal lands. Binders were prepared that summarized data for each state and Tribe, and a CD was included that contained the entire agricultural burning database. An introductory letter was sent with the binders to explain the purpose for the QC review as well as to give instruction on how to conduct the review and submit a response. 

### 3.6.2 QC Response Summary
Binders were sent to 16 state reviewers and 3 tribal reviewers, as shown in Table 30. Some states received more than one binder. There was no burning data in the inventory for Nevada, so a special packet was prepared for Nevada to provid e agricultural burning activity data. Three of the states reviewed the data and responded that no changes were necessary, including Nevada, which responded that agricultural burning data was not available. Ten states submitted new or revised burning activity data. No new data was received from Tribes. Details of the responses received are given in Appendix A. Overall, th e QC process resulted in documented review of agricultural burning for every state in the WR AP. The ETT determined that there was no agricultural burning in Alaska and, therefore, Alaska was omitted from the Phase II EI.WRAP 2002 PhII EI Report_20050722.doc54Table 30: Detail of Agricultural Burning QC Binder Feedback ReceivedWRAP 2002 PhII EI Report_20050722.doc 55 SECTION 4 

# THE 2002 NON-FEDERAL PRESCRIBED RANGELAND BURNING EMISSION INVENTORY

For the Phase II EI an emission inventory of pr escribed rangeland burning on non-federal lands in the WRAP region was prepared for 2002. In this section, rangeland burning is defined as prescribed fires on non-federal lands used for livestock grazing and ranching. Rangeland burning on federal lands was assumed to appear in the wildfire and prescribed burning activity data sources and corresponding emission inventories. Event-level fire activity data for non-federal rangeland burning was not available for the entire WRAP region. This first WRAP rangeland burn ing emission inventory was designed to be complete for the WRAP region for 2002, albeit re lying on expert opinion for total burning by state. This “base layer” was designed to acco mmodate superseding levels of detailed activity information as they become available. This layering concept was proposed as an alternative to the “gap-filling” method where trends observed in av ailable specific data are used to fill the areas for which data is not available. 

## 4.1 Rangeland Burning Activity Data Rangeland burning activity data across the entire WRAP region was based on the Fire Emissions Joint Forum’s assessment led by Pat Shaver of the USDA – Natural Resources Conservation Service (NRCS). Table 31 shows the FEJF estimate of acres burned by state. Burn activity was then pro-rated to the county level using acres of rangeland present in each county per the 1997 National Resources Inventory (NRI) CD-ROM Version 1 (December 2001) produced by the NRCS.
Table 31: Non-Federal Prescribed Rangeland Burning Activity by State

State Acres Burned AZ 250,000 CA 40,000 CO 12,000 ID 8,000 MT 150,000 ND 25,000 NM 60,000 NV 1,000 OR 300,000 SD 150,000 UT 25,000 WA 6,000 WY 15,000 Total **1,042,000**WRAP 2002 PhII EI Report_20050722.doc 56 

## 4.2 Temporal Allocation of Burn Activity The temporal resolution of the rangeland burning activity for WRAP was supplied by the FEJF on an annual basis for 2002. Annual estimates of rangeland burning were allocated to the month according to FEJF instructions. The percent of activity per month used for the entire WRAP region is shown in Table 32.
Table 32: Percent Activity per Month for Non-Federal Rangeland Burning

Month %-Annual Jan 0 Feb 0 Mar 0.24 Apr 0.24 May 0.24 Jun 0.12 Jul 0 Aug 0 Sep 0.08 Oct 0.08 Nov 0 Dec 0 Total **1.00**



## 4.3 Emission Calculations Emissions per pollutant were calculated as activi ty (acres burned) multiplied by a fuel loading factor (ton/acre burned) and an emission factor (l b/ton) as shown in Equation 7. A fuel loading of 1.75 tons per acre was provided by Pat Shaver USDA – NRCS and accepted by the ETT to be representative of rangelands. The Conservation Reserve Program (CRP) suite of emission factors (derived from the California Air Resources Board’ s average of emission factors for field crops) were used to calculate emissions from rangelan d burning activity. Fuel loading and emission factors for non-federal rangeland burning are show in Table 33.
Table 33: Rangeland Fuel Loading and Emission Factors

Fuel Loading Emission Factors (Lbs Pollutant) / (Ton Biomass Consumed) Tons/Acre PM PM 10 PM 2.5 EC OC VOC CH 4 NH 3 NO x CO SO 2 PM C 1.75 18.02 17.73 16.95 4.43 7.62 11.93 9.01 2.54 5.02 127.09 0.67 0.78

lbs 2000

Tons Biomass Tons Emissions lbs Burned Acres Biomass Tons Burned Acres Emissions Tons × × × = Equation 7WRAP 2002 PhII EI Report_20050722.doc 57 

## 4.4 Allocation of Emissions to Realistic Event Size and Day of Year Emissions calculated per month were allocated into realistic fire size packets in a process similar to allocating agricultural fire emission into daily events. A suite of statistics of typical rangeland fire sizes and frequency distributions (probability of occurrence) by plume class were supplied by the FEJF and appear in Table 34. It was not po ssible to split the by-month by-county emissions exactly into the probabilities specified by the FE JF. Regardless, a fundamental distribution of events was achieved. This actual occurrence by plume class size is recorded in Table 34.
Table 34: Rangeland Burning Fire Size Packet Statistics

Plume Class Low End of Range (tons PM 2.5 ) High End of Range (tons PM 2.5 ) Packet Fire Size

(acres) Packet Fire Size (tons PM 2.5 ) Proposed Probability of

Occurrence Actual Occurrence in

Daily Data 1 0 1 100 1.483 0.1 0.3 2 >1 10 200 2.966 0.6 0.6 3 >10 100 1,000 14.831 0.3 0.1

All fire events in a given month were assigned ra ndomly to a day in that month. No blackout days were deemed applicable to the months in which rangeland burning was presumed to occur.


## 4.5 Allocation of Emissions to Coordinate Location Daily burning events were located randomly with in the county to portions considered to be rangeland, as mapped in the U.S. Geologic Servic e’s Land Cover Characteristics (LCC) Database. LCCs are categorized per Table 35, and a corresponding map of rangeland is shown in Figure 11. The coordinate of the fire location was the ce ntroid of a 1-km square LCC pixel randomly selected within the county.WRAP 2002 PhII EI Report_20050722.doc 58 Table 35: USGS Land Cover Characteristics Flagged as Rangeland

LCC Description Rangeland? Urban and Built-Up Land - Dryland Cropland and Pasture Yes Irrigated Cropland and Pasture - Cropland/Grassland Mosaic - Cropland/Woodland Mosaic - Grassland Yes Shrubland Yes Mixed Shrubland/Grassland Yes Savanna Yes Deciduous Broadleaf Forest - Evergreen Broadleaf Forest - Evergreen Needleleaf Forest - Mixed Forest - Water Bodies - Wooded Wetland - Barren or Sparsely Vegetated - Wooded Tundra - Mixed Tundra - Snow or Ice - 254 - Unlabelled Land Area -WRAP 2002 PhII EI Report_20050722.doc 59 Figure 11: USGS Land Cover Characteristics Mapped as RangelandWRAP 2002 PhII EI Report_20050722.doc 60 SECTION 5 

