Appendix D. 2008, 2015, and 2023 Emissions Inventories 

for the Treasure Valley Airshed
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2008, 2015, AND 2023 EMISSIONS INVENTORIES 

FOR THE TREASURE VALLEY AIRSHED

Final Report

Submitted to:

Idaho Department of Environmental Quality

1410 North Hilton

Boise, ID 83706

Submitted by:

August 31, 2010

Revised by DEQ in February 2013 to reflect updated MOVES 

and paved road dust emission estimates.

Eastern Research Group, Inc.

8950 Cal Center Drive, Suite 348

Sacramento, CA 95826

Contact: Paula Fields

916-361-6751

ENVIRON International Corporation

773 San Marin Drive, Suite 2115

Novato, CA 94998

Eastern Research Group, Inc.

10860 Gold Center Drive, Suite 275

Rancho Cordova, CA 95670
This page intentionally left blank for correct double-sided printing.
2008, 2015, AND 2023 EMISSIONS INVENTORIES FOR THE 

TREASURE VALLEY AIRSHED

Final Report

Prepared for:

Idaho Department of Environmental Quality

1410 North Hilton

Boise, ID 93706

Prepared by:

Eastern Research Group, Inc. (ERG)

10860 Gold Center Drive, Suite 275

Rancho Cordova, CA 95670

and

ENVIRON International Corporation

773 San Marin Drive, Suite 2115

Novato, CA 94998

August 31, 2010

Revised by DEQ in February 2013 to reflect updated MOVES 

and paved road dust emission estimates.
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2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

i

TABLE OF CONTENTS 

Section Page

1.0 INTRODUCTION............................................................................................................... 1-1

1.1 Background............................................................................................................. 1-1

1.2 Inventory Scope ...................................................................................................... 1-4

1.3 Report Contents ...................................................................................................... 1-6

2.0 2008 POINT SOURCE EMISSIONS INVENTORY ......................................................... 2-1

2.1 Point Source Data Collection.................................................................................. 2-1

2.2 Emission Calculation Methodologies – Annual ..................................................... 2-5

2.3 Emission Calculation Methodologies – Ozone and PM Season............................. 2-8

2.4 Emission Results by Facility................................................................................... 2-9

2.5 QA/QC Procedures ................................................................................................. 2-9

3.0 2008 AREA SOURCE EMISSIONS INVENTORY .......................................................... 3-1

3.1 Emissions Calculation Methodologies – Annual.................................................... 3-1

3.1.1 Fuel Combustion......................................................................................... 3-1

3.1.2 Residential Wood Combustion ................................................................... 3-6

3.1.3 Paved Road Dust......................................................................................... 3-8

3.1.4 Unpaved Road Dust .................................................................................. 3-10

3.1.5 Commercial Cooking................................................................................ 3-14

3.1.6 Construction.............................................................................................. 3-15

3.1.7 Architectural Surface Coatings................................................................. 3-16

3.1.8 Traffic Markings....................................................................................... 3-16

3.1.9 Industrial Surface Coating ........................................................................ 3-16

3.1.10 Degreasing ................................................................................................ 3-18

3.1.11 Other Per Employee Emission Factor Source Categories......................... 3-19

3.1.12 Bakeries and Consumer Solvents.............................................................. 3-21

3.1.13 Dry Cleaning............................................................................................. 3-22

3.1.14 Asphalt Application .................................................................................. 3-22

3.1.15 Pesticide Application ................................................................................ 3-24

3.1.16 Gasoline Distribution................................................................................ 3-26

3.1.17 Wastewater Treatment .............................................................................. 3-26

3.1.18 Landfills.................................................................................................... 3-27

3.1.19 Open Burning (Yard Waste and Household Waste)................................. 3-29

3.1.20 Agricultural Tilling and Harvesting.......................................................... 3-31

3.1.21 Agricultural Burning – Fields................................................................... 3-31

3.1.22 Agricultural Burning – Irrigation Ditches................................................. 3-32

3.1.23 Beef Cattle Feedlots.................................................................................. 3-33

3.1.24 Other Fires ................................................................................................ 3-34

3.1.25 Windblown Dust....................................................................................... 3-35

3.1.26 Ammonia Emissions................................................................................. 3-50

3.2 Emissions Calculation Methodologies – Ozone and PM Season ......................... 3-68

3.2.1 Fuel Combustion....................................................................................... 3-68

3.2.2 Residential Wood Combustion ................................................................. 3-70

3.2.3 Paved Road Dust....................................................................................... 3-70
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3.2.4 Unpaved Road Dust .................................................................................. 3-70

3.2.5 Commercial Cooking................................................................................ 3-71

3.2.6 Construction.............................................................................................. 3-71

3.2.7 Architectural Surface Coatings................................................................. 3-72

3.2.8 Traffic Markings....................................................................................... 3-72

3.2.9 Industrial Surface Coating ........................................................................ 3-72

3.2.10 Degreasing ................................................................................................ 3-73

3.2.11 Other Per Employee Emission Factor Source Categories......................... 3-73

3.2.12 ........................................................................... Bakeries and Consumer Solvents 3-74

3.2.13 Dry Cleaning.............................................................................................. 3-74

3.2.14 Asphalt Application .................................................................................. 3-74

3.2.15 Pesticide Application ................................................................................ 3-74

3.2.16 Gasoline Distribution................................................................................ 3-75

3.2.17 Wastewater Treatment .............................................................................. 3-75

3.2.18 Landfills.................................................................................................... 3-75

3.2.19 Open Burning (Yard Waste and Household Waste)................................. 3-75

3.2.20 Agricultural Tilling and Harvesting.......................................................... 3-75

3.2.21 Agricultural Burning – Fields.................................................................... 3-76

3.2.22 Agricultural Burning – Irrigation Ditches.................................................. 3-76

3.2.23 Beef Cattle Feedlots.................................................................................. 3-76

3.2.24 Other Fires ................................................................................................ 3-76

3.2.25 Windblown Dust....................................................................................... 3-76

3.2.26 Ammonia Emissions................................................................................. 3-77

3.3 Emission Results................................................................................................... 3-77

3.4 QA/QC Procedures ............................................................................................... 3-81

4.0 2008 ON-ROAD MOTOR VEHICLE SOURCE EMISSIONS INVENTORIES.............. 4-1

5.0 2008 NONROAD MOBILE SOURCE EMISSIONS INVENTORY................................. 5-3

5.1 Emission Calculation Methodologies – Annual ..................................................... 5-3

5.1.1 Nonroad Equipment.................................................................................... 5-3

5.1.2 Aircraft...................................................................................................... 5-10

5.1.3 Locomotives.............................................................................................. 5-12

5.2 Emission Calculation Methodologies – Ozone and PM Season........................... 5-23

5.2.1 Nonroad Equipment.................................................................................. 5-23

5.2.2 Aircraft...................................................................................................... 5-24

5.2.3 Locomotives................................................................................................. 5-25

5.3 QA/QC procedures................................................................................................ 5-26

6.0 2008 BIOGENIC SOURCE EMISSIONS INVENTORY.................................................. 6-1

6.1 Emissions Calculation Methodologies – Annual.................................................... 6-1

6.2 Emissions Calculation Methodologies – Ozone and PM Season ........................... 6-1

6.3 Emission Results..................................................................................................... 6-1

7.0 2015 AND 2023 PROJECTED EMISSIONS INVENTORIES.......................................... 7-1

7.1 Development of 2015 and 2023 Projection Factors................................................ 7-1

7.1.1 Point Sources .............................................................................................. 7-1

7.1.2 Area Sources............................................................................................... 7-2

7.1.2.1 Fuel Combustion............................................................................ 7-2

7.1.2.2 Population ...................................................................................... 7-3
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

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7.1.2.3 Industrial Output Projections......................................................... 7-3

7.1.2.4 Long-Term Agricultural Averages ................................................ 7-4

7.1.2.5 Vehicle Miles Travelled (VMT).................................................... 7-4

7.1.2.6 No Growth ..................................................................................... 7-5

7.1.2.7 Ammonia Sources.......................................................................... 7-5

7.1.2.8 Road Dust....................................................................................... 7-5

7.1.3 On-Road Motor Vehicles............................................................................ 7-6

7.1.4 Nonroad Mobile Sources ............................................................................ 7-9

7.1.4.1 Nonroad Equipment .................................................................... 7-10

7.1.4.2 Aircraft ........................................................................................ 7-10

7.1.4.3 Locomotives................................................................................ 7-11

7.1.5 Biogenic Sources ...................................................................................... 7-12

7.2 2015, 2023, and 2050 Inventory Summaries ........................................................ 7-13

8.0 EMISSIONS INVENTORY DATA FORMATTING......................................................... 8-1

9.0 REFERENCES .................................................................................................................... 9-1

APPENDIX A LISTING OF PBR AND UNPERMITTED FACILITIES

APPENDIX B LETTERS TO TIER 1 AND 2 FACILITIES; PBR AND UNPERMITTED 

FACILITIES

APPENDIX C AREA SOURCE SURVEYS (FUEL DEALER AND DISTRIBUTOR 

SURVEY, DRY CLEANING SURVEY, WASTEWATER TREATMENT 

SURVEY, AND LANDFILL SURVEY)

APPENDIX D AURORA RESIDENTIAL WOOD COMBUSTION SURVEY REPORT

APPENDIX E DEQ CONCEPT-MV TECHNICAL MEMORANDUM

APPENDIX F BIOGENICS TECHNICAL MEMORANDUM

APPENDIX G DETAILED AREA SOURCE EMISSION INVENTORY SUMMARIES

Tables Page

Table 1-1. Source Types and Categories Included in the Treasure Valley Emissions Inventories

.............................................................................................................................. 1-5

Table 2-1. Permitted Point Sources in the Treasure Valley........................................................ 2-3

Table 2-2. Facilities Operating Under Permit by Rule in the Treasure Valley Air Shed ........... 2-4

Table 2-3. Unpermitted Facilities that Exceeded Point Source Thresholds in 2008 Emissions. 2-8

Table 2-4. 2008 Annual Point Source Emissions (Tons/Year)................................................. 2-10

Table 2-5. 2008 Ozone Season Point Source Emissions (Tons/Day)....................................... 2-13

Table 2-6. 2008 PM Season Point Source Emissions (Tons/Day)............................................ 2-16

Table 3-1. Area Source Matrix ................................................................................................... 3-2

Table 3-2. Elmore County Paved Road Parameters..................................................................... 3-9

Table 3-3. Elmore County Silt Loading Estimates...................................................................... 3-9

Table 3-4. Elmore County Days with at Least 0.01 Inches of Rain ......................................... 3-10

Table 3-5. 2008 Annual Paved Road Dust Emission Estimates............................................... 3-10

Table 3-6. 2008 Unpaved Road Dust Activity Data and Sources............................................. 3-12

Table 3-7. Unpaved Road Dust Precipitation Adjustments...................................................... 3-13

Table 3-8. Elmore County Unpaved Road Surface Silt Content .............................................. 3-14

Table 3-9. Unpaved Emissions Estimation Parameters............................................................ 3-14
2008, 2015, 2023 Treasure Valley Emissions Inventories

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Table 3-10. 2008 Annual Unpaved Road Dust Emission Estimates ........................................ 3-14

Table 3-11. NAICS Code Assignments for Industrial Surface Coating Subcategories............ 3-17

Table 3-12. NAICS Code Assignments for Degreasing ........................................................... 3-18

Table 3-13. NAICS Code Assignments for Autobody Refinishing, Industrial Refrigeration/Cold 

Storage, and Graphic Arts Categories................................................................ 3-20

Table 3-14. Fire Code Assignments for the Structural Fire and Vehicle Fire Source Categories 3-

34

Table 3-15. DEQ and CTIC Crop Type Mapping and Descriptions ......................................... 3-41

Table 3-16. Idaho Crop Canopy Cover by Crop Type and Julian Day Since Planting (%) ..... 3-42

Table 3-17. Idaho Planting and Harvesting Dates (Julian Day) and Crop Canopy Crop Type 3-43

Table 3-18. Soil Texture and Soil Group Codes....................................................................... 3-47

Table 3-19. Surface Characteristics by Dust Code and Land Use Category ............................. 3-48

Table 3-20. 2008 Annual Windblown Fugitive PM Dust Emissions for Ada, Canyon and Elmore 

Counties (Tons/Year)......................................................................................... 3-50

Table 3-21. 2008 Annual County-Level Livestock Head Counts............................................. 3-53

Table 3-22. Ammonia Emission Factors for Livestock ............................................................ 3-53

Table 3-23. Monthly Livestock Allocation Factors.................................................................. 3-54

Table 3-24. 2008 Annual Fertilizer Application Data by Type and County (kg/year)............. 3-56

Table 3-25. Ammonia Emissions Factors for Fertilizer Application........................................ 3-57

Table 3-26. Ammonia Emission Factors for Native Soils........................................................ 3-58

Table 3-27. 2008 County-Level Population Estimates............................................................. 3-59

Table 3-28. Ammonia Emission Factors for Domestic Ammonia Sources.............................. 3-60

Table 3-29. Ammonia Emission Factors for Wild Animal Ammonia Sources........................ 3-61

Table 3-30. CDL Classifications and NH3 Model Cross-References....................................... 3-62

Table 3-31. Land Use Summary by Category and County for the 4-Km Modeling Domain 

(Acres)................................................................................................................ 3-65

Table 3-32. Land Use/Surrogate Cross-Reference ................................................................... 3-67

Table 3-33. Source Category/Surrogate Cross-Reference ........................................................ 3-67

Table 3-34. 2008 Annual Ammonia Emissions for Ada, Canyon, and Elmore Counties by 

Source Category (Tons/Year) ............................................................................ 3-69

Table 3-35. 2008 Seasonal Paved Road Dust Emission Estimates........................................... 3-71

Table 3-36. 2008 Seasonal Unpaved Road Dust Emission Estimates...................................... 3-71

Table 3-37. Temporal Allocation Profile Assignment for Architectural Surface Coating ....... 3-72

Table 3-38. Temporal Allocation Profile Assignments for Industrial Surface Coating 

Subcategories..................................................................................................... 3-72

Table 3-39. Temporal Allocation Profile Assignment for Degreasing..................................... 3-73

Table 3-40. Temporal Allocation Profile Assignment for Graphic Arts.................................. 3-73

Table 3-41. Temporal Allocation Profile Assignment for Dry Cleaning ................................. 3-74

Table 3-42. Summarized 2008 Annual Area Source Emissions – All Counties ...................... 3-78

Table 3-43. Summarized 2008 Annual Area Source Emissions – Ada County ....................... 3-79

Table 3-44. Summarized 2008 Annual Area Source Emissions – Canyon County.................. 3-80

Table 3-45. Summarized 2008 Annual Area Source Emissions – Elmore County .................. 3-81

Table 4-1. 2008 On-road Emissions Summary (Tons/Year and Tons/Day)a............................. 4-2

Table 5-1. 2008 Pleasure Craft and Recreational Equipment Populations................................. 5-4

Table 5-2. NONROAD Model Default and Revised Agricultural Equipment Populations....... 5-5

Table 5-3. Lawn and Garden Equipment Temporal Profile Groupings...................................... 5-8
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Table 5-4. 2008 Gasoline RVP (psi) by Season ......................................................................... 5-9

Table 5-5. 2008 Annual Nonroad Equipment Emissions by County........................................ 5-10

Table 5-6. 2008 Annual Nonroad Equipment Emissions by Equipment Type (Ada, Canyon, and 

Elmore Counties Combined).............................................................................. 5-10

Table 5-7. 2008 Aircraft Associated Emissions by Airport (Tons/Year)................................. 5-13

Table 5-8. FRA Rail Link Definitions...................................................................................... 5-15

Table 5-9. Idaho Northern Pacific Railroad Activity Data ....................................................... 5-16

Table 5-10. Locomotive Emission Standards for Line-haul (Duty Cycle) Engines................. 5-18

Table 5-11. Locomotive Emission Standards for Switching (Duty Cycle) Engines ................ 5-18

Table 5-12. Locomotive Emission Factors for Calendar Years 1999 and Earlier.................... 5-19

Table 5-13. Average Line-Haul Locomotive Emission Factors............................................... 5-19

Table 5-14. Fuel Efficiency by Railroad................................................................................... 5-19

Table 5-15. Class 1 Railroad Emission Factors for 2008 ......................................................... 5-19

Table 5-16. 2008 Line-haul Locomotive Emissions (Tons/Year) ............................................ 5-20

Table 5-17. Switching Locomotive Activity Data for the Nampa Yard................................... 5-21

Table 5-18. Switching Locomotive Emission Factors.............................................................. 5-21

Table 5-19. Estimated Switching Locomotive Emissions in 2008........................................... 5-22

Table 5-20. 2008 Annual Locomotive Emissions by Source Category.................................... 5-22

Table 5-21. 2008 Seasonal Nonroad Equipment Emissions by County ................................... 5-23

Table 5-22. 2008 Seasonal Nonroad Equipment Emissions by Equipment Type (Ada, Canyon, 

and Elmore Counties Combined)....................................................................... 5-24

Table 5-23. Fraction of Aircraft Activity Occurring in the Ozone and PM Seasons................ 5-25

Table 5-24. 2008 Ozone and PM Season Daily Locomotive Emission Estimates by Source 

Category............................................................................................................. 5-25

Table 6-1. Annual, Ozone Season, and PM Season Biogenic Emissions................................... 6-2

Table 7-1. 2015 and 2023 I/M Inputs by County: Anti-Tampering Program Parametersa....... 7-7

Table 7-2. 2015, 2023, and 2030 MOBILE6 Inputs by County: I/M Program Parameters a.... 7-8

Table 7-3. Base Year Aircraft LTO Activity Data and Future Year Projection Factors .......... 7-11

Table 7-4. Union Pacific Historic Fuel Consumption ............................................................... 7-12

Table 7-5. 2008 County-Level Annual Emissions Summarized by Source Type .................... 7-14

Table 7-6. 2015 County-Level Annual Emissions Summarized by Source Type .................... 7-15

Table 7-7. 2023 County-Level Annual Emissions Summarized by Source Type .................... 7-16

Table 7-8. 2050 County-Level Annual On-Road Emissions for Ada County ........................... 7-16

Table 7-9. 2008 County-Level Ozone Season Emissions Summarized by Source Type ......... 7-17

Table 7-10. 2015 County-Level Ozone Season Emissions Summarized by Source Type ....... 7-18

Table 7-11. 2023 County-Level Ozone Season Emissions Summarized by Source Type ....... 7-19

Table 7-12. 2050 Ozone Season On-Road Emissions for Ada County..................................... 7-20

Table 7-13. 2008 County-Level PM Season Emissions Summarized by Source Type............ 7-20

Table 7-14. 2015 County-Level PM Season Emissions Summarized by Source Type............ 7-21

Table 7-15. 2023 County-Level PM Season Emissions Summarized by Source Type............ 7-22

Table 7-16. 2050 County-Level PM Season On-Road Emissions for Ada County................... 7-22
2008, 2015, 2023 Treasure Valley Emissions Inventories

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Figures Page

Figure 3-1. DEQ 4-km Modeling Domain for Windblown Dust Emissions Development...... 3-36

Figure 3-2. Merged Soil Texture Data from the SSURGO and STATSGO Databases ........... 3-38

Figure 3-3. Land Use/Land Cover Data Used for the DEQ Windblown Dust PM Emissions 

Inventory Development ..................................................................................... 3-39

Figure 3-4. Comparison Between the Marticorena et al. (1997) Modeled Relationship of 

Threshold Friction Velocity and Aerodynamic Roughness Length and Wind 

Tunnel Data from Gillette et al. (1980, 1982), Gillette (1988) and Nickling and 

Gillies (1989) ..................................................................................................... 3-46

Figure 3-5. The Emission Flux as a Function of Friction Velocity Predicted by the Alfaro and 

Gomes (2001) Model Constrained by the Four Soil Geometric Mean Diameter 

Classes of Alfaro et al. (2004) ........................................................................... 3-47

Figure 3-6. DEQ 4-km Modeling Domain for Ammonia Emissions Development................. 3-51

Figure 3-7. Land Use/Land Cover Data Used for the DEQ Ammonia Emissions Inventory 

Development...................................................................................................... 3-64

Figure 3-8. Mean Soil pH for the DEQ Modeling Domain from the STATSGO Database..... 3-65

Figure 5-1. Local Off-Road Agricultural Equipment Monthly Temporal Profile ...................... 5-6

Figure 5-2. Local Construction Equipment Monthly Temporal Profile ..................................... 5-7

Figure 5-3. Local Lawn-, Soil-, and Leaf-Related Lawn and Garden Equipment Monthly 

Temporal Profiles................................................................................................. 5-8

Figure 5-4. Local Wood-Related Lawn and Garden Equipment Monthly Temporal Profile ..... 5-9

Figure 5-5. 2008 Aircraft Associated Emissions Contributions............................................... 5-14

Figure 5-6. FRA Line-Haul Freight Density............................................................................. 5-16
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vii

ACRONYMS

μg/m3 microgram per cubic meter

μm micrometers

AAR Association of American Railroads

ADT average daily traffic

AEO Annual Energy Outlook

AFB Air Force Base

AFS Air Facility System

ALVW adjusted loaded vehicle weight

AP-42 Compilation of Air Pollutant Emission Factors

APU auxiliary power units

ASCII American Standard Code for Information Interchange

ATADS Air Traffic Activity Data System

Atm standard atmosphere, a unit of pressure

ATR automatic traffic recorder

BEIS Biogenic Emission Inventory System

BLS Bureau of Labor Statistics

CARB California Air Resources Board

CDL cropland data layer

CH4 methane

CMAQ Congestion Mitigation and Air Quality

CMU Carnegie Mellon University

CO carbon monoxide

CO2 carbon dioxide

COMPASS Community Planning Association of Southwest Idaho

CONCEPT MV Consolidated Community Emissions Processing Tool On-Road Motor Vehicle Model

CTIC Conservation Technology Information Center

DEQ Department of Environmental Quality

DQOs Data Quality Objectives

EDMS Emissions and Dispersion Modeling System

EEA European Environment Agency
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EIA Energy Information Administration

EIIP Emission Inventory Improvement Program

ERG Eastern Research Group, Inc.

ETBE ethyl tert-butyl ether

FAA Federal Aviation Administration

FHWA Federal Highway Administration

FIPS Federal Information Processing Standards

FRA Federal Railroad Administration

FRS Facility Registry System

ft3cubic feet

g/l grams per liter

GIS Geographic Information System

Gmol grams per mole

GSE ground support equipment

GTM gross ton-mile

GVWR gross vehicle weight rating

HC hydrocarbons

HDDV Heavy-Duty Diesel Vehicle

HDGV Heavy-Duty Gasoline Vehicle

HP horsepower

HPMS Highway Performance Monitoring System

I/M inspection and maintenance

ICAO International Civil Aviation Organization

ID identification number

IDPR Idaho Department of Parks and Recreation

IDWR Idaho Department of Water Resources

IFIRS Idaho Fire Incident Reporting System

INPR Idaho Northern Pacific Railroad

IPM Integrated Pest Management

IPP Inventory Preparation Plan

ISDA Idaho State Department of Agriculture
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ITD Idaho transportation department

km kilometers

lbs pounds

LDDT Light-Duty Diesel Truck

LDDV Light-Duty Diesel Vehicle

LDGT Light-Duty Gasoline Truck

LDGV Light-Duty Gasoline Vehicle

LPG liquefied petroleum gas

LTOs landing-takeoff cycles

LULC land use-land cover

MC Motorcycles

MEGAN Model of Emissions of Gases and Aerosol from Nature

Mg Megagrams

MM5 Fifth-Generation NCAR/Penn State Mesoscale Model

mmHG millimeters of mercury

MMscf million standard cubic feet

MOVES MOtor Vehicle Emission Simulator

mph miles per hour

mps meters per second

MSDS Material Safety Data Sheets

MTBE methyl tert-butyl ether

NAAQS National Ambient Air Quality Standards

NAICS North American Industry Classification System

NASS National Agricultural Statistics Service

NEI National Emissions Inventory

NH3 ammonia

NO nitric oxide

NOx nitrogen oxides

O3 ozone

ORIS Office of Regulatory Information Systems

OSD ozone season daily
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PAN Pesticide Action Network

PBR permit by rule

PM particulate matter

PM10 particulate matter with an aerodynamic diameter of 10 micrometers or less

PM2.5 particulate matter with an aerodynamic diameter of 2.5 micrometers or less

POSST Point Source Survey Tool

ppm parts per million

ppmv parts per million by volume

psi pounds per square inch

PTC Permit to construct

QA quality assurance

QAP Quality Assurance Plan

QC quality control

RVP Reid vapor pressure

RWC residential wood combustion

SCC Source Classification Code

scf standard cubic feet

SIC Source Industrial Classification

SIP State Implementation Plan

SMOKE Sparse Matrix Operator Kernel Emissions

SO2 sulfur dioxide

SSURGO Soil Survey Geographic Database

STATSGO State Soil Geographic Database

TAF Terminal Area Forecast

TAME tert-amyl methyl ether

TAZ Transportation Analysis Zone

TDM Transportation Demand Model

TIMs Time-in modes

TPD tons per day

TPY tons per year

TRI Toxic Release Inventory
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TVRDS Treasure Valley Road Dust Study

U.S. EPA United States Environmental Protection Agency

UP Union Pacific

USDA United States Department of Agriculture

USGS United States Geological Survey

UW University of Washington

VIN vehicle identification number

VKT vehicle kilometers travelled

VMT vehicle miles travelled

VOC volatile organic compounds

VTRIS Vehicle Travel Information System

WRAP Western Regional Air Partnership

WRCC Western Regional Climate Center

WRF Weather Research and Forecasting

WSFO National Weather Service Forecast Office

WWTPs wastewater treatment plants
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1.0 INTRODUCTION

This report was originally prepared by the team of Eastern Research Group, Inc. (ERG)

and ENVIRON International Corporation (ENVIRON), with assistance from Aurora Research 

Group (Aurora), according to the scope of Idaho Department of Environmental Quality (DEQ) 

Contract C774, dated March 26, 2009. 