# RESULTS
5.1 Summary of 2002 Phase II Fire Emission Inventory A total of 1,748 wildfires were included in th e 2002 wildfire emission inventory with a mean duration for each fire of 3.3 days. These fires represented a total of 1,281,000 tons PM 2.5 and 1,490,000 tons PM 2.5 with smoldering factored in. An estimated total of approximately 5.3 million acres and 124 million tons of fuel were consumed by wildfire in 2002. Wildfire acres burned were highest during the summer months and peaked in the month of July. Wildfire activity differed widely by state with the highest ac tivities in Alaska and Oregon.
A total of 35 Wildland Fire Use (WFU) events we re included in the 2002 Phase II fire emission inventory. These fires lasted an average of 10. 3 days, burned a total of 202,000 acres and emitted 82,000 tons of PM 2.5 . The 2002 prescribed fire emission inventory was co mprised of significantly more events than the wildfire inventory with 16,396 original fire days . The total acreage consumed by prescribed burns was 649,000 acres and the total fuel consumed was approximately 7.2 million tons. Over 45 percent of the prescribed burning activity reco rds were piled fuels. Temporally, prescribed burning had two peaks: one in the spring and a higher peak in the fall.
Non-federal prescribed rangeland burning cont ributed 1.04 million acres burned and 15,000 tons of PM 2.5 to the 2002 inventory while agricultural bu rning totaled 2.2 million burned acres and 35,000 tons PM 2.5 . The lower emissions rates with respect to acres burned of both of these sources (relative to wildland burning) are indi cative of lower average fuel loadings.
Wildfires contributed nearly 88 percent of the total emission of PM 2.5 for the 2002 Phase II EI. Prescribed burning and WFU fires contributed 4.2 percent and 4.8 percent, respectively. Rangeland and agricultural contributed 3 percent combined. Wildfire contributed the dominant percentage of PM 2.5 due to a combination of greater acres of activity and higher fuel loading rates.
According to the FEJF natural and anthropogenic categorization, 4 percent of the Phase II EI PM 2.5 emissions were classified as anthropogenic and 96 percent were classified as natural.
Table 36 and Figures 12 through 22 present the resu lts of the Phase II EI. The assortment of figures, though not an exhaustive display for emi ssion inventory statistics, is intended to provide a meaningful summary of the Phase II EI data.WRAP 2002 PhII EI Report_20050722.doc61Table 36: 2002 Phase II EI Fire Activity and PM2.5Emissions by State – All Fire Types(Including fuel loading and PM2.5emissions added due to smoldering.)Wildfire Prescribed Fire WFUStateFireDays AcresTons FuelConsumedTonsPM2.5FireDays AcresTons FuelConsumedTonsPM2.5FireDays AcresTons FuelConsumed Tons PM2.5AK 1,109 1,790,533 66,614,205 802,701 214 1,108 15,024 177 158 159,554 5,611,305 67,616AZ 402 556,601 8,375,651 100,927 1,412 103,619 1,814,906 20,230 0 0 0 0CA 907 505,940 9,294,232 111,995 1,595 86,790 847,822 9,396 38 4,051 191,197 2,304CO 446 412,633 8,998,546 108,432 186 17,425 56,988 379 52 22,852 676,518 8,152ID 286 78,141 617,118 7,436 1,308 89,754 995,366 11,661 56 3,543 156,105 1,881MT 220 113,463 921,178 11,100 2,815 77,719 666,265 7,086 4 25 1,180 14ND 148 83,397 303,228 3,654 185 26,826 59,151 713 0 0 0 0NM 244 247,243 1,649,118 19,872 155 25,292 185,821 2,029 16 4,759 16,141 194NV 178 82,163 1,629,911 19,640 71 5,795 31,106 327 0 0 0 0OR 835 899,800 19,342,371 233,076 4,174 129,068 1,713,780 12,553 0 0 0 0SD 156 78,566 199,517 2,404 219 8,811 20,294 245 0 0 0 0UT 436 210,711 2,521,795 30,388 385 14,531 190,945 2,021 14 545 16,285 196WA 200 89,809 983,495 11,851 3,377 41,164 363,093 2,243 0 0 0 0WY 268 127,486 2,191,658 26,409 349 21,140 234,928 2,360 31 6,220 95,208 1,147Total 5,835 5,276,485 123,642,024 1,489,886 16,445 649,044 7,195,489 71,421 369 201,548 6,763,940 81,505Agricultural Burning Non-FederalRangeland Prescribed BurningStateFireDays AcresTons FuelConsumedTonsPM2.5FireDays AcresTons FuelConsumedTonsPM2.5AK 0 0 0 0 0 0 0 0AZ 1,344 16,203 32,045 209 352 250,001 437,502 3,708CA 62,428 727,641 1,734,750 8,543 383 40,000 70,000 593CO 2,124 38,231 139,180 852 372 12,000 21,000 178ID 11,155 292,352 604,994 4,303 234 8,000 14,000 119MT 1,848 8,888 24,796 194 556 150,001 262,502 2,225ND 17,627 212,574 414,306 2,162 327 25,000 43,750 371NM 329 21,180 35,745 190 311 60,000 105,000 890NV 0 0 0 0 102 1,000 1,750 15OR 2,250 129,781 436,622 3,407 450 300,001 525,002 4,449SD 528 5,018 15,998 136 590 150,001 262,501 2,225UT 725 16,684 36,605 210 196 25,000 43,750 371WA 3,127 656,705 2,515,880 13,797 114 6,000 10,500 89WY 2,506 38,221 70,871 576 141 15,000 26,250 222Total 105,991 2,163,478 6,061,792 34,578 4,128 1,042,003 1,823,508 15,454WRAP 2002 PhII EI Report_20050722.doc 62 Figure 12: Annual Acres Burned by Fire Type

WRAP 2002 Phase II Fire Emission Inventory Annual Acres Burned by Fire Type

5,276,485

649,044 201,548 2,163,478 1,042,003

Wildfire Prescribed WFU Agricultural Nfrangeland

Figure 13: Annual PM 2.5 Emissions by Fire Type (tons) WRAP 2002 Phase II Fire Emission Inventory Annual PM 2.5 Emissions by Fire Type (tons)

1,489,886 71,421 81,505 34,578 15,454

Wildfire Prescribed WFU Agricultural NfrangelandWRAP 2002 PhII EI Report_20050722.doc 63 Figure 14: Annual Region-Wide Emissions (tons) WRAP 2002 Phase II Fire Emission Inventory Annual Region-Wide Emissions (tons)

0 500,000 1,000,000 1,500,000 2,000,000 2,500,000Tons

Wildfire Prescribed WFU Agricultural Nfrangeland

Nfrangeland 16,165 15,454 6,948 4,039 711 8,215 10,877 4,577 611 2,316 115,875 Agricultural 36,587 34,578 14,329 6,747 1,745 13,939 32,575 15,710 2,374 7,363 364,202 WFU 95,033 81,505 39,231 5,073 13,528 45,995 45,995 20,968 5,749 4,397 977,389 Prescribed 82,014 71,421 34,803 4,542 10,593 43,328 41,999 22,306 6,116 3,918 835,917 Wildfire 1,737,170 1,489,886 717,124 92,732 247,284 840,766 840,766 383,290 105,096 80,367 17,866,27 PM10 PM2.5 OC EC PMC CH4 VOC NOX SO2 NH3 CO