Between completion of the ERG/Environ emissions inventory final report in 2010 and 

application of the emissions inventories in the attainment demonstration for the Northern Ada 

County PM10 Limited Maintenance Plan Ten-Year Update, four events dictated that updates 

were necessary:

1. The Motor Vehicle Emission Simulator (MOVES) model became a requirement for all 

state implementation plans (SIPs) and conformity tests to be based on SIPs (EPA, 

2011a); 

2. The methodology originally used for paved road dust emission estimates was found to 

be flawed; 

3. Small errors in ozone season distillate combustion sulfur dioxide (SO2) emissions 

were discovered; and,

4. On-road and paved road emission projections out to 2050 were added to support 

conformity evaluations of the Community Planning Association of Southwest Idaho

(COMPASS) long-range transportation plans with horizons out to 2050. 

As a result of the first two events, DEQ updated the on-road and paved road dust emissions in 

2012. The development of updated on-road (MOVES) and paved road dust emission estimates 

are both described in “Development of the Base- and Future-Year Mobile Source Emissions 

Inventories for the Treasure Valley, Idaho” (DEQ, 2012), included as Appendix E of the 

Northern Ada County PM10 Limited Maintenance Plan Ten-Year Update. For clarity and ease of 

use, this report was also updated (all revised text and values are shown in italic to clearly 

distinguish the DEQ updates from the original of ERG/Environ report). 

1.1 Background

The Treasure Valley Airshed consists of Ada and Canyon counties in total; portions of 

Elmore, Boise, Gem, Payette, and Owyhee counties in Idaho; plus, a portion of Malheur County, 
2008, 2015, 2023 Treasure Valley Emissions Inventories

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1-2

Oregon (see report cover). This airshed boundary was determined using population, model runs, 

seasonal episodic events for particulate matter (PM) with an aerodynamic diameter of 2.5 μm or 

less (PM2.5) and ozone (O3), and meteorological data such as average mixing heights. Activity in 

all of the counties contributes to the air quality conditions, as emissions mix within and are 

essentially trapped in the roughly 60-mile by 100-mile bathtub-shaped Treasure Valley. The 

terrain includes mountains northwest-north-northeast that rise to more than 7,000 feet (i.e., the

Boise Front); a nearly closed end of the valley to the southeast where a rise off the Boise Front 

sometimes keeps pollutants from being transported away; mountains to the south-southwest rise 

to over 8,000 feet (i.e., the Owyhee Mountains); and the valley is open to the west-northwest.

The Treasure Valley, and especially Ada County, has a history of problems with PM with 

an aerodynamic diameter of 10 micrometers (μm) or less (PM10), and carbon monoxide (CO). 

Local weather patterns that occur in winter months, terrain, and human activities contributed to 

episodes of particulate build-up. Northern Ada County was designated as in nonattainment of 

the PM10 National Ambient Air Quality Standard (NAAQS) in 1986. Violations of the PM10

NAAQS have not occurred since 1991 and northern Ada County remains in maintenance. 

The CO problem stems from automobile exhaust and residential wood heating during 

winter inversions. Exceedance of the 8-hour CO NAAQS has not occurred since January 1991 

and the area remains in maintenance since that time.

Currently, the Treasure Valley is close to violating the O3 NAAQS. Air quality 

monitoring data indicate the area has equaled the 0.075 parts per million (ppm) NAAQS when 

averaging the fourth-highest readings from 2006, 2007, and 2008. Sunny summer weather, air 

stagnation, increased vehicle miles traveled from rapid population growth, industrial activity, and 

the terrain all contribute to high O3 levels. The occasional nearby wildfire and transport from 

other urban areas in the region also contribute to high levels of O3 in the valley.

After approaching the 35 microgram per cubic meter (μg/m3) 24-hour NAAQS for PM2.5, 

favorable meteorological conditions in the Treasure Valley during the winters of 2006/2007 and 

2007/2008 have allowed the PM2.5 design value to decrease. Lower frequency and shorter 

duration inversion conditions have occurred as synoptic weather systems passed through 

Southwestern Idaho with more regularity. Although the Treasure Valley is not in danger of 
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violating the annual PM2.5 standard in the short term, interest remains in obtaining accurate PM2.5

emissions data for use in modeling and air quality studies should the typical winter inversions 

return. 

Planning efforts and special projects have identified certain contributors to the O3, PM10, 

and PM2.5 issues in the Treasure Valley, as well as a need for more recent SIP-level emissions 

inventory data. DEQ has begun an extensive effort to reduce O3 levels in the valley, as well as 

ensuring PM2.5 problems remain in check even if stagnant winter weather patterns return. To be 

fully able to control certain pollutant contributions to the airshed, DEQ must first have the 

emissions inventory data to be able to determine controls and the human behavioral changes 

necessary to possibly keep the area from going into nonattainment for one or both of these 

pollutants. 

Idaho DEQ needed an accurate emissions inventory of O3 precursors, and primary PM10

and PM2.5 and their precursors for the Treasure Valley Airshed. This emissions inventory must 

be of sufficient quality and detail to: 

 Support development of O3, PM10, and PM2.5 control strategies; 

 Support photochemical grid modeling for control strategy development; and

 If necessary, in the event of a non-attainment designation, to fully meet U.S. 

Environmental Protection Agency (U.S. EPA) expectations and guidance as part of an 

O3, PM10, or PM2.5 non-attainment area SIP and maintenance plan submittal.

The Treasure Valley emissions inventory project was funded through the Congestion 

Mitigation and Air Quality (CMAQ) grant program, which is distributed via the Idaho 

Transportation Department (ITD). DEQ is the lead agency on the project, working cooperatively 

with ITD; the local Metropolitan Planning Organization, COMPASS; and the contractor team of 

ERG, ENVIRON, and Aurora. 

The emissions inventory was developed according to Emission Inventory Improvement 

Program (EIIP) Level II requirements (EIIP, 1997a).
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1.2 Inventory Scope

The scope of the Treasure Valley emissions inventory includes these characteristics:

 Pollutants: Emissions were estimated for the following pollutants:

– Ozone precursors: nitrogen oxides (NOx), volatile organic compounds (VOC), and CO;

– Primary PM10 and PM2.5; and

– Precursors of PM10 and PM2.5: NOx, sulfur dioxide (SOx), VOC, and ammonia (NH3).

 Time Frame and Temporal Resolution: The base year inventory was developed is for 

calendar year 2008. Projections were developed for years 2015 and 2023. In addition 

to annual inventories, estimates were also developed for ozone season daily (OSD) 

and PM10/PM2.5 (PM) season daily emissions. The ozone season is April 1 through 

October 31, and the PM season is November 1 through February 28.

 Sources: The inventories included estimates of emissions from industrial point 

sources, area sources, and nonroad mobile sources. Also, ENVIRON estimated linklevel on-road motor vehicle emissions for the 15-day period of February 1-15, 2008. 

DEQ then used the CONCEPT-MV system and identical methodologies, with 

assistance and peer review by ENVIRON, to estimate on-road emissions for each 

season during all three inventory years (i.e., 2008, 2015, and 2023) using the 

MOBILE6.2 model. In 2012 DEQ recomputed the 2008, 2015, and 2023 on-road 

emissions inventories using the MOVES2010a model and EPA’s AP-42 Paved Road 

Dust method. Finally, DEQ has also completed the on-road modeling for 2050 to 

support the Northern Ada County PM10 Limited Maintenance Plan Ten-Year Update

and subsequent conformity determinations in the long-range transportation planning 

cycle that must be based on the plan.

 Geographic Domain and Resolution: The inventories were estimated for the subject 

pollutants and sources located entirely within Ada, Canyon, and Elmore counties, 

Idaho. For the point sources, specific location coordinates will be provided. For area 

and nonroad mobile sources, emissions will be provided at the county level. 

Table 1-1 lists the source types and pollutants included in the Treasure Valley emissions 

inventory.

The contract scope includes the following tasks: 

 Task 1: Work Plan for the Development of the Emissions Inventory

 Task 2: Inventory Preparation Plan and Quality Assurance Plan (IPP/QAP)

 Task 3: 2008 Point Sources Emissions Inventory

 Task 4: 2008 Area Sources Emissions Inventory
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 Task 5: 2008 Nonroad Mobile Sources Emissions Inventory

 Task 6: Emissions Inventory Document

 Task 7: Emissions Inventory Data Spreadsheets

 Task 8: Peer Review Biogenic and On-Road Motor Vehicle Emissions

Table 1-1. Source Types and Categories Included in the Treasure Valley 

Emissions Inventories

Source Type Source Category Pollutants

Point Industrial Facilities (Various)a NOx, SO2, VOC, CO, PM10, PM2.5, NH3

Area Industrial Fuel Combustion (distillate, LPG, natural 

gas)

NOx, SO2, VOC, CO, PM10, PM2.5, NH3

Commercial/ Institutional Fuel Combustion

(distillate, kerosene, LPG, natural gas)

NOx, SO2, VOC, CO, PM10, PM2.5, NH3

Residential Fuel Combustion (distillate, kerosene, 

LPG, natural gas)

NOx, SO2, VOC, CO, PM10, PM2.5, NH3

Residential Wood Combustion (fireplaces, 

woodstoves, fireplaces with inserts, pellet stoves)

NOx, SO2, VOC, CO, PM10, PM2.5, NH3

Paved Road Dust PM10, PM2.5

Unpaved Road Dust PM10, PM2.5

Commercial Cooking NOx, SO2, VOC, CO, PM10, PM2.5, NH3

Construction Dust PM10, PM2.5

Architectural Surface Coating VOC

Traffic Markings VOC

Autobody Refinishing VOC

Industrial Surface Coating VOC

Degreasing VOC

Graphic Arts VOC

Industrial Refrigeration/Cold Storage NH3

Consumer Solvent Use VOC

Bakeries VOC

Dry Cleaning VOC

Asphalt Application VOC

Agricultural Pesticides VOC

Gasoline Transport and Distribution VOC

Wastewater Treatment Plant VOC

Landfills VOC

Open Burning (yard waste, household waste) NOx, SO2, VOC, CO, PM10, PM2.5, NH3

Agricultural Tilling PM10, PM2.5

Agricultural Harvesting PM10, PM2.5

Agricultural Burning (fields, irrigation ditches) NOx, SO2, VOC, CO, PM10, PM2.5, NH3

Beef Cattle Feedlots VOC, PM10, PM2.5

Structural Fires NOx, SO2, VOC, CO, PM10, PM2.5, NH3

Vehicle Fires NOx, SO2, VOC, CO, PM10, PM2.5, NH3

Windblown Dust PM10, PM2.5

Livestock Ammonia NH3

Agricultural Fertilizer NH3

Domestic Ammonia NH3

Wild Animals NH3

Native soils NH3

Nonroad Nonroad Equipment NOx, SO2, VOC, CO, PM10, PM2.5, NH3
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Source Type Source Category Pollutants

Mobile Aircraft NOx, SO2, VOC, CO, PM10, PM2.5, NH3

Locomotives NOx, SO2, VOC, CO, PM10, PM2.5, NH3

On-Road 

Motor Vehicles

 Vehicle Types (8)

 Roadway Types

NOx, SO2, VOC, CO, PM10, PM2.5, NH3

Biogenics To be provided by DEQ NOx, VOC

a

Industrial point sources include facilities that emit pollutant quantities above the following amounts: 5 tons per year (TPY) PM10, 

PM2.5, SO2, or NH3; 10 TPY VOC; 25 TPY NOx or CO. Sources with annual emissions below these amounts will be included in 

the area sources inventory.

 Task 9: Provide all Data to DEQ

 Task 10: Emissions Inventory Projections (2015 and 2023)

 Task 11: CONCEPT MV Motor Vehicle Emissions Modeling

All work under all tasks has been completed. The methods used and results achieved are 

documented in this final report. All data files (e.g., emissions inventory calculation spreadsheets, 

model-ready formatted files, etc.) are being submitted along with this final report. 

1.3 Report Contents

The remainder of this report is organized as follows:

 Section 2.0 presents the methodologies and results for the 2008 point source 

inventory;

 Section 3.0 provides the methodologies and results for the 2008 area source 

inventory;

 Section 4.0 presents review and results for the 2008 on-road motor vehicle inventory; 

 Section 5.0 provides the methodologies and results for the 2008 nonroad mobile 

source inventory; 

 Section 6.0 provides the review and results for the 2008 biogenic inventory;

 Section 7.0 outlines the methodologies used to project the 2008 point, area, on-road 

motor vehicle, nonroad mobile, and biogenic inventories to the future years of 2015 

and 2023;

 Section 8.0 describes the emissions inventory data formatting that was conducted;

 Section 9.0 lists all of the references that were used in the development of the overall 

emissions inventory.