Figure 15: State Totals for All Fire Sources as a Percentage of Regional Total (Annual) WRAP 2002 Phase II Fire Emission Inventory State Totals for All Fire Sources as a Percentage of Regional Total (Annual)

0% 10% 20% 30% 40% 50% 60%

AK AZ CA CO ID MT ND NM NV OR SD UT WA WY
Acres Fuel Loading PM2.5WRAP 2002 PhII EI Report_20050722.doc 64 Figure 16: Acres Burned Temporal Distribution (month) WRAP 2002 Phase II Fire Emission Inventory Acres Burned Temporal Distribution (month)

0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000

MonthAcres

Wildfire Prescribed WFU Agricultural Nfrangeland Wildfire 1,040 17,617 27,464 96,221 364,567 1,597,409 1,552,0611,400,131 194,851 13,325 10,468 1,332 Prescribed 12,876 18,977 28,175 63,674 69,192 16,312 19,599 2,548 78,421 122,755 171,827 44,688 WFU 0 0 0 250 0 0 85,326 109,738 5,216 939 79 0 Agricultural 142,348 70,074 238,123 286,824 57,743 57,579 52,529 276,929 458,561 288,153 146,313 88,302 Nfrangeland 0 0 253,058 253,058 253,058 126,529 0 0 78,150 78,150 0 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Figure 17: PM 2.5 Emissions (tons) Temporal Distribution (month) WRAP 2002 Phase II Fire Emission Inventory PM 2.5 Emissions (tons) Temporal Distribution (month)

0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 20,000

MonthTons PM2.5

Wildfire Prescribed WFU Agricultural Nfrangeland Wildfire 47 727 2,571 4,808 111,175 426,477 374,590 516,077 44,714 3,857 4,306 538 Prescribed 887 1,961 2,651 5,083 7,666 2,275 838 203 10,057 18,186 18,333 3,280 WFU 0 0 0 14 0 0 38,932 40,270 1,700 503 85 0 Agricultural 1,657 838 4,088 6,011 988 1,121 1,423 4,383 7,453 4,253 1,479 884 Nfrangeland 0 0 3,753 3,753 3,753 1,877 0 0 1,159 1,159 0 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecWRAP 2002 PhII EI Report_20050722.doc 65 Figure 18: Annual Acres Burned Spatial Distribution (state) WRAP 2002 Phase II Fire Emission Inventory Annual Acres Burned Spatial Distribution (state)

0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 200,000

StateThousands of Acres

Wildfire Prescribed WFU Agricultural Nfrangeland Wildfire 1,790,533 556,601 505,940 412,633 78,141 113,463 83,397 247,243 82,163 899,800 78,566 210,711 89,809 127,486 Prescribed 1,108 103,619 86,790 17,425 89,754 77,719 26,826 25,292 5,795 129,068 8,811 14,531 41,164 21,140 WFU 159,554 0 4,051 22,852 3,543 25 0 4,759 0 0 0 545 0 6,220 Agricultural 0 16,203 727,641 38,231 292,352 8,888 212,574 21,180 0 129,781 5,018 16,684 656,705 38,221 Nfrangeland 0 250,001 40,000 12,000 8,000 150,001 25,000 60,000 1,000 300,001 150,001 25,000 6,000 15,000 AK AZ CA CO ID MT ND NM NV OR SD UT WA WY

Figure 19: Annual PM 2.5 Emissions (tons) Spatial Distribution (state) WRAP 2002 Phase II Fire Emission Inventory Annual PM 2.5 Emissions (tons) Spatial Distribution (state)

0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 20,000

StateTons PM2.5

Wildfire Prescribed WFU Agricultural Nfrangeland Wildfire 802,701 100,927 111,995 108,432 7,436 11,100 3,654 19,872 19,640 233,076 2,404 30,388 11,851 26,409 Prescribed 177 20,230 9,396 379 11,661 7,086 713 2,029 327 12,553 245 2,021 2,243 2,360 WFU 67,616 0 2,304 8,152 1,881 14 0 194 0 0 0 196 0 1,147 Agricultural 0 209 8,543 852 4,303 194 2,162 190 0 3,407 136 210 13,797 576 Nfrangeland 0 3,708 593 178 119 2,225 371 890 15 4,449 2,225 371 89 222 AK AZ CA CO ID MT ND NM NV OR SD UT WA WYWRAP 2002 PhII EI Report_20050722.doc 66 Figure 20: Annual Natural and Anthropogenic PM 2.5 Emissions by State (tons) WRAP 2002 Phase II Fire Emission Inventory Annual Natural and Anthropogenic PM 2.5 Emissions by State (tons)

-10,000 10,000 30,000 50,000 70,000 90,000 110,000 130,000 150,000Tons PM2.5

Anthropogenic Natural Natural 870,324 123,984 118,516 116,941 12,709 15,701 4,737 22,577 19,884 239,754 4,873 32,572 12,833 29,201 Anthropogenic 170 1,090 14,315 1,052 12,691 4,919 2,162 598 98 13,731 136 614 15,147 1,515 AK AZ CA CO ID MT ND NM NV OR SD UT WA WY

Figure 21: Annual Anthropogenic PM 2.5 Emissions by State and Fire Type (tons) WRAP 2002 Phase II Fire Emission Inventory Annual Anthropogenic PM 2.5 Emissions by State and Fire Type (tons)

0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000

AK AZ CA CO ID MT ND NM NV OR SD UT WA WYTons PM2.5

Agricultural Prescribed Piled Prescribed BroadcastWRAP 2002 PhII EI Report_20050722.doc67Figure 22: Anthropogenic PM2.5Emissions by Month and State (tons)WRAP 2002 Phase II Fire Emission InventoryAnthropogenic PM2.5Emissions by Month and State (tons)02,0004,0006,0008,00010,00012,00014,000Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Tons PM 2.5AKAZCACOIDMTNDNMNVORSDUTWAWA30 38 2,472 4,874 212 38 76 490 3,457 2,767 557 137UT7 11 14 270 22 17 0 88 116 58 8 2SD0 0 68 68 0 0 0 0 0 0 0 0OR43 156 188 1,377 2,553 814 941 1,293 563 1,450 2,946 1,407NV24 0 10 1 56 0 0 0 0 2 5 0NM56 68 50 11 0 141 20 3 184 62 2 1ND0 0 0 0 0 0 0 0 720 721 721 0MT0 0 18 184 563 270 4 14 371 464 3,030 0ID0 0 221 644 1,872 539 135 1,673 3,704 1,646 1,787 470CO152 132 143 66 22 6 120 137 137 67 65 5CA1,528 694 1,248 1,298 827 604 221 371 2,395 2,365 1,519 1,245AZ55 38 90 17 0 40 53 16 109 416 149 107AK0 0 0 0 0 18 50 53 49 0 0 0Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecWRAP 2002 PhII EI Report_20050722.doc 68 SECTION 6 

# DELIVERABLES AND END USER DATA SUPPORT

Deliverables for this contract were made av ailable on CD-ROM and for download on the Internet. The link(s) to the webpage for deliverables are on the WRAP’s website at http://www.wrapair.org/forums/fejf/tasks/FEJF task7.html. Digital products include:

• SMOKE input text files (IDA format) for all fire sources. These are PTINV, PTDAY, and PTHOUR files as specified by the WR AP Modeling Forum and Regional Modeling Center.

• NIF 3.0 for Fire (NIF Point text format) for all fire sources intended for CERR submittal and upload to the WRAP EDMS. These files were provided in a region-wide file and by state for each fire source.

• This final report as a PDF file.
The initial delivery of the electronic data files of fire inventories were acquired by the WRAP’s contractors for the Emissions Data Management System (EDMS) and the Regional Modeling Center (RMC). These “end users” of the Phase II emissions inventory files identified several data content and format issues as the electronic file s were integrated into the EDMS or the modeling system. As data issues were discovered, the contractors (Pechan and the RMC) contacted Air Sciences to investigate the cause of the data pr oblems. Some of these issues stemmed from the formats of the files delivered by data suppliers (e .g., states) during the QC Binder review process (labeled DATA SUPPLIER in the list below). Othe r issues (labeled as END USER tasks) reflect specific data formatting demands or recommend ations from the RMC or Pechan. The DATA SUPPLIER and END USER tasks were completed to re solve issues in the emission inventory data that would not have been reasonably discovered by Air Sciences until end users of the data attempted to utilize the data files.
In addition, during the QC effort involving the en d users, Air Sciences discovered several issues that could have reasonably been discovered by Ai r Sciences during our internal QC checks of the data. These tasks have been labeled AIR SCIENCES and there are no costs to the FEJF associated with executing these tasks.
1. Malformed dates in CA Ag files (DATA SUPPLIER). Issue: Records were intended to be dropped and had zero emissions.
Resolution: Drop flag enforced in the emissions processing file.
2. Blank dates in AZ prescr ibed burning (DATA SUPPLIER).WRAP 2002 PhII EI Report_20050722.doc 69 Issue: Error in date pars ing during raw data import.
Resolution: Corrected records and re-merged to main database.
3. NIF files inconsistently referred to year "2002" vs. "02" (DATA SUPPLIER). Issue: Format of year data was variable ac ross data coming into system from federal and state data sources. PT files required "02" and NIF/EDMS system required "2002."
Resolution: Revised NIF export script to en force "2002." PT export script continued to enforce "02."
4. Missing PTHOUR records with rega rd to PTINV file (AIR SCIENCES). Issue: CA agricultural burning data record s were missed during data processing for a block of records during the integration of CA records during the QC-binder review/integration process.

Resolution: Batch file amended.
5. NIF export produced large Combustion Efficiency (CE) table (END USER).

Issue: The CE table was included in the NIF scripts, and the NIF export files were checked for completeness (specifically, valid valu es for fields for control efficiency were filled in so that NIF files would pass EPA's QA Checker). Advised by Pechan to flag events as "uncontrolled" in EM table and thereby eliminating the need for CE table.
Resolution: Amended NIF script. EPA QA chec ker run with blank text file for CE table as work around.

6. SCC miscode. Issue: SCC miscoded for certain piled pres cribed burns (note: Natural/Anthropogenic flagging was correct) (AIR SCIENCES).

Resolution: Corrected SCC formula in Ex cel and recalculated emission inventory worksheet.

7. Emission factor for "other ag burning" in incorrect units (in the look-up table as kg/Mg but should be lbs/ton, a factor of 2x greater than kg/Mg) (AIR SCIENCES). Issue: Problem was isolated to that crop code (which is used exclusively when crop type information is not provided in source data). Correction added about 250 tons PM 2.5 to the inventory, mostly in CA with small amounts in two other states.
Resolution: Corrected look-up table and re calculated emission inventory worksheet.WRAP 2002 PhII EI Report_20050722.doc 70 SECTION 7 

# REFERENCES

Air Sciences Inc. 2002. Integrated Asse ssment Update and 2018 Emission Inventory for Prescribed Fire, Wildfire, and Agricultural Bu rning. Draft Report. Prepared for the Fire Emissions Joint Forum of the Weste rn Regional Air Partnership. Anderson, G. K., D. V. Sandberg and R. A. No rheim. 2001. Fire Emission Production Simulator (FEPS) User's Guide. Version 1.0. USDA Forest Service. Battye, W., and R. Battye. 2001. Development of Emissions Inventory Methods for Wildland Fire. Draft Final Report to the U.S. EPA OAQPS. Cohen, J.D. and J.E. Deeming. 1985. The Nation al Fire-Danger Rating System: Basic Equations. USDA, Forest Service. Report PSW-82. Eastern Research Group, Inc.; Enviro-Tech Co mmunications. 2002. Non-Burning Management Alternatives on Agricultural Lands in the Wes tern United States. Prepared for the Fire Emissions Joint Forum of the Weste rn Regional Air Partnership. U.S. Environmental Protection Agency. 1996. Supplements to the Compilation of Air Pollutant Emission Factors AP-42, Fifth Edition, Volume I: Stationary Point and Area Sources, Section 13.1- Wildfires and Prescribed Burning.

# APPENDIX A 

# Data Gathering and CompilationWRAP 2002 PhII EI Report_20050722.doc A-1 

## Wildfire Wildfire activity data was collected from federal databases by WRAP staff.

• Contact name and agency : John Graves, Arizona DEQ.

• Date received : 7/24/2003

• Assumptions : Wildfire activity data reportedly included both wildfire and wildland fire use (WFU). Therefore, WFU activity in prescribed fire databases not included in the (prescribed) fire activity. This was a categorical decision based on information provided by John Graves that was subsequently applied to all states. Decision was made since some databases for prescribed fire activity also included WFU activity, for example, the DOI database (see below).



## Prescribed Fire Alaska

• Contact name and agency : Ron King, Program Manager, Alaska DEC. (Backup contact: Joan Hardesty, Alaska DEC.)

• Date received : 4/20/04

• Assumptions : None

• Additional notes : Data only contained wildfire re cords. Based on further inquiry prescribed fire activity for AK not availabl e. However, a NFDRS fuel loading map for AK was located in the process of additional research on AK fire data (downloadable from the state forest health web site). This map was incorporated into the wildfire inventory in order to assign fuel loading to the AK wildfire records that did not have an NFDRS entry. The AK map was based on the Canadian equivalent of the NFDRS, the CFFDRS. A cross-referenced key to convert the CFFDRS codes to NFDRS codes was obtained from the same source as the map (http://agdc.usgs.gov/AGDCgateway.html).

Arizona

• Contact name and agency : Mark Fitch, Arizona DEQ.

• Date received : 3/8/04

• Assumptions : End date assumed to be same as st art date, effectively creating all oneday fire events. Both burn types in the da tabase, specifically, "Activity-nonpile" and "Natural" were assumed to be prescribed burns, broadcast burns.