The report appendices contain various supplemental information, including the following:

 Appendix A – Listing of PBR and Unpermitted Facilities
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 Appendix B – Letters to Tier 1 and 2 Facilities; PBR and Unpermitted Facilities

 Appendix C – Area Source Surveys (Fuel Dealer and Distributor Survey, Dry 

Cleaning Survey, Wastewater Treatment Survey, and Landfill Survey)

 Appendix D – Aurora Residential Wood Combustion Survey Report

 Appendix E – DEQ CONCEPT-MV Technical Memorandum

 Appendix F – Biogenics Technical Memorandum

 Appendix G – Detailed Area Source Emission Inventory Summaries
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2.0 2008 POINT SOURCE EMISSIONS INVENTORY

2.1 Point Source Data Collection

Early in the development of the point source inventory, it was decided that the industrial 

point source facilities would be divided into two categories: permitted sources and unpermitted 

sources. The permitted sources include facilities that operate under a current Tier 1 permit (i.e., 

Title V) or a Tier 2 (including permit to construct [PTC]) permits. The unpermitted sources 

include facilities that were operating under a permit by rule (PBR) (i.e., portable sand and gravel 

equipment and dairies), as well as the possible universe of industrial facilities that do not possess 

current DEQ air permits. DEQ provided a list of the Tier 1 and Tier 2 permitted facilities and the 

PBR facilities, including facility and contact name and address. 

For the Treasure Valley emissions inventory, point sources are defined to include 

industrial facilities emitting greater than one of the following thresholds:

 5 tons per year (tpy) of PM10, PM2.5, SOx, or NH3;

 10 tpy of VOC; or

 25 tpy of NOx or CO.

Sources with annual emissions below these levels will be included in the area sources inventory.

The procedure described below was used to develop a master database of potential point 

source facilities located within the Treasure Valley Airshed (i.e., Ada, Canyon, and Elmore 

counties) in order to include full contact information needed for mailing point source survey 

letters. The data sources used were DEQ’s Tier 1, Tier 2/PTC, and PBR lists; 2002 and 2005 

National Emissions Inventory (NEI); the U.S. EPA’s Facility Registry System (FRS); Idaho 

Secretary of State Business Listing; and 2005-2007 Toxic Release Inventories (TRI). The 

procedure steps included the following:

 The starting point was the DEQ’s Tier 1 and Tier 2/PTC permit lists (109 facilities). 

Information for these facilities included contact person, facility name(s), and address. 

A unique facility identification number (ID) was assigned. This information was 

given the highest priority in the merged database.

 Using the 2002 and 2005 NEI, facility information was merged with the above 

permits list (42 facilities). For overlapping facilities, IDs were updated. Non-
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2-2

overlapping facilities were appended into the master database and a unique Facility 

ID was assigned. Information included: facility name(s), address information, 

SIC/NAICS/Industry codes and descriptors, location coordinates, and other facility 

identifiers (i.e., NEI Site ID, ORIS Facility Code, TRI ID and FRS ID). This 

information was assigned the second highest priority.

 Using DEQ’s listing of facilities with PBRs (i.e., portable rock crushers and dairies), 

facility information was added to database. Information for these facilities included

contact person, facility name(s), and address. Also, these facilities were assigned an 

SIC of either 1442 (Construction Sand and Gravel) or 0241 (Dairy Farms). A unique 

Facility ID was assigned, along with a POSST User Name and Password. This 

information was assigned the third highest priority.

 The next data source used for the merge was from U.S. EPA’s FRS. For Ada, 

Canyon, and Elmore counties, over 2,100 unique facilities were identified. For nonoverlapping facilities, the information obtained from FRS included facility name(s), 

address information, location coordinates, SIC/NAICS codes, and other facility 

identifiers (i.e., FRS ID, NEI ID, AFS ID, and TRI ID). This information was 

assigned the fourth highest priority.

 A business listing provided by the Idaho Secretary of State was merged with the 

above list, and appended to the master database for non-overlapping businesses. 

Information included contact person, facility name(s), and address information. This 

information was assigned the fifth highest priority. 

 The final data source to be merged into the master database was the 2005 through 

2007 TRI datasets. While the basic facility information was contained in the FRS 

data source, the TRI datasets also contained contact information. This information 

was assigned the lowest priority.

Using this procedure, the following quantities of potential point source facilities were 

identified:

 Tier 1 and Tier 2 permitted facilities: 109 (see Table 2-1)

 PBR facilities (portable rock crushers and dairies): 23 portable plants and 6 dairies 

(see Table 2-2)

 Unpermitted facilities: 1,654 facilities

A listing of the 1,683 total PBR and unpermitted facilities is presented in Appendix A. 
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Table 2-1. Permitted Point Sources in the Treasure Valley

Co. Facility Name

2008 

Emissions 

Data Co. Facility Name

2008 

Emissions 

Data

Ada

Ada Animal Crematorium 

Ada

Western Aircraft

Ada County/Hidden Hollow Landfill Western Electronics Inc 

American Paving Company  Western Idaho Cabinets 

Arrow Planers & Moulding

Canyon

Ace Supply Inc

B & D Foods  The Amalgamated Sugar Co (TASCO)-Nampa 

BFI Boise  Boise Packaging & Newsprint LLC Nampa 

Boise Independent School District - Victory  C & B Quality Trailer Works Inc 

Boise Moulding & Lumber Carco Mineral Resources Inc

C Wright Construction  Chevron USA Inc SS 98628

Chen Northern Inc Crookham Company

Chevron/NW Terminalling Boise  Darigold-Caldwell 

Circle K Store #440 Eco-Tech Services Inc

Classic Kitchen Doors Environmental Oil Services

Cremation Society Of Idaho  Flahiff Funeral Chapels Inc 

Darling International Fleetwood Homes of Idaho Inc 04-1 

Earl Scheib Inc Idaho Ethanol Processing

Empire Transport Inc Cloverdale Interstate Group LLC 

Envirosafe Svcs of Idaho Inc JC Penney Co Inc

EPSCO Corporation J.R. Simplot Company-Diversified Nampa 

Fiber Composites LLC  J.R. Simplot

Fiberglass Systems Inc Kuna J.R. Simplot Company - Food Group 

Fiberglass Systems Incorporated  Low's Ready Mix Inc 

G2 Energy LLC Mercy Medical Center 

Hewlett Packard Co - Boise Site  Micron Technology Inc Nampa 

Idaho Timber of Boise LLC  Mirage Enterprises Inc 

Jack's Tire & Oil Inc  Oldcastle Precast Inc 

Lar-Ken Septic Tanks Inc  Pacific Press Publishing Assoc 

Larson Miller Inc Pyro Energy

MAACO Collision Repair And Auto Center Rogers NK Seed Co

Michaels of Oregon  Seedbiotics 

Micron Technology Inc.  Seminis Vegetable Seeds 

Mike's Sand & Gravel Snake River Chemicals Caldwell

Motivepower Truck and Engine Annex (TEA)  Snake River Trailer Company 

Mountain View Animal Clinic Sorrento Lactalis Inc Swiss Village Plant 

Mountain View Funeral Home Boise  Summit Seed Coatings 

Mountain View Power Teton Sales Co 

Northwest Pipeline GP Boise  Univar USA Inc Nampa

Nxedge Inc Of Boise  US Army National Guard OMS2

Plum Creek Northwest Lumber  Western Farm Service – Caldwell 

Pre Cote Industries  Western Stockmens Inc 

Safety Kleen Corporation  Western World Incorporated

Saint Alphonsus Regional Medical Center  White's Hauling & Farm 

Saint Luke's Meridian Medical Center  Woodgrain Millwork Inc Nampa

Semmaterials L.P.-Boise Id Plant  XI Four Star Beef

Sinclair Pipeline Company  Z Casting Inc

St. Luke’s Regional Medical Center

Elmore

Double J Milling LLC 

Summers Funeral Home Evander Andrews Power Complex 

Tesoro Refining and Marketing Co., Boise  Glenns Ferry Cogeneration Partners Ltd

Treasure Valley Forest Products Boise  Idaho Fresh Pak (Plant #4) Glenns Ferry

Turner Sand & Gravel Idaho Power Co - Bennett Mountain 

Turner Sand & Gravel Northwest Pipeline Gp Mountain Home 

USAF Idaho Air National Guard Simplot Livestock Company Grandview

US DOT FAA Traffic Control Tower Treasure Valley Forest Products

Valley Sand & Gravel US Air Force-Mountain Home 

West Park/Walla Walla Shopping Center
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Table 2-2. Facilities Operating Under Permit by Rule in the Treasure Valley Air 

Shed

It should be noted that the listing of PBR and unpermitted sources does not include 

landfills, fuel suppliers/distributors, dry cleaners, municipal wastewater treatment plants

(WWTPs), beef cattle feedlots, and airports (to the extent that they could be identified). The 

reason for excluding these sources is because their activity data will be collected separately to 

use with methods for estimating their emissions which are unique to those source categories. 

These methodologies for these source categories are discussed in the following sections:

 Fuel suppliers/distributors (Section 3.1.1)

 Dry cleaners (Section 3.1.13)

 Wastewater treatment plants (Section 3.1.17)

DEQ ID or County Type of Facility Facility Name

1677700335 Portable C Wright Construction Co Inc

1677700418 Portable C Wright Construction Co Inc

1677700158 Portable Camas Gravel Company

1677700093 Portable Central Paving Company

1677700024 Portable Central Paving Company

1677700243 Portable Central Paving Company

1677700304 Portable Combined Districts Crushing Fund

1677700099 Portable Concrete Placing Company Inc

1677700389 Portable Debco Construction

1677700370 Portable Deerflat Sand & Gravel

1677700378 Portable Knife River (Masco Inc)

1677700209 Portable Nelson-Deppe Inc

1677700390 Portable Rambo Crushing Company

1677700162 Portable River Rock Sand & Gravel LLC

1677700100 Portable Seubert Excavators Inc

1677700103 Portable Seubert Excavators Inc

1677700373 Portable Staker & Parson Companies

77700407 Portable Staker & Parson Company

777-00422 Portable STP Concrete Co., Inc

041-00007 Portable Treasure Canyon Calcium

1677700231 Portable Western Construction

1677700042 Portable Western Construction

1677700212 Portable Western Construction

Ada Dairy Degroot Dairy

Canyon Dairy Beranna Dairy

Canyon Dairy Dry Lakes Dairy

Canyon Dairy Sun Ridge Dairy

Canyon Dairy T&T Cattle

Elmore Dairy TLK Dairy
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 Landfills (Section 3.1.18)

 Beef cattle feedlots (Section 3.1.23)

 Airports (Section 5.1.2)

The final database was provided to DEQ. DEQ then assigned a POSST User Name and 

Password to each record, and used the file to print names and contact information on each of the 

letters for both the permitted and PBR/unpermitted sources. Letters were then developed to mail 

to each facility to request completion of the POSST forms. The permitted sources were 

requested to complete the full POSST form (previously developed by DEQ for annual reporting), 

while the unpermitted facilities were allowed to complete a simplified “EZ” form (i.e., emission 

estimates were not required). Examples of these letters (i.e., one for the Tier 1 and Tier 2 

permitted facilities, and another for the PBR and unpermitted facilities) are included in Appendix 

B. Finally, the contact information and POSST User Names and Passwords from the final 

merged database were transferred to the POSST survey letters and mailed to each facility.

2.2 Emission Calculation Methodologies – Annual 

The methodologies used to calculate annual point source emissions for the 2008 base 

year are presented in this section. The estimation of the seasonal ozone and PM daily emissions 

for 2008 is discussed in Section 2.3, while the development of the future 2015 and 2023 

projected point source emissions inventories is presented in Section 7.1.1. 

Annual point source emissions were developed from data collected electronically by 

DEQ using the POSST submittal process. Of the 109 permitted facilities, a total of 60 facilities 

submitted 2008 annual emissions either through the complete POSST or as a separate facilitywide emissions inventory (see Table 2-1). Initial quality assurance (QA) was conducted by DEQ 

before emissions data were compiled.

Following DEQ’s QA, an additional QA step was conducted for consistency. The PM 

data submitted through POSST was very inconsistent. Some facilities submitted primary PM10

(PM10-PRI) emissions, while others submitted filterable PM10 (PM10-FIL) emissions. Most 

combustion sources did not submit condensable PM (PM-CON) emissions, even though such 

emissions would be expected. Some facilities submitted PM2.5 emissions that were identical to 

PM10 emissions based on an apparent assumption of equality, even though such an assumption 
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was incorrect. In order to address the inconsistency in PM emissions, the PM augmentation 

scheme utilized in the 2002 NEI was implemented (U.S. EPA, 2006). The PM augmentation 

scheme provided look-up tables of SCC-specific conversion factors (e.g., PM10-PRI to PM10-

FIL, PM10-FIL to PM-CON, PM10-FIL to PM2.5-FIL, etc.). The augmentation scheme was 

applied to either PM10-PRI or PM10-FIL emissions for every point source process reported in 

POSST. Wherever possible, identified controls were accounted for in this augmentation 

procedure. Application of the augmentation procedure resulted in PM10-FIL, PM2.5-FIL, and 

PM-CON emissions for every point source process. For inclusion in this report, these point 

source emissions were reported as PM10-PRI (i.e., sum of PM10-FIL and PM-CON) and PM2.5-

PRI (i.e., sum of PM2.5-FIL and PM-CON). However, in the formatted data files to be provided 

along with the final report, the filterable and condensable PM emissions will be provided, instead 

of the primary PM emissions.

Of the 1,683 unpermitted and PBR facilities included in Appendix A, a total of 632 

facilities (i.e., nearly a 38 percent return rate) submitted a simplified “EZ” form to DEQ. DEQ 

then performed the initial compilation of the EZ data. Subsequent QA was then conducted and 

facilities with unusable data were discarded. Because the unpermitted and PBR facilities had 

little or no previous interaction with DEQ concerning air emissions, there were considerable 

amounts of invalid data that were submitted to DEQ. Some issues included:

 Because the selection of the 1,683 unpermitted and PBR facilities was fairly broad, 

there were a large number of facilities that did not have emissive processes (e.g., 

businesses run out of homes, land management companies, etc.).

 Some facilities reported nonsensical units (e.g., tons of electricity, million cubic feet 

of heat, 1000 gallons of vehicles, gallons of steel, etc.).

 Some reported material quantities were not reasonable (e.g., a particular facility’s 

reported fuel use was a significant fraction of the state’s total industrial or 

commercial fuel use, etc.).

 Some reported material quantities did not match the reported SCC.

 There were handful of instances where submitted incorrect or missing data were 

corrected (i.e., typically based upon notes found elsewhere in the submitted data 

records), but, in general, the intent of incorrect or missing data was not discernible 

and so these facilities were discarded.
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After these QA steps, a total of 291 facilities that submitted EZ data remained with valid 

and reasonable activity data.

The next step for these 291 facilities was to determine which facilities exceeded the point 

source thresholds (i.e., 5 tpy for PM10, PM2.5, SOx, and NH3; 10 tpy for VOC; and 25 tpy for NOx

and CO). This was accomplished by using emission factors from a variety of sources including 

emission factors from AP-42 and other guidance documents, as well as information submitted by 

respondents (e.g., paint or adhesive VOC content, etc.). For example, the threshold 

determination for natural gas combustion used the AP-42 emission factors for small natural gas 

boilers (i.e., 100 lbs NOx/106ft3, 0.6 lbs SO2/106ft3, 5.5 lbs VOC/106ft3, 84 lbs CO/106ft3, 7.6 

lbs PM10/106ft3, and 7.6 lbs PM2.5/10

6

ft3) (U.S. EPA, 2010). The resultant natural gas quantities 

needed to exceed the respective pollutant thresholds were: 500 × 106ft3 for NOx, 16,667 × 106

ft3 for SO2, 3,636 × 106ft3 for VOC, 595 × 106ft3 for CO, and 1,316 × 106ft3 for PM10 and PM2.5. 

The lowest quantity (i.e., 500 × 106ft3 for NOx) was then used to determine which facilities had 

natural gas combustion sources that exceeded the thresholds and should be considered to be point 

sources. Threshold determinations were conducted for the following source categories: fuel 

combustion (i.e., natural gas, LPG, distillate oil, and waste oil), gasoline distribution, rock 

crushing, concrete batching, graphic arts, aviation gasoline distribution, and adhesive 

application. Following the threshold determination, a total of 33 non-permitted sources were 

identified as exceeding DEQ’s point source thresholds with 24 of these being gasoline stations. 

Because of the potential difficulty associated with modeling some gasoline stations as point 

sources and some as area sources, all gasoline stations were kept in the gasoline distribution area 

source category, even though 24 gasoline stations exceeded DEQ’s point source thresholds. The 

remaining nine non-permitted sources that exceeded DEQ’s point source thresholds are listed in 

Table 2-3. 

The reconciliation between point source activity data and area source activity data was 

performed. Due to incompatibilities between activity data and estimation methodologies, 

activity data reconciliation was only possible for natural gas combustion in the industrial and 

commercial sectors. The activity data reconciliation is described further in Section 3.1.1 

(industrial and commercial natural gas combustion).
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Table 2-3. Unpermitted Facilities that Exceeded Point Source Thresholds in 2008 

Emissions

Facility Name County

C Wright Construction Co., Inc. (Fac Id: 1677700418) Ada

Guerdon Enterprises LLC Ada

Knife River Ada

Western Construction (Portable Plant) Ada

C Wright Construction Co., Inc. (Fac Id: 1677700335) Canyon

Combined Districts Crushing Fund Canyon

Kit Home Builders West Canyon

Nelson-Deppe Inc. Canyon

River Rock Sand & Gravel LLC Canyon

2.3 Emission Calculation Methodologies – Ozone and PM Season

After the annual point source emissions were estimated using the methodologies 

described in Section 2.2, the daily ozone season and PM season emission estimates were 

developed. The ozone season extends from April 1 through October 31 (i.e., 214 days), while 

the PM season is from November 1 through February 29 (2008 is a leap year) (i.e., 121 days). 

The seasonal emissions were developed using a seasonal temporal allocation profiles. All of the 

sources that submitted electronic data via the POSST or EZ submittal identified the percent of 

operations, as number between 0 and 100, that occurred during the spring (i.e., March through 

May), summer (i.e., June through August), fall (i.e., September through November), and winter 

(i.e., December through February) for each process. In a few instances, the seasonal percent of 

operations was not identified for a particular process at a facility. These were gapfilled based 

upon seasonal percent information for other processes at the same facility.

The ozone season and PM season factors were developed using the following equations:

Where:

OSF = Ozone seasonal factor

PSF = PM seasonal factor

SPR = Percent of operations in spring

SUM = Percent of operations in summer

FAL = Percent of operations in fall

WIN = Percent of operations in winter



















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



 











 

























91

61

100

FAL

100

SUM

92

61

100

SPR OSF 











 

























100

WIN

91

30

100

FAL PSF
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

2-9

The ozone season and PM season daily emissions were calculated by multiplying annual 

emissions by the ozone/PM season factors and then dividing by the number of days in the 

ozone/PM season. This is shown with the following equations:

Where:

EA = Annual emissions (tons/year);

EOS = Ozone season daily emissions (tons/day);

EPS = PM season daily emissions (tons/day);

OSF = Ozone seasonal factor; and

PSF = PM seasonal factor.

2.4 Emission Results by Facility

The facility-level annual point source emissions are presented in Table 2-4. The facilities 

are listed alphabetically by county. The permitted point sources are identified as a POSST 

facility type; the unpermitted point sources are identified as an EZ facility type. Table cells 

containing a value of 0.0 represent some non-zero value less than 0.05 tons per year (tpy); blank 

cells represent zero emissions. One facility listed in Table 2-1 (Fiberglass Systems in Ada 

County) submitted a POSST submittal with zero emissions and was not included in Table 2-4. 

Similarly, the facility-level ozone season and PM season emissions are presented in Table 2-5

and 2-6, respectively. Table cells containing a value of 0.00 represent some non-zero value less 

than 0.005 tons per day (tpd); blank cells represent zero emissions. All facility-level point 

source data presented in Tables 2-4, 2-5, and 2-6 are included in the electronic data files 

submitted in conjunction with this final report.

2.5 QA/QC Procedures

For the point source inventory development, a number of QA/QC procedures were 

described in the project IPP/QAP (ERG and ENVIRON, 2009). However, the actual point 

source inventory development process was somewhat different than envisioned in the IPP/QAP. 

ERG’s involvement with the POSST and EZ data processing and manipulation was considerably 

reduced with DEQ taking on a larger role. However, ERG did conduct some QA/QC following 

214

E OSF

E

A

OS





121

E PSF

E

A

PS




2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

2-10

Table 2-4. 2008 Annual Point Source Emissions (Tons/Year)

Facility Name County

Facility 

Type NOx SO2 VOC CO PM10 PM2.5 NH3

Ada Animal 

Crematorium Ada POSST 0.4 0.1 0.0 0.2 0.1 0.1

American Paving 

Company Ada POSST 4.5 1.3 0.3

B & D Foods Ada POSST 1.2 0.0 0.1 1.0 0.6 0.4

BFI Boise Ada POSST 0.0

Boise Independent 

School District -

Victory Ada POSST 0.0 0.0 0.0

C Wright Construction Ada POSST 0.6 0.1 1.1 3.1 1.1 0.3

C Wright Construction 

Co., Inc. (Fac Id: 

1677700418) Ada EZ 5.2 1.7

Cremation Society Of 

Idaho Ada POSST 0.1 0.0 0.1 0.1 0.1

Fiber Composites LLC Ada POSST 29.5 21.3

Guerdon Enterprises 

LLC Ada EZ 21.4

Hewlett Packard Co -

Boise Site Ada POSST 50.4 2.0 3.0 16.2 3.0 2.9

Idaho Timber of Boise 

LLC Ada POSST 0.1 0.0

Jack's Tire & Oil Inc Ada POSST 0.1 0.0 0.1 0.1 0.0 0.0 0.0

Knife River Ada EZ 7.2 5.3 2.2 24.0 0.3 0.2

LAR KEN Septic Tanks 

Inc Ada POSST 0.5 0.2

Micron Technology Inc Ada POSST 34.0 1.4 17.1 24.6 36.7 34.2 45.9

MotivePower Truck & 

Engine Annex (TEA) Ada POSST 10.2 0.8 33.8 5.1 0.6 0.6

Mountain View Funeral 

Home Boise Ada POSST 0.5 0.0 0.0 0.1 0.1 0.1

Northwest Pipeline -

Boise Ada POSST 84.6 0.5 2.9 2.9 2.9

NW Terminalling, 

Boise Ada POSST 4.5 74.4 11.2 2.7 1.9

Nxedge Inc of Boise Ada POSST 0.3 0.0 0.1 0.3 0.1 0.1

Plum Creek Northwest 

Lumber Ada POSST 25.2 24.4

Pre Cote Industries Ada POSST 11.5

Safety Kleen 

Corporation Ada POSST 0.2

Saint Alphonsus 

Regional Medical 

Center Ada POSST 14.3 0.1 0.4 6.3 0.6 0.6

Saint Luke's Meridian 

Medical Center Ada POSST 21.7 3.7 1.2 17.5 7.6 7.4

Saint Luke's Regional 

Medical Center Ada POSST 115.1 46.9 4.1 52.9 23.6 23.3

Semmaterials L.P.-

Boise Plant Ada POSST 2.7 0.0 2.9 2.2 0.9 0.5

Sinclair Pipeline Ada POSST 54.8
Table 2-4. Continued

2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

2-11

Facility Name County

Facility 

Type NOx SO2 VOC CO PM10 PM2.5 NH3

Company 

Tesoro Refining and 

Marketing Company, 

Boise Ada POSST 0.0 0.0 20.9 0.0 0.0 0.0

Treasure Valley Forest 

Products, Boise Ada POSST 0.5 0.0 1.1 1.9 25.8 18.9

Western Construction 

(Portable Plant) Ada EZ 7.3 5.4 2.2 24.4 0.3 0.2

Western Electronics Inc Ada POSST 0.0 0.0 0.0 0.0

Western Idaho Cabinets Ada POSST 15.1 0.1 0.1

Boise Packaging & 

Newsprint LLC Nampa Canyon POSST 2.1 0.0 25.2 2.2 1.8 1.3

C Wright Construction 

Co., Inc. (Fac Id: 

1677700335) Canyon EZ 9.7 3.1

C&B Quality Trailer 

Works Canyon POSST 0.1 0.0 33.1 0.0 0.2 0.2

Combined Districts 

Crushing Fund Canyon EZ 11.3 3.7

Darigold-Caldwell Canyon POSST 16.0 0.1 0.9 13.0 8.4 5.4

Flahiff Funeral Chapels 

Inc Canyon POSST 1.2 0.4 0.0 0.0 0.2 0.1

Fleetwood Homes of 

Idaho Inc 04-1 Canyon POSST 10.6 0.3 0.2

Interstate Group LLC Canyon POSST 0.0 14.3 0.0 0.7 0.5

JR Simplot Company –

Diversified Nampa Canyon POSST 31.3 0.2 41.6 32.5 52.1 39.0

JR Simplot Company -

Food Group Canyon POSST 57.0 36.0 17.9 67.5 119.6 102.2 240.1

Kit Home Builders 

West Canyon EZ 36.1

Low's Ready Mix, Inc. Canyon POSST 0.2 0.1

Mercy Medical Center Canyon POSST 1.8 0.0 0.1 1.5 0.1 0.1

Micron Technology Inc 

Nampa Canyon POSST 3.1 0.1 40.6 2.1 1.0 0.9 0.5

Mirage Enterprises Inc Canyon POSST 12.7 0.3 0.2

Nelson-Deppe Inc. Canyon EZ 36.8 12.0

Oldcastle Precast Inc Canyon POSST 0.0 0.0 0.0 0.0 0.0 0.0

Pacific Press Publishing 

Assoc Canyon POSST 1.3 0.0 20.0 1.1 0.1 0.1

River Rock Sand & 

Gravel LLC Canyon EZ 6.1 2.0

Seedbiotics Canyon POSST 9.4 8.7

Seminis Vegetable 

Seeds Canyon POSST 0.9 2.9 21.6 0.1 0.1

Snake River Trailer 

Company Canyon POSST 0.0

Sorrento Lactalis 

Incorporated Swiss 

Village Plant Canyon POSST 37.6 0.3 2.1 40.4 17.5 17.2

Summit Seed Coatings Canyon POSST 0.3 0.0 0.0 0.2 0.3 0.2

TASCO Nampa Canyon POSST 1,203.5 1,969.9 29.2 862.4 219.0 80.2 175.7
Table 2-4. Continued