• Additional notes : Complete data set with approximately 73,000 acres, distributed over 433 fire entries, and several burn agencies.WRAP 2002 PhII EI Report_20050722.doc A-2 California

• Contact name and agency : Neva Sotolongo, California ARB

• Date received : 4/8/04

• Assumptions : Burn type assumed to be all broadcast burns. No identifier for piles included in data. Some records have fire end date of ZERO. End date assumed to be same as start date, effectively creating one-day fire events.

• Additional notes : The data only included incomplete records reported by CDF, not from other agencies. Hence, the data unde restimated actual statewide activity. Data was received in the form of a GIS layer, which was converted to latitude/longitude by Air Sciences Inc.

Colorado

• Contact name and agency : Colleen Campbell, Colorado DPHE

• Date received : 4/9/04

• Assumptions : End date assumed to be same as st art date, effectively creating one-day fire events. Fuel loading – broadcast data was provided in terms of fuel loading and consumption (by size class). Pile loading on ly indicated volume of piles, percent of piles and corresponding PM emissions, not actual tonnage. Tonnage was backcalculated from PM emissions in one of tw o ways: (1) if pile volume and consumption available, then calculated by mu ltiplication (Pile volume)*(percent consumption)*(loading per pile volume). The latter was back-calculated from PM emissions assuming the same emission factors for pile as for broadcast burns. (2) if only acres available for pile burn, assumed (g eometric) mean of all CO pile burns (9.1 t/a). Also, the approach described under (1) resulted in two entries with very high fuel loading (up to >920 t/a); these two records were adjusted by assuming the geometric mean pile loading (~10 t/a). This adjustment decreased fuel loading and increased the acreage, thereby keeping the total fuel co nsumed the same as the original data.

• Additional notes : This data set had ~18K acres distributed over 189 fire records. Data was received in two different file formats, which were combined to provide the most complete information. The daily acres file was used to derive actual acres burned under each permit. The general permit inform ation was used as a look-up table to fill out the activity data in the daily acres file, for example, fire location.WRAP 2002 PhII EI Report_20050722.doc A-3 Idaho

• Contact name and agency : David Grace, USFS.

• Date received : 3/22/04

• Assumptions : Data missing description of fire ty pe. All fires assumed to be broadcast burns.

• Additional notes : Although data was provided by the USFS, the data was originally assembled by ID-DEQ (e-mail communication , David Grace, 3/22/04). After deletion of nine fire records dated in 2003, this data set was ~33K acres, distributed over 554 fire entries, and several burn agencies.

Montana

• Contact name and agency : Robert Habeck, Montana DEQ.

• Date received : 3/12/04

• Assumptions : None.

• Additional notes : Complete data set with ~219K acres, distributed over 1,813 fire entries, and several burn agencies.

North Dakota

• Contact name and agency : Chuck McDonald, North Dakota Dept. of Health.

• Date received : 4/1/04

• Assumptions : If more than one section entered for location, set to first section only.

• Additional notes : Data received as hard copy an d entered into spreadsheet. Corrected mix-up in units of the pre-burn fuel loading in the data entry sheets.

New Mexico

• Contact name and agency : Lisa Bye, New Mexico DEQ.

• Date received : 3/16/04

• Assumptions : End date assumed to be same as st art date, effectively creating one-day fire events. If more than one section entered for location, set to first section only, but this was not a major issue, since latitude an d longitude were provided for each entry as well.

• Additional notes : Complete data set with ~9K acres, distributed over 44 fire entries, and several burn agencies. Also, two entrie s in the data set (~3,500 acre total) had 2003 data instead of 2002. Assumed to be 2002.WRAP 2002 PhII EI Report_20050722.doc A-4 Nevada

• Contact name and agency : Samuel Jackson, Nevada DEP.

• Date received : 4/13/04

• Assumptions : Fuel loading provided for 3 record s only; loading for remaining records based on NFDRS. NFDRS assigned by the fu el type description provided in the raw data. Location - some fire locations were reported as a lat/long combination; most reported as TRS. If more than one section entered for location, set to first section only.

• Additional notes : Data received in form of Excel f ile with 21 fire records, totaling ~8K

acres.

Oregon

• Contact name and agency : Mike Ziolko, Oregon DF.

• Date received : 4/19/04

• Assumptions : The piled burns were inconsistent in quality. Some records had very high acreages associated, up to 9,600 acres, others had very high fuel loading, up to 2,500 tons/acre. In order to resolve these unrealistically high values, the mean loading for piled burns in the OR data (excluding the outliers, specifically, acreage>1,500 acres or loading >150 t/a) was calculated. Next a ll OR pile burns were normalized based on the (geometric) mean loading, specifically, 12. 5 t/a. Since this procedure concurrently adjusted fuel loading and acreage, the tota l fuel consumption for each fire record stayed the same. Location – format of state TRS notation was converted to GIS format. Specifically, T or R entries, which were in the hundreds, had the last zero removed (for example, township 360 N changed to 36N).

• Additional notes : This data set was clean and complete except for inconsistent reporting of piled fire acreage, with ~166K acres total, distributed over 3,603 fire records.

South Dakota

• Contact name and agency : Steven Hasenohrl, South Dakota DA.

• Date received : 3/26/04

• Assumptions : No fire type provided, so assumed to be broadcast burn.

• Additional notes : Only one state record for 2002 (150 acres).WRAP 2002 PhII EI Report_20050722.doc A-5 Utah

• Contact name and agency : Greg Zschaechner, Utah DEQ. (Via Pete Lahm)

• Date received : 2/20/04

• Assumptions : None

• Additional notes : Only 11 records totaling ~1.5K acres satisfied data quality objectives and were carried over to EI. UTM coordinate s (provided) were converted to latitude and longitude using a GIS overlay map.

Washington

• Contact name and agency : Mark Gray, Washington DNR.

• Date received : 4/6/04

• Assumptions : Agency information based on key fr om Mark Gray. Burn type indicated as piled or broadcast. Calculated defaul t fuel loadings were 14.2 and 8.5 t/a for broadcast- and piled burns, respectively. Broadcast fuel loading- if data available loading in t/a calculated from provided data, if not, set to default. Piled fuel loading set to default loading, calculated as the mean loading for broadcast burns, multiplied with fuel collection efficiency of 60 percent (*0.6). Blackened acres for broadcast burns were available from the data. Acres for p iled burns (not provided) were calculated based on total loading (provided) and defaul t tonnage per acre. Location – format of state TRS notation was converted to GIS form at. Specifically, T or R entries, which were in the hundreds, had the last zero removed (for example, township 360 N changed to 36N).

• Additional notes : Large data set containing 3,261 records totaling ~41K acres.

Wyoming

• Contact name and agency : Darla Potter, Wyoming DEQ.

• Date received : 8/3/04

• Assumptions : Start date - assumed to be same as date in comment field. If comment data absent, set to planned date; if planned date absent, then assumed to be onsubmitted date. End date - assumed to be same as start date, effectively creating oneday fire events. Fuel type - raw data give s fuel type. This description was specific enough to assign an NFDRS fuel model (letter code). Fire location - if more than one section reported for location, set to first sect ion only. Fire type - several fire entries without acres, but with number of piles. In absence of loading data, the median pile size was calculated from all complete WY ac res by number of pile combinations. This resulted in 1 acre per pile (n=24). For a ll pile burns without acreage then, acreage wasWRAP 2002 PhII EI Report_20050722.doc A-6 set to 1 acre per pile. Fuel loading – no da ta, but will be calculated based on assigned NFDRS model.

• Additional notes : The pre-processing described above resulted in ~40K acres, distributed over 100 fire entries, and several burn agencies. One 11,000 fire entry was deleted from database upon recommendat ion as it never was burned (personal communication, Gavin Lowell, 6/3/04).

DOI-1202

• Contact name and agency : [Confirm with source]

• Date received : [Confirm with source]

• Assumptions : All fires assumed to be broadcast burns. Location based on provided latitude and longitude or, alternatively, TRS coordinates. Fuel loading based on NFDRS fuels map, which was either provid ed in the data or derived from a GIS overlay with the NFDRS fuels map.

• Additional notes : This data set covered four agencies: BIA, BLM, FWS and NPS. It was clean and had ~180K acres, distributed ov er 707 fire records, all for Rx on USFS lands.

NIFPORS

• Contact name and agency : Susan Lee, USFS

• Date received : 4/20/04

• Assumptions : Fuel loading was not provided and was calculated based on NFDRS fuel loading map. Two large fires set to zero due to extreme outliers: UT Dixie National Forest D3 Adams Head (~25K acres) and D3 Sandford Creek (~10K acres). Both were broadcast burns. If kept in database, thes e fires would have been assigned to one-day event only.

• Additional notes : This data set was clean and had ~290K acres, distributed over 1,145 fire records, all for Rx on USFS lands.

FASTRAC (WA and OR)

• Contact name and agency : Jim Russell, USFS.

• Date received : 4/22/04

• Assumptions : None

• Additional notes : This data set was similar to data provided earlier by the state agencies in WA and OR. Hence, to avoid duplicate fire entries this data was notWRAP 2002 PhII EI Report_20050722.doc A-7 incorporated in the emission inventory. However, it was used in the quality assurance effort of the WA and OR state data.



## Agricultural Burning – QC Packet Responses

Alaska

• No Packet sent to Alaska

Arizona

• Contact name and agency : Randy Sedlacek/Trevor Baggiore, USFS c/o Arizona DEQ

• QC response : No change.

California

• Contact name and agency : Neva Sotolongo, CA EPA

• QC response : All new data - Year 2000 statewide database. 2002 database for San Joaquin Valley Air District.

• Additional notes : The 2000 CA statewide database included 71,457 event records. All records in the statewide database incl uded a crop and county, most included date or month, some included TRS location.

• The 2002 SJV ag burning activity database included 51,782 event records. All records included county, crop, and date. The database included location data in the form of street addresses rather than coordinates or TRS data. Reportedly, TRS location data is available, but it was never received.

• For the WRAP inventory, the statewide da tabase was used but the records for SJV and all of Kern County were replaced with the SJV 2002 data. The inventory includes 9,324 records from the statewide database and 51,712 records from the SJV database. A few of these records were subsequently dropped because of incomplete information.

Colorado

• Contact name and agency : Coleen Campbell, CO APCD

• QC response : Initial response was from James Sharkoff, who reported that no ag burning occurs in CO. Further inquiry le d to an ag burning summary from Coleen Campbell. The data submitted by Coleen was an annual summary with three crop types by county.WRAP 2002 PhII EI Report_20050722.doc A-8 • Additional notes : A monthly distribution of crop burning based on local anecdotal information, developed in coordination with Coleen, was used for temporal allocation.

Idaho

• Contact name and agency : Diane Riley, ID DEQ

• QC response : New data for 16 counties including 1,088 records. Suggested updating 1996 NASS-based data with 2002 NASS data.

• Additional notes : Post-QC Phase II database for ID comes from three sources: new database for 16 counties from Diane Rile y, NASS-based data for wheat and barley updated using 2002 NASS data, and 1996 EI da ta for remainder of counties and crops.

Montana

• Contact name and agency : James Carlin, MT DEQ

• QC response : MT submitted ditch burning data to supplement the existing ag burning activity data. The data included acres of ditch burning by month and county.

• Additional notes : MT ag burning inventory remained unchanged aside from the addition of ditch burning data.

New Mexico

• Contact name and agency : Rita Trujillo, NM Environmental Dept.

• QC response : NM submitted revised data, which included acres by county, month and crop.

• Additional notes : Rita Trujillo sent an electronic copy of Feedback Form B marked up with changes for the Phase II EI. The new data includes 20 records and replaces the 1996 EI data for NM.

Nevada

• Contact name and agency : Chester Sergent, NV Bureau of Air Quality

• QC response : No new data.

• Additional notes : 1996 EI had no data for NV ag burning. Existing 1996 data for NV was an annual summary of burning with no crop data. A special packet was sent to NV to solicit more specific da ta with crops and monthly allocation of burning. The response from NV was that there was no ag burning data availableWRAP 2002 PhII EI Report_20050722.doc A-9 other than the annual summary without crop information. This database does not meet the minimum requirements for the WRAP EI and cannot be included in the inventory without additional informat ion concerning crops and temporal allocation.

North Dakota

• Contact name and agency : Gene Nelson, ND Health Dept.

• QC response : ND said the data looks representative for ND, and no changes were necessary.
Oregon

• Contact name and agency : Jeffrey Stocum, OR DEQ

• QC response : New database for 2002: annual summary of acres burned by crop plus a temporal allocation scheme to allocate the annual data to months.

South Dakota

• Contact name and agency : Rick Boddicker

• QC response : 5,000 ditch burning acres to replace SD ag burning data.

• Additional notes : Rick Boddicker reports that there is very little ag burning in South Dakota. Total burning is reported to be 1,000 to 5,000 acres to clear weeds and cattails in wet areas in eastern SD. For Phase II, 5,000 acres of ditch burning was estimated for SD and allocated equally between the counties on the eastern border. The temporal allocation was not changed from 1996 EI: half in March, half in April.

Utah

• Contact name and agency : Aaron Chambers, UT DEQ

• QC response : Annual summary of burning by crop and county to replace 1996 EI data.

• Additional notes : Aaron Chambers submitted 30 MS Excel files, each containing an annual summary of ag burning for 2002 for one county. Aaron sent some basic guidelines for when burning occurred, but said it was crop-specific and was unable to give a detailed temporal allocation by crop. A temporal allocation was derived using the guidelines given by Aaron and looking at Idaho and other WRAP data for each crop.WRAP 2002 PhII EI Report_20050722.doc A-10 Washington

• Contact name and agency : Karen Wood, WA Ecology

• QC response : 2003 statewide ag burning database.

• Additional notes : Washington sent a new 2003 ag burning database to be used as the most representative data for 2002. The 2003 data was event-level data with TRS location, crop, month, and acres and resi due loading. There are 3,235 records in the data set. This data replaced the Washington data in the 1996 EI.