2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

2-12

Facility Name County

Facility 

Type NOx SO2 VOC CO PM10 PM2.5 NH3

Teton Sales Company Canyon POSST 0.1 0.0 16.2 0.1 0.1 0.1

Western Farm Service -

Caldwell Canyon POSST 0.1 0.3 0.0 0.0 0.1 0.1 4.3

Western Stockmens Inc

 Canyon POSST 0.1 0.0 0.0 0.1 0.3 0.1

White's Hauling & 

Farm Canyon POSST 0.2 0.1

Double J Milling LLC Elmore POSST 5.3 0.0 0.3 4.5 5.3 3.1

Evander Andrew 

Complex Elmore POSST 29.1 0.5 1.8 32.7 5.6 5.6

Idaho Power - Bennett 

Mountain Elmore POSST 18.6 0.1 0.6 6.4 1.7 1.7

Mountain Home Air 

Force Base Elmore POSST 100.6 1.8 18.1 49.3 123.2 48.2

Northwest Pipeline -

Mountain Home Elmore POSST 206.6 0.0 5.8 12.3 0.0 0.0

Ada County 355.6 65.7 268.1 198.5 169.1 142.6 46.0

Canyon County 1,356.5 2,007.3 303.4 1,044.7 495.9 277.8 420.6

Elmore County 360.3 2.5 26.6 105.3 135.9 58.7 0.0

Total 2,072.4 2,075.4 598.1 1,348.5 800.9 479.0 466.6
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

2-13

Table 2-5. 2008 Ozone Season Point Source Emissions (Tons/Day)

Facility Name County

Facility 

Type NOx SO2 VOC CO PM10 PM2.5 NH3

Ada Animal 

Crematorium Ada POSST 0.00 0.00 0.00 0.00 0.00 0.00

American Paving 

Company Ada POSST 0.01 0.00

B & D Foods Ada POSST 0.00 0.00 0.00 0.00 0.00 0.00

BFI Boise Ada POSST 0.00

Boise Independent 

School District -

Victory Ada POSST 0.00 0.00 0.00

C Wright Construction Ada POSST 0.00 0.00 0.00 0.01 0.00 0.00

C Wright Construction 

Co., Inc. (Fac Id: 

1677700418) Ada EZ 0.01 0.00

Cremation Society Of 

Idaho Ada POSST 0.00 0.00 0.00 0.00 0.00

Fiber Composites LLC Ada POSST 0.08 0.06

Guerdon Enterprises 

LLC Ada EZ 0.06

Hewlett Packard Co -

Boise Site Ada POSST 0.14 0.01 0.01 0.04 0.01 0.01

Idaho Timber of Boise 

LLC Ada POSST 0.00 0.00

Jack's Tire & Oil Inc Ada POSST 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Knife River Ada EZ 0.03 0.02 0.01 0.10 0.00 0.00

LAR KEN Septic Tanks 

Inc Ada POSST 0.00 0.00

Micron Technology Inc Ada POSST 0.08 0.00 0.05 0.06 0.10 0.09 0.12

MotivePower Truck & 

Engine Annex (TEA) Ada POSST 0.03 0.00 0.09 0.01 0.00 0.00

Mountain View Funeral 

Home Boise Ada POSST 0.00 0.00 0.00 0.00 0.00 0.00

Northwest Pipeline -

Boise Ada POSST 0.23 0.00 0.01 0.01 0.01

NW Terminalling, 

Boise Ada POSST 0.01 0.21 0.03 0.01 0.01

Nxedge Inc of Boise Ada POSST 0.00 0.00 0.00 0.00 0.00 0.00

Plum Creek Northwest 

Lumber Ada POSST 0.07 0.07

Pre Cote Industries Ada POSST 0.03

Safety Kleen 

Corporation Ada POSST 0.00

Saint Alphonsus 

Regional Medical 

Center Ada POSST 0.04 0.00 0.00 0.02 0.00 0.00

Saint Luke's Meridian 

Medical Center Ada POSST 0.06 0.01 0.00 0.04 0.02 0.02

Saint Luke's Regional 

Medical Center Ada POSST 0.29 0.09 0.01 0.13 0.05 0.05

Semmaterials L.P.-

Boise Plant Ada POSST 0.01 0.00 0.01 0.01 0.00 0.00

Sinclair Pipeline Ada POSST 0.15
Table 2-5. Continued

2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

2-14

Facility Name County

Facility 

Type NOx SO2 VOC CO PM10 PM2.5 NH3

Company 

Tesoro Refining and 

Marketing Company, 

Boise Ada POSST 0.00 0.00 0.06 0.00 0.00 0.00

Treasure Valley Forest 

Products, Boise Ada POSST 0.00 0.00 0.00 0.01 0.08 0.06

Western Construction 

(Portable Plant) Ada EZ 0.03 0.02 0.01 0.09 0.00 0.00

Western Electronics Inc Ada POSST 0.00 0.00 0.00 0.00

Western Idaho Cabinets Ada POSST 0.04 0.00 0.00

Boise Packaging & 

Newsprint LLC Nampa Canyon POSST 0.01 0.00 0.07 0.01 0.01 0.00

C Wright Construction 

Co., Inc. (Fac Id: 

1677700335) Canyon EZ 0.03 0.01

C&B Quality Trailer 

Works Canyon POSST 0.00 0.00 0.10 0.00 0.00 0.00

Combined Districts 

Crushing Fund Canyon EZ 0.03 0.01

Darigold-Caldwell Canyon POSST 0.04 0.00 0.00 0.04 0.02 0.01

Flahiff Funeral Chapels 

Inc Canyon POSST 0.00 0.00 0.00 0.00 0.00 0.00

Fleetwood Homes of 

Idaho Inc 04-1 Canyon POSST 0.03 0.00 0.00

Interstate Group LLC Canyon POSST 0.00 0.04 0.00 0.00 0.00

JR Simplot Company –

Diversified Nampa Canyon POSST 0.09 0.00 0.11 0.09 0.14 0.11

JR Simplot Company -

Food Group Canyon POSST 0.13 0.10 0.05 0.16 0.32 0.28 0.65

Kit Home Builders 

West Canyon EZ 0.10

Low's Ready Mix, Inc. Canyon POSST 0.00 0.00

Mercy Medical Center Canyon POSST 0.00 0.00 0.00 0.00 0.00 0.00

Micron Technology Inc 

Nampa Canyon POSST 0.01 0.00 0.11 0.00 0.00 0.00 0.00

Mirage Enterprises Inc Canyon POSST 0.03 0.00 0.00

Nelson-Deppe Inc. Canyon EZ 0.11 0.04

Oldcastle Precast Inc Canyon POSST 0.00 0.00 0.00 0.00 0.00 0.00

Pacific Press Publishing 

Assoc Canyon POSST 0.00 0.00 0.06 0.00 0.00 0.00

River Rock Sand & 

Gravel LLC Canyon EZ 0.02 0.01

Seedbiotics Canyon POSST 0.01 0.01

Seminis Vegetable 

Seeds Canyon POSST 0.00 0.01 0.07 0.00 0.00

Snake River Trailer 

Company Canyon POSST 0.00

Sorrento Lactalis 

Incorporated Swiss 

Village Plant Canyon POSST 0.10 0.00 0.01 0.11 0.05 0.05

Summit Seed Coatings Canyon POSST 0.00 0.00 0.00 0.00 0.00 0.00

TASCO Nampa Canyon POSST 3.14 5.10 0.06 1.63 0.57 0.21 0.40
Table 2-5. Continued

2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

2-15

Facility Name County

Facility 

Type NOx SO2 VOC CO PM10 PM2.5 NH3

Teton Sales Company Canyon POSST 0.00 0.00 0.04 0.00 0.00 0.00

Western Farm Service -

Caldwell Canyon POSST 0.00 0.00 0.00 0.00 0.00 0.00 0.02

Western Stockmens Inc

 Canyon POSST 0.00 0.00 0.00 0.00 0.00 0.00

White's Hauling & 

Farm Canyon POSST 0.00 0.00

Double J Milling LLC Elmore POSST 0.01 0.00 0.00 0.01 0.01 0.01

Evander Andrew 

Complex Elmore POSST 0.11 0.00 0.01 0.13 0.02 0.02

Idaho Power - Bennett 

Mountain Elmore POSST 0.04 0.00 0.00 0.01 0.00 0.00

Mountain Home Air 

Force Base Elmore POSST 0.27 0.00 0.05 0.13 0.34 0.13

Northwest Pipeline -

Mountain Home Elmore POSST 0.56 0.00 0.02 0.03 0.00 0.00

Ada County 0.96 0.16 0.75 0.58 0.46 0.38 0.12

Canyon County 3.52 5.20 0.82 2.11 1.31 0.73 1.07

Elmore County 1.00 0.01 0.07 0.32 0.38 0.17 0.00

Total 5.48 5.36 1.64 3.01 2.15 1.28 1.20
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

2-16

Table 2-6. 2008 PM Season Point Source Emissions (Tons/Day)

Facility Name County

Facility 

Type NOx SO2 VOC CO PM10 PM2.5 NH3

Ada Animal 

Crematorium Ada POSST 0.00 0.00 0.00 0.00 0.00 0.00

American Paving 

Company Ada POSST 0.00 0.00

B & D Foods Ada POSST 0.00 0.00 0.00 0.00 0.00 0.00

BFI Boise Ada POSST 0.00

Boise Independent 

School District -

Victory Ada POSST 0.00 0.00 0.00

C Wright Construction Ada POSST 0.00 0.00 0.00 0.00 0.00 0.00

C Wright Construction 

Co., Inc. (Fac Id: 

1677700418) Ada EZ 0.01 0.00

Cremation Society Of 

Idaho Ada POSST 0.00 0.00 0.00 0.00 0.00

Fiber Composites LLC Ada POSST 0.08 0.06

Guerdon Enterprises 

LLC Ada EZ 0.05

Hewlett Packard Co -

Boise Site Ada POSST 0.14 0.01 0.01 0.04 0.01 0.01

Idaho Timber of Boise 

LLC Ada POSST 0.00 0.00

Jack's Tire & Oil Inc Ada POSST 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Knife River Ada EZ 0.00 0.00 0.00 0.01 0.00 0.00

LAR KEN Septic Tanks 

Inc Ada POSST 0.00 0.00

Micron Technology Inc Ada POSST 0.11 0.00 0.05 0.09 0.10 0.10 0.13

MotivePower Truck & 

Engine Annex (TEA) Ada POSST 0.03 0.00 0.09 0.01 0.00 0.00

Mountain View Funeral 

Home Boise Ada POSST 0.00 0.00 0.00 0.00 0.00 0.00

Northwest Pipeline -

Boise Ada POSST 0.23 0.00 0.01 0.01 0.01

NW Terminalling, 

Boise Ada POSST 0.01 0.19 0.03 0.01 0.01

Nxedge Inc of Boise Ada POSST 0.00 0.00 0.00 0.00 0.00 0.00

Plum Creek Northwest 

Lumber Ada POSST 0.07 0.07

Pre Cote Industries Ada POSST 0.03

Safety Kleen 

Corporation Ada POSST 0.00

Saint Alphonsus 

Regional Medical 

Center Ada POSST 0.04 0.00 0.00 0.02 0.00 0.00

Saint Luke's Meridian 

Medical Center Ada POSST 0.06 0.01 0.00 0.07 0.03 0.03

Saint Luke's Regional 

Medical Center Ada POSST 0.36 0.19 0.01 0.17 0.08 0.08

Semmaterials L.P.-

Boise Plant Ada POSST 0.00 0.00 0.01 0.00 0.00 0.00

Sinclair Pipeline Ada POSST 0.15
Table 2-6. Continued

2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

2-17

Facility Name County

Facility 

Type NOx SO2 VOC CO PM10 PM2.5 NH3

Company 

Tesoro Refining and 

Marketing Company, 

Boise Ada POSST 0.00 0.00 0.06 0.00 0.00 0.00

Treasure Valley Forest 

Products, Boise Ada POSST 0.00 0.00 0.00 0.00 0.04 0.03

Western Construction 

(Portable Plant) Ada EZ 0.00 0.00 0.00 0.01 0.00 0.00

Western Electronics Inc Ada POSST 0.00 0.00 0.00 0.00

Western Idaho Cabinets Ada POSST 0.04 0.00 0.00

Boise Packaging & 

Newsprint LLC Nampa Canyon POSST 0.01 0.00 0.07 0.01 0.01 0.00

C Wright Construction 

Co., Inc. (Fac Id: 