Wyoming

• Contact name and agency : Darla Potter, WY DEQ

• QC response : New 2002 statewide ag burning inventory

• Additional notes : The new WY database for 2002 ag burning included acres by summary by county, crop, and month.

Nez Perce, Coeur d’Alene and Spirit Lake Tribes

• Contact name and agency : Alene George, Coeur d'Alene Lands Dept. Julie Simpson, Nez Perce Air Quality Frank Black Cloud, Spirit Lake Air Programs

• QC response : No formal response

# APPENDIX B 

# WRAP NIF 3.0 for Fire Format SpecificationWRAP 2002 PhII EI Report_20050722.doc B-1 Table B-1: WRAP NIF 3.0 for Fire - Transmittal Record

EPA NIF Field WRAP NIF Fire Field Example Value Comment strRecordType Record Type TR TR for every record strStateCountyFIPS FIPS 02050 No two entries in this record will have the same FIPS code strOrganizationName Org Name WRAP strTransactionType Transaction Type 00 "00" means "Original" intInventoryYear Inventory Year 2002 strInventoryTypeCode Inventory Type CRIT "CRIT" = Criteria lngTransactionCreationDate Transaction Creation Date 20050204 Date of report generation

intIncrementalSubmissionNumber Incremental Submission Number 1 All records get a submission number of 1 unless data gets submitted for a county more than
once sngReliabilityIndicator (Blank)

strTransactionComments Comment s on Inventory no comment Any comments on inventory. Can be entered when creating record
strContactPersonName Client Name Tom Moore WRAP Contact name strContactPhoneNumber Client Phone Number (970) 491-8837 WRAP Contact phone number strTelephoneNumberTypeName Client Phone Type Office WRAP Contact phone number type strElectronicAddressText Client E Address moor et@cira.colostate.edu WRAP Contact E address strElectronicAddressTypeName Type of E A ddress Email WRAP Contact E address type

strSourceType Source Type FIRE FIRE is not a valid NIF code. Submitted as such to make implicit that this is a new format strAffiliationType Affiliation Type Report Certifier According to NIF doc. is always Report Certifier sngFormatVersion NIF Format version 3 NIF version 3.0

strTribalCode Tribal Code 000 WRAP does not report tribal code but required data field in NIF format "000" = "not used"WRAP 2002 PhII EI Report_20050722.doc B-2 Table B-2: WRAP NIF 3.0 for Fire - Site Record

EPA NIF Field WRAP NIF Fire Field Example Value Comment strRecordType Record Type SI SI for every record strStateCountyFIPs FIPS 02110

strStateFacilityIdentifie r Fire ID AK-WF-229-1 Fire ID must be unique for every flaming fire day. Every corresponding smoldering day has the same fire ID. Must be less than 15 characters. strFacilityRegistryIdentifier (Blank) strFacilityCategory (Blank) strORISFacilityCode (Blank) strSICPrimary (Blank) strNAICSPrimary NAICS NA Mandatory NIF field. Will be flagged by QC checker. strFacilityName Fire Name GYPSUM CREEK strSiteDescription Fire Type wildf ire Either wildfire or prescribed.
strLocationAddress Address NA Mandatory NIF field. strCity City NA Mandatory NIF field.
strState State AK strZipCode ZipCode NA Mandatory NIF field. Will be flagged by QC checker strCountry Country US strNTISiteID (Blank) strDun&BradstreetNumber (Blank) strTRIID (Blank) strSubmittalFlag Submittal Flag A "A" = "ADD" other options are delete or revise etc.

strTribalCode Tribal Code 000 WRAP does not report tribal code but required data field in NIF format "000" = "not used"WRAP 2002 PhII EI Report_20050722.doc B-3 Table B-3: WRAP NIF 3.0 for Fire – Emission Unit Record

EPA NIF Field WRAP NIF Fire Field Example Value Comment strRecordType Record Type EU EU for every record strStateCountyFIPs FIPS 02110

strStateFacilityIdentifie r Fire ID AK-WF-229-1 Fire ID must be unique for every flaming fire day. Every corresponding smoldering day has the same fire ID. Must be less than 15 characters.

strEmissionUnitID EU ID (F or S) F Either F or S indicating a flaming or a smoldering fire day No two entries may have the same Fire ID and EU ID strORISBoilerID (Blank) strSICUnitLevel (Blank) strNAICSUnitLevel (Blank) strBlankField (Blank) sngDesignCapacity Area Burned 10 strDesignCapacityUnitNumerator Area Burned Unit ACRE strDesignCapacityUnitDenominator (Blank) sngMaxNameplateCapacity (Blank) strEmissionUnitDescription (Blank) strSubmittalFlag Submittal Flag A "A" = "ADD" other options are delete or revise, etc.

strTribalCode Tribal Code 000 WRAP does not report tribal code but required data field in NIF format "000" = "not used"WRAP 2002 PhII EI Report_20050722.doc B-4 Table B-4: WRAP NIF 3.0 for Fire - Emission Process Record

EPA NIF Field WRAP NIF Fire Field Example Value Comment strRecordType Record Type EP EP for every record strStateCountyFIPS FIPS 02110

strStateFacilityIdentifie r Fire ID AK-WF-229-1 Fire ID must be unique for every flaming fire day. Every corresponding smoldering day has the same fire ID. Must be less than 15 characters.

strEmissionUnitID EU ID (F or S) F Either F or S indicating a flaming or a smoldering fire day

strEmissionReleasePointID Release Point ID F H1 Used to relate the entries in the "EP" record to entries in the "ER" record. A single entry in the ER record exists for every EP record. One for every hour of every fire day (both smolder and flaming fire days).

strProcessID Hour ID H1 Hourly designation. No two records may have the same Fire, EU and Hour ID.
strSCC SCC 2810001000 strProcessMACTCode (Blank)
strEmissionProcessDes cription NFDRS A intWinterThroughputPCT (Blank) intSpringThroughputPCT (Blank) intSummerThroughputPCT (Blank) intFallThroughputPCT (Blank) intAnnualAvgDaysPer Week (Blank) intAnnualAvgWeeksPerYear (Blank) intAnnualAvgHoursPerDay (Blank) IntAnnualAvgHoursPerYear (Blank) sngHeatContent Fuel Loading 0.50 sngSulfurContent (Blank) sngAshContent (Blank) strProcessMACTComplianceStatus (Blank) strSubmittalFlag Submittal Flag A "A" = "ADD" other options are delete or revise etc.

strTribalCode Tribal Code 000 WRAP does not report tribal code but required data field in NIF format "000" = "not used"WRAP 2002 PhII EI Report_20050722.doc B-5 Table B-5: WRAP NIF 3.0 for Fire - Emission Release Point Record

EPA NIF Field WRAP NIF Fire Field Example Value Comment strRecordType ER ER ER for every record strStateCountyFIPs FIPS 02110

strStateFacilityIdentifie r Fire ID AK-WF-229-1 Fire ID must be unique for every flaming fire day. Every corresponding smoldering day has the same fire ID. Must be less than 15 characters. strBlankField (Blank)

strEmissionReleasePoi ntID ER ID F H1 Used to relate the entries in the "EP" record to entries in the "ER" record. A single entry in the ER record exists for every EP record. One for every hour of every fire day (both smolder and flaming fire days). strEmissionReleasePointType ER Point Type 05 strBlankField2 (Blank) sngStackHeight plume top 0.023040 sngStackDiameter plume bottom 0.000000 sngStackFencelineDistance percent first layer 0.469300 sngExitGasTemperature (Blank) sngExitGasVelocity (Blank) sngExitGasFlowRate (Blank)
dblXCoordinate X Position -134.977493
dblYCoordinate Y Position 58.909443 intUTMZone (Blank) Not required for LATLON strXYCoordinateType Coordinate Type LATLON IngHorizontalAreaFugitive (Blank) IngReleaseHeightFugi tive (Blank) strFugitiveDimensionsUnit (Blank) strEmissionsReleasePtDescription ER record Description Hour1 strSubmittalFlag Submittal Flag A "A" = "ADD" other options are delete or revise etc.

strHorizontalCollectionMethodCode Collection Method 027 "027" = "The information is not known" strHorizontalAccuracyMeasure Horizontal Accuracy 0 No accuracy data available

strHorizontalReferenceDatumCode Horizontal Reference NA Mandatory field. NA will be flagged by QC checker.

strReferencePointCode Reference Point 108 "108" = point not included in Code Tables strSourceMapScaleNumber (Blank) strCoordinateDataSourceCode (Blank)

strTribalCode Tribal Code 000 WRAP does not report tribal code but required data field in NIF format "000" = "not used"WRAP 2002 PhII EI Report_20050722.doc B-6 Table B-6: WRAP NIF 3.0 for Fire - Emission Period Record

EPA NIF Field WRAP NIF Fire Field Example Value Comment strRecordType Record Type PE PE for every record strStateCountyFIPs FIPS 02110

strStateFacilityIdentifie r Fire ID AK-WF-229-1 Fire ID must be unique for every flaming fire day. Every corresponding smoldering day has the same fire ID. Must be less than 15 characters.

strEmissionUnitID EU ID (F or S) F Either F or S indicating a flaming or a smoldering fire day

strProcessID Hour ID H1 Hourly designation. No two records may have the same Fire, EU and Hour ID.

IngStartDate Start Date 20020424 Since fire records are daily, StartDate=EndDate and there are the same # of records in the this table as there are in the ER and EP records. Taken From DateSlash Field of GISOUT IngEndDate End Date 20020424 strBlankField (Blank)
intStartTime Start Time 0000 intEndTime End Time 0059 strBlankField2 (Blank) sngActualThroughput Area Burned/Hour 0.0570 Acres Burned times temporal burn factor strThroughputUnitNumerator Area Unit ACRE

intMaterial Material Burned 936 Many options are available such as wood & wood/bark. "936" is vegetation which is what LADCO was reporting strMaterialIO Material Input/Output I intPeriodDaysPerWeek (Blank) intPeriodWeeksPerPeriod (Blank) intPeriodHoursPerDays (Blank) intPeriodHoursPerPeriod (Blank) strSubmittalFlag Submittal Flag A "A" = "ADD" other options are delete or revise etc.

strTribalCode Tribal Code 000 WRAP does not report tribal code but required data field in NIF format "000" = "not used"WRAP 2002 PhII EI Report_20050722.doc B-7 Table B-7: WRAP NIF 3.0 for Fire - Control Record

EPA NIF Field WRAP NIF Fire Field Example Value Comment strRecordType Record Type CE CE for every record strStateCountyFIPs FIPS 02110

strStateFacilityIdentifie r Fire ID AK-WF-229-1 Fire ID must be unique for every flaming fire day. Every corresponding smoldering day has the same fire ID. Must be less than 15 characters.

strEmissionUnitID EU ID (F or S) F Either F or S indicating a flaming or a smoldering fire day

strProcessID Hour ID H1 Hourly designation. No two records may have the same Fire, EU and Hour ID.

strPollutantCode Pollutant Code PM10-PRI Some pollutants like EC OC and CH4 aren't in the table POLLUTANT_CODES but are in the POLLUTANT_CATEGORIES both of which are NIF standard code tables strBlankField (Blank) sngPrimaryPCTControlEfficiency (Blank) sngPCTCaptureEfficiency (Blank) sngTotalCaptureControlEfficiency (Blank) strPrimaryDeviceTypeCode Primary Device Type Code 000 Mandatory Field "000" = "uncontrolled" strSecondaryDeviceTypeCode (Blank) strBlankField2 (Blank) strControlSystemDescription (Blank) strThirdControlDeviceTypeCode (Blank) strFourthControlDeviceTypeCode (Blank) strSubmittalFlag Submittal Flag A "A" = "ADD" other options are delete or revise etc.

strTribalCode Tribal Code 000 WRAP does not report tribal code but required data field in NIF format "000" = "not used"WRAP 2002 PhII EI Report_20050722.doc B-8 Table B-8: WRAP NIF 3.0 for Fire - Emission Record

EPA NIF Field WRAP NIF Fire Field Example Value Comment strRecordType Record Type EM EM for every record strStateCountyFIPs FIPS 02110

strStateFacilityIdentifie r Fire ID AK-WF-229-1 Fire ID must be unique for every flaming fire day. Every corresponding smoldering day has the same fire ID. Must be less than 15 characters.

strEmissionUnitID EU ID (F or S) F Either F or S indicating a flaming or a smoldering fire day

strProcessID Hour ID H1 Hourly designation. No two records may have the same Fire, EU and Hour ID.

strPollutantCode Pollutant Code PM10-PRI Some pollutants like EC OC and CH4 aren't in the table POLLUTANT_CODES but are in the POLLUTANT_CATEGORIES both of which are NIF standard code tables strBlankField (Blank) strEmissionReleasePointID ER ID F H01 lngStartDate Start Date 20020424 lngEndDate End Date 20020424 intStartTime Start Time 0000 intEndTime End Time 0059 strBlankField2 (Blank) dblEmissionNumericValue Hourly Emissi ons 0.0004014 strEmissionUnitNumerator Unit TON strEmissionType Emission Type 30 sngEMReliabilityIndicator (Blank) sngFactorNumericValue Emission Factor 28.10 strFactorUnitNumerator Emission Factor Numerator LB

strFactorUnitDenominator Emission Factor Denominator TON

intMaterial Material Burned 936 Many options are available such as wood & wood/bark. "936" is vegetation which is what LADCO was reporting strMaterialIO Material Input/Output I strBlankField3 (Blank) strEmissionCalculationMethodCode (Blank) strEFReliabilityIndicator (Blank) sngRuleEffectiveness (Blank) strRuleEffectivenessMethod (Blank) strBlankField4 (Blank) strHAPEmissionsPerformanceLevel (Blank) strControlStatus (Blank) strEmissionDataLevel (Blank) strSubmittalFlag Submittal Flag A "A" = "ADD" other options are delete or revise etc.

strTribalCode Tribal Code 000 WRAP does not report tribal code but required data field in NIF format "000" = "not used"