1677700335) Canyon EZ 0.03 0.01

C&B Quality Trailer 

Works Canyon POSST 0.00 0.00 0.06 0.00 0.00 0.00

Combined Districts 

Crushing Fund Canyon EZ 0.03 0.01

Darigold-Caldwell Canyon POSST 0.04 0.00 0.00 0.04 0.02 0.01

Flahiff Funeral Chapels 

Inc Canyon POSST 0.00 0.00 0.00 0.00 0.00 0.00

Fleetwood Homes of 

Idaho Inc 04-1 Canyon POSST 0.03 0.00 0.00

Interstate Group LLC Canyon POSST 0.00 0.04 0.00 0.00 0.00

JR Simplot Company –

Diversified Nampa Canyon POSST 0.09 0.00 0.11 0.09 0.14 0.11

JR Simplot Company -

Food Group Canyon POSST 0.21 0.10 0.05 0.23 0.33 0.28 0.66

Kit Home Builders 

West Canyon EZ 0.10

Low's Ready Mix, Inc. Canyon POSST 0.00 0.00

Mercy Medical Center Canyon POSST 0.00 0.00 0.00 0.00 0.00 0.00

Micron Technology Inc 

Nampa Canyon POSST 0.01 0.00 0.11 0.01 0.00 0.00 0.00

Mirage Enterprises Inc Canyon POSST 0.03 0.00 0.00

Nelson-Deppe Inc. Canyon EZ 0.09 0.03

Oldcastle Precast Inc Canyon POSST 0.00 0.00 0.00 0.00 0.00 0.00

Pacific Press Publishing 

Assoc Canyon POSST 0.00 0.00 0.05 0.00 0.00 0.00

River Rock Sand & 

Gravel LLC Canyon EZ 0.02 0.01

Seedbiotics Canyon POSST 0.05 0.04

Seminis Vegetable 

Seeds Canyon POSST 0.00 0.01 0.06 0.00 0.00

Snake River Trailer 

Company Canyon POSST 0.00

Sorrento Lactalis 

Incorporated Swiss 

Village Plant Canyon POSST 0.10 0.00 0.01 0.11 0.05 0.05

Summit Seed Coatings Canyon POSST 0.00 0.00 0.00 0.00 0.00 0.00

TASCO Nampa Canyon POSST 3.94 6.40 0.14 4.22 0.72 0.27 0.68
Table 2-6. Continued

2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

2-18

Facility Name County

Facility 

Type NOx SO2 VOC CO PM10 PM2.5 NH3

Teton Sales Company Canyon POSST 0.00 0.00 0.04 0.00 0.00 0.00

Western Farm Service -

Caldwell Canyon POSST 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Western Stockmens Inc

 Canyon POSST 0.00 0.00 0.00 0.00 0.00 0.00

White's Hauling & 

Farm Canyon POSST 0.00 0.00

Double J Milling LLC Elmore POSST 0.01 0.00 0.00 0.01 0.01 0.01

Evander Andrew 

Complex Elmore POSST 0.03 0.00 0.00 0.03 0.01 0.01

Idaho Power - Bennett 

Mountain Elmore POSST 0.07 0.00 0.00 0.03 0.01 0.01

Mountain Home Air 

Force Base Elmore POSST 0.28 0.00 0.05 0.14 0.34 0.13

Northwest Pipeline -

Mountain Home Elmore POSST 0.57 0.00 0.02 0.03 0.00 0.00

Ada County 1.00 0.22 0.70 0.48 0.45 0.39 0.13

Canyon County 4.41 6.50 0.86 4.76 1.49 0.83 1.34

Elmore County 0.97 0.01 0.07 0.24 0.37 0.15 0.00

Total 6.38 6.73 1.63 5.48 2.31 1.37 1.47
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

2-19

the transmittal of the POSST and EZ data from DEQ. Before initiating any emission 

calculations, ERG conducted a high-level review of the transmitted POSST and EZ data files and 

examined the data for any questionable outliers. Questions regarding these outliers were then 

communicated to DEQ staff. Analysis of the EZ data did involved some QA/QC procedures 

(e.g., identification of non-emissive processes, nonsensical units, unreasonably high material 

quantities, SCC-material inconsistencies, incorrectly input information, etc.). Subsequent 

manipulation of point source data included frequent summation checks to ensure that individual 

process emissions were not accidentally omitted.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

2-20

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2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-1

3.0 2008 AREA SOURCE EMISSIONS INVENTORY

Area sources are defined as those sources emitting annual emissions less than the point 

source thresholds. The Treasure Valley emissions inventory includes all of the area source 

emission categories listed in Table 1-1. In general, these are identical to the categories identified 

in the IPP/QAP document (ERG and ENVIRON, 2009). The only significant changes are that a 

few additional ammonia source categories (i.e., wild animal ammonia and soil ammonia) and a 

few specialized categories (i.e., industrial refrigeration/cold storage and irrigation ditch burning)

have been added.

3.1 Emissions Calculation Methodologies – Annual 

The annual area source emissions calculation methodologies are briefly summarized in 

Table 3-1 (i.e., the Area Source Matrix). The Area Source Matrix was previously presented in 

the IPP/QAP and summarized the preferred and alternative methodologies for each area source 

category, as well as activity data and emission factors. The Area Source Matrix has been 

modified based upon the methodologies, activity data, and emission factors actually used; in 

addition, each details of each methodology are presented in the subsections below.

3.1.1 Fuel Combustion

Fuel combustion includes three distinct sectors (i.e., industrial, commercial/ institutional, 

and residential) and a number of different fuels (e.g., natural gas, distillate fuel oil, liquefied 

petroleum gas [LPG], etc.); residential wood combustion is treated as a separate area source 

category, which is described in the following section.

Activity data for industrial, commercial/institutional, and residential fuel combustion 

were collected using a mail-out survey (included as Appendix C) that was sent to fuel dealers 

and distributors in September 2009. The survey was mailed to a total of 66 fuel dealers and 

distributors located in Ada, Canyon, or Elmore counties, or in adjacent counties (i.e., Boise, 

Gem, Gooding, Owyhee, Payette, and Twin Falls counties) that might sell fuel within Ada, 

Canyon, or Elmore counties. The list of fuel dealers and distributors was compiled from four online business directories or listings (i.e., Yellow Pages, Dun & Bradstreet, Manta, and Hoover’s).
2008, 2015, 2023 Treasure Valley Emissions Inventories

3-2

Final, August 31, 2010

Table 3-1. Area Source Matrix

Source Category Pollutants Methodology Activity Data Notes

Industrial Fuel 

Combustion

NOx, SO2, VOC, 

CO, PM10, PM2.5, 

NH3

Emission factors: AP-42 (Sections 1.3, 1.4, and 

1.5); 2002 NEI Documentation; EIIP Ammonia 

Report 

Local fuel survey (fuel 

quantities and sulfur 

content)

Includes distillate, natural gas, and 

LPG.

Point source reconciliation conducted 

for natural gas only.

Commercial/ 

Institutional Fuel 

Combustion

NOx, SO2, VOC, 

CO, PM10, PM2.5, 

NH3

Emission factors: AP-42 (Sections 1.3, 1.4, and 

1.5); 2002 NEI Documentation; EIIP Ammonia 

Report

Local fuel survey (fuel 

quantities and sulfur 

content)

Includes distillate, natural gas, LPG, 

and kerosene.

Point source reconciliation conducted 

for natural gas only.

Residential Fuel 

Combustion (excluding 

wood)

NOx, SO2, VOC, 

CO, PM10, PM2.5, 

NH3

Emission factors: AP-42 (Sections 1.3, 1.4, and 

1.5); 2002 NEI Documentation; EIIP Ammonia 

Report

Local fuel survey (fuel 

quantities and sulfur 

content)

Includes distillate, natural gas, LPG, 

and kerosene.

Residential Wood 

Combustion

NOx, SO2, VOC, 

CO, PM10, PM2.5, 

NH3

Emission factors: 2002 NEI Documentation Local residential wood 

combustion survey

Paved Road Dust PM10, PM2.5 2011 AP-42 Section 13.2.1 (Ada and Canyon); 

1996 AP-42 (Section 13.2.1) (Elmore)

VMT, silt loading

Unpaved Road Dust PM10, PM2.5 TVRDS methodology (Ada and Canyon); AP-42 

(Section 13.2.2) (Elmore)

VMT, silt content 

Commercial Cooking VOC, CO, PM10, 

PM2.5

Emission factors: 2002 NEI Documentation Number of equipment, 

annual meat cooked per 

equipment

Includes charbroiling, deep fat 

frying, and griddle frying

Bakeries VOC Per capita emission factors: EIIP (Vol. III, 

Abstracts)

Population, per capita 

bread consumption

Construction PM10, PM2.5 Emission factors: 2002 NEI Documentation Number of building 

permits

Industrial Refrigeration/ 

Cold Storage

NH3 Per employee emission factors: EIIP Ammonia 

Report

Employee counts

Architectural Surface 

Coating

VOC Emissions ratioing based on population and 

employment: 2002 NEI Documentation 

2002 NEI emissions; 

population and 

employee counts

Autobody Refinishing VOC Per employee emission factors: 2002 NEI 

Documentation

Employee counts

Traffic Markings VOC Mass balance Traffic marking 

quantities; VOC 

content
Table 3-1. Continued

2008, 2015, 2023 Treasure Valley Emissions Inventories

3-3

Final, August 31, 2010

Source Category Pollutants Methodology Activity Data Notes

Industrial Surface 

Coating

VOC Emissions ratioing based on employment: 2002 

NEI Documentation 

2002 NEI emissions; 

employee counts

No point source reconciliation 

conducted.

Degreasing VOC Emissions ratioing based on employment: 2002 

NEI Documentation 

2002 NEI emissions; 

employee counts

No point source reconciliation 

conducted.

Dry Cleaning VOC Mass balance Local survey (quantity 

of solvent used)

Graphic Arts VOC Per employee emission factors: 2002 NEI 

Documentation

Employee counts

Consumer Solvent Use VOC Per capita emission factors: 2002 NEI 

Documentation

Population

Pesticide Application VOC Emission factors: EIIP (Vol. III, Chap. 9) Planted acreage, 

application rates, % 

active ingredient, 

formulation type

Gasoline Transport and 

Distribution

VOC Emission factors: AP-42 (Section 5.2), on-road 

motor vehicle modeling files

Quantity of fuel, Stage 

I/II controls

Point source reconciliation 

conducted.

Open Burning 

(Household and Yard)

NOx, SO2, VOC, 

CO, PM10, PM2.5

Emission factors: 2002 NEI Documentation Population not subject 

to burn bans

Wastewater Treatment VOC, NH3 Emission factors: 2002 NEI Documentation Local survey (quantity 

of water treated)

Landfills VOC Theoretical first-order kinetic model: AP-42 

(Section 2.4)

Local survey (refuse 

acceptance rate, landfill 

opening/closing)

Agricultural Tilling PM10, PM2.5 Emission factors: ARB Area Source Method 

(Section 7.4)

Acreage planted, 

planting practices

Agricultural Harvesting PM10, PM2.5 Emission factors: ARB Area Source Method 

(Section 7.5)

Acreage harvested, 

harvesting practices

Agricultural Burning –

Fields

VOC, CO, PM10, 

PM2.5

Emission factors: AP-42 (Section 2.5) Burned acreage, fuel 

loading, burning 

practices

Agricultural Burning –

Irrigation Ditches

VOC, CO, PM10, 

PM2.5

Emission factors: AP-42 (Section 2.5) Burned acreage, fuel 

loading, burning 

practices

Beef Cattle Feedlots VOC, PM10, PM2.5 Emission factors: ARB Area Source Method 

(Section 7.6)

Head of cattle, 

residence time

Structural Fires NOx, VOC, CO, 

PM10, PM2.5

Emission factors: EIIP (Vol. III, Chap. 18) Number of houses 

burned

Vehicle Fires NOx, VOC, CO, Emission factors: EIIP (Vol. III, Abstracts) Number of vehicles 
Table 3

-1. Continued

2008, 2015, 2023 Treasure Valley Emissions Inventories 3-4Final, August 31, 2010

Source Category Pollutants Methodology Activity Data Notes

PM10, PM2.5 burned

Windblown Dust PM10, PM2.5 WRAP windblown dust model Wind speeds, soil 

textures, crop acreages, 

crop calendars

Livestock Ammonia NH

3 WRAP NH3 emissions model Livestock population

Agricultural Fertilizer NH

3 WRAP NH3 emissions model Harvested acreage, type 

and quantity of 

fertilizers

Domestic Ammonia NH

3 WRAP NH3 emissions model Population

Wild Animals NH

3 WRAP NH3 emissions model Wild animal population

Soil Ammonia NH

3 WRAP NH3 emissions model Land use/land cover 

acreages
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-5

Out of the 66 surveys that were mailed out, 7 of the surveys were returned as 

undeliverable. Of the 59 surveys that were successfully delivered, only 16 surveys were returned 

by actual active fuel dealers or distributors. However, an additional 11 surveys were identified 

as being associated with these 16 fuel dealers/distributors (e.g., duplicates, under common 

ownership, recently purchased, etc.). In addition, another 20 surveys were returned with an 

indication of no fuel sales or distribution. Based on these actual positive and negative responses, 

the nominal fuel survey return rate was nearly 80 percent (i.e., 47 surveys returned out of 59 

delivered). However, examination of the remaining 12 non-respondent surveys points to a 

potentially even higher return rate; a total of 9 of the non-respondent surveys were identified as 

being either definitively out of business or potentially out of business based upon a number of 

factors (e.g., available contact numbers being disconnected, all available contact numbers being 

wrong numbers, no answer after repeated calls, no available contact numbers, etc.). Actual 

contact was only made with 3 of the 12 non-respondent surveys; in spite of this contact, these 3 

companies failed to return the survey.

Based upon the survey results, the following 11 sector/fuel combinations were included 

in the Treasure Valley emissions inventory:

 Industrial distillate oil

 Industrial natural gas

 Industrial LPG

 Commercial/institutional distillate oil

 Commercial/institutional natural gas

 Commercial/institutional LPG

 Commercial/institutional kerosene

 Residential distillate oil

 Residential natural gas

 Residential LPG

 Residential kerosene
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-6

Although the IPP/QPP indicated an expectation that residual fuel oil and coal would be 

sold or distributed in the inventory domain, neither of these fuels were identified in the returned 

surveys. The industrial and commercial/institutional natural gas quantities were adjusted 

downward as part of the point and area source reconciliation based upon the quantities identified 

by point source facilities during the POSST submittal process.

In general, fuel combustion emissions were estimated using emission factors from AP-42 

(U.S. EPA, 1995). Additional emission factors for kerosene combustion and distillate 

combustion (NH3 only) were obtained from other guidance documents (U.S. EPA, 2006; EIIP, 

2004). Two different distillate sulfur contents (i.e., 15 ppm and 500 ppm) were identified by the 

fuel survey respondents; both sulfur contents were used to calculate weighted SOx estimates.

The general equation used to estimate emissions from fuel combustion was:

Where:

Ef,p = Emissions for fuel f and pollutant p (tons/year);

Uf = Fuel usage for fuel f (106ft3or 103gal); and 

EFf,p = Emission factor for fuel f and pollutant p (lb/106ft3or lb/103gal).

A sample calculation using this equation for estimating annual NOx emissions from Ada 

County residential natural gas usage is as follows:

UNG = 9,321 MMscf (i.e., 106ft3) natural gas

EFNG,NOx = 94 lbs NOx/MMscf natural gas

ENG,NOx = 9,321 MMscf × 94 lbs NOx/MMscf natural gas × (1 ton/2,000 lbs)

= 438.1 tons NOx

3.1.2 Residential Wood Combustion

The residential wood combustion source category includes emissions from fireplaces, 

woodstoves, fireplaces with inserts, and pellet stoves. Activity data for residential wood 

combustion were obtained from a residential wood combustion (RWC) survey conducted by 

Aurora (ERG’s subcontractor) (Aurora, 2009). The RWC survey report is included as Appendix

D. The following steps were followed to derive activity data for each county.



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  

2,000 lbs

1 ton Ef ,p Uf EFf ,p
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-7

1. Determine number of existing devices (i.e., fireplace, woodstove/insert, and pellet 

stove) by applying existing device ratio from RWC survey to the number of 

households.

2. Disaggregate number of woodstoves/inserts into number of woodstoves and 

number of inserts using woodstove/insert ratio from RWC survey.

3. Determine number of actively used devices by applying device-specific use ratio 

from RWC survey to number of existing devices.

4. For woodstoves and inserts, determine the number of conventional, catalytic, and 

non-catalytic devices by applying device type ratios from RWC survey to number 

of actively used devices.

5. For each group of devices (i.e., fireplace, woodstove, insert, and pellet stove) 

determine the average wood use (i.e., cordwood and processed log) per device 

using RWC survey response – assumed weight of cordwood is 1.163 tons/cord 

and assumed weight of processed logs is 6 lbs/log. Based upon survey findings, 

the predominant wood type used in fireplaces, woodstoves, and inserts is 

softwood; lesser amounts of hardwood and unspecified wood are also used. Only 

minor amounts of processed wood logs, scrap wood/building materials, and other 

materials are burned. 

 

The general equation used to estimate emissions from residential wood combustion was:

Where:

Ep = Emissions for pollutant p (tons/year);

D = Number of in-use devices;

W = Wood usage per device (tons/yr); and 

EFp = Emission factor for fuel f and pollutant p (lb/ton).

A sample calculation using this equation for estimating annual NOx emissions from Ada 

County residential natural gas usage is as follows:

D = 20,608 in-use fireplaces

W = 0.739 tons wood/device 

EFNOx = 2.6 lbs NOx/ton wood

ENOx = 20,608 in-use fireplaces × 0.739 tons wood/fireplace × 2.6 lbs NOx/ton wood × 

(1 ton/2,000 lbs) = 19.8 tons NOx

Emission factors for the residential wood combustion category were obtained from a 

recent review of residential wood combustion emission factors (Houck and Eagle, 2006).



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

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   

2,000 lbs

1 ton Ep D W EFp
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-8

3.1.3 Paved Road Dust

Fugitive dust from paved roads can be a significant source of PM emissions. In general, 

the factors that affect paved road dust emissions include weight of the vehicles driving on the 

roadway surface, vehicle speed, fine particle (silt) loading on the roadway surface available for 

entrainment, and precipitation on the roadway that decreases road dust emissions. 

In 2010, the 2008, 2015, and 2023 paved road dust emission estimates were completed

for the Treasure Valley by DEQ’s contractor team, ERG/Environ, as part of the SIP-level 

emissions inventories (ERG and Environ, 2010). The paved road dust emissions inventories were 

completed using an emission factor methodology and local data developed during the Treasure 

Valley Road Dust Study (TVRDS) (Etyemezian et al., 2002). DEQ subsequently learned after 

ERG/Environ prepared the 2008 emissions inventories (this report) that the TVRDS paved road 

dust emissions estimates were based on a calibration originally established for unpaved roads, 

not paved roads. This calibration was believed to be appropriate and the best available

approach at the time. However, in studies following the TVRDS when Etyemezian et al. (2002)

recalibrated the system specifically for paved roads, they determined that the 2002 TVRDS 

emission factor measurements in the Treasure Valley were “unreasonably high” in their own 

review of the 2002 study (Langston et al., 2008). As a result, when completing the final emissions 

inventories in support of the Northern Ada County PM10 Limited Maintenance Plan Ten-Year 

Update, DEQ abandoned the 2002 TVRDS emission factors for paved roads and recalculated 

Ada and Canyon counties paved road dust emissions using a new emission factor method 

published in “AP-42 Compilation of Air Pollutant Emission Factors” (EPA, 2011b;

section 13.2.1). However, since the silt loadings measured by Etyemezian et al. (2002) in the 

TVRDS are based on local conditions and are somewhat more conservative than the default silt 

loadings published in the EPA (2011) AP-42 method, the local silt loadings were retained rather 

than using the default loadings in the new AP-42 method. Local PM2.5/PM10 emission fractions 

measured during the TVRDS were also used in the updated calculations to better reflect local 

conditions. This approach is described in Appendix E of the Northern Ada County PM10 Limited 

Maintenance Plan Ten-Year Update, entitled “Development of the Base- and Future-Year 

Mobile Source Emission Inventories for the Treasure Valley, Idaho.” Unpaved road dust 

calibrations from the TVRDS were not flawed (Langston et al., 2008) so unpaved road dust 

estimates made by ERG/Environ were not updated by DEQ in 2012.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-9

Elmore County

Because Elmore County was not included in the TVRDS, paved road dust emission 

estimates for Elmore County were computed by ERG/Environ based upon the AP-42 

methodology (U.S. EPA, 2010a). Although the original Elmore estimates were based on an 

earlier version of the EPA AP-42 method, they were not “unreasonably high” as were Ada and 

Canyon counties estimates based on the TVRDS, so the Elmore County paved road dust 

estimates were not revised. The estimation equation used for Elmore County paved roads is

shown below:

Where:

E = particulate emission factor (g/VMT);

k = particle size multiplier for particle size range and units of interest (g/VMT);

s = road surface silt loading (g/m2);

W = mean vehicle weight (tons);

C = emission factor for 1980's vehicle fleet exhaust, brake wear and tire wear;

P = number of days with at least 0.01 inch of precipitation; and

N = number of days in the averaging period.

The AP-42 default input parameters that were used are shown in Table 3-2 (U.S. EPA, 

2010a). A mean vehicle weight of 3.58 tons was estimated based upon the estimated on-road 

vehicle mix (DEQ, 2006). Silt loading estimates were estimated as shown in Table 3-3.

Table 3-2. Elmore County Paved Road Parameters

Parameter PM10 PM2.5

k (g/VMT) 7.3 1.1

C (g/VMT) 0.2119 0.1617

Table 3-3. Elmore County Silt Loading Estimates

Road Type

Winter Silt 

Loading (g/m2)

Summer Silt 

Loading (g/m2) Source

Arterial 1.9 0.5 Etymezian et al., 2002

Local 4.0 0.4 Etymezian et al., 2002

Freeway 0.015 0.015 DEQ, 2006

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

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 





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













N

P

C

sL W

E k

4

1

2 3

0.6 5 1.5
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-10

The precipitation correction factors for Elmore County were estimated using 2008 

precipitation data from the Western Regional Climate Center (WRCC) (WRCC, 2009). Data 

from the Mountain Home Station (No. 106174) was used. These data are shown in Table 3-4.

Table 3-4. Elmore County Days with at Least 0.01 Inches of Rain

Month Elmore

January 8

February 7

March 7

April 6

May 5

June 4

July 2

August 1

September 2

October 4

November 8

December 8

The resultant paved road dust emission estimates by county are shown in Table 3-5.

Table 3-5. 2008 Annual Paved Road Dust Emission Estimates

County

Annual (TPY)

PM10 PM2.5

Ada Countya7,501 428

Canyon Countya4,154 237

Elmore Countyb1,253 284

a

Ada and Canyon counties paved road dust updated by DEQ in 2012; see Appendix E of

the Northern Ada County PM10 Limited Maintenance Plan Ten-Year Update.

b Elmore road dust original estimates were not needed for Northern Ada County PM10

Limited Maintenance Plan Ten-Year Update and were not updated in 2012.

3.1.4 Unpaved Road Dust

Similar to paved roads, fugitive dust from unpaved roads can be a significant source of 

PM emissions. In general, the processes that affect unpaved road dust emissions include

roadway surface material properties and moisture content, vehicle speed, and precipitation on the 

roadway. Unlike the paved road dust emissions estimates, which were revised by DEQ in 2012, 

the primary source of data used in the development of unpaved road dust emissions remains the 

2002 TVRDS. ERG/Environ developed the 2008 and future year unpaved road dust using the 

original TVRDS methodology. The TVRDS methodology for unpaved roads was not flawed; only 

the calibration factors used for paved roads were flawed. Thus, unpaved road calibration factors 
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-11

were used for the unpaved emission estimates by ERG/Environ and that analysis is described 

below.

Unpaved roadway activity estimates were obtained from a number of sources including 

highway districts (HDs), cities, and COMPASS as shown in Table 3-6. In most cases, the data 

available was limited to unpaved roadway length, although in some cases estimates of average 

daily traffic (ADT) was available. In cases where average daily traffic estimates were not 

available, an ADT estimate was assigned based on existing data as identified in Table 3-6. 

Annual VMT was estimated as unpaved roadway length multiplied by average daily traffic. 

Average speed estimates were not available; therefore, an average speed of 25 mph was assumed 

for all unpaved roads per the TVRDS.

Ada and Canyon Counties

The unpaved road dust emissions estimation methodology was taken from the TVRDS 

for Ada and Canyon counties. Emissions were estimated according to the following equation: 

Where:

EF = roadway PM10 emissions factor (grams PM10/VMT);

b = roadway emissions potential (grams PM10/VMT/mph); and

s = roadway speed (mph).

EF  b s
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-12

Table 3-6. 2008 Unpaved Road Dust Activity Data and Sources

City/Highway District /Area

Length 

(miles)

ADT (vehicles 

per day)

Annual VMT 

(miles) Source

Ada County

Included in TDM 6 36 73,910 Waldinger, 2010

Not in TDM 70 129a3,292,940 Waldinger, 2010

Totals 88 4,220,303

Canyon County

City of Caldwell 11.4 20a82,892 Baker, 2010

City of Greenleaf 0 - 0 Amick, 2010

City of Middleton 0.3c20a2,518 c

City of Melba 0.1c20a371 c

City of Nampa 8.9c20a64,755 c

City of Wilder 0.1 20a438 Lane, 2010

Nampa Highway District 2 30 21,900 Bequeath, 2010

Notus-Parma Highway District 9 20 65,700 Bowman, 2010a

Canyon Highway District 3 67 78,790 Richard, 2010a

Golden Gate Highway District 18 40 259,150 Norris, 2010b

Totals 53 576,514

Elmore County

Atlanta Highway District 54 87.5 1,724,625 Gill, 2010

Mountain Home Highway 

District 291 87.5b9,293,813 Tindall, 2010a

Glenns Ferry Hwy Highway 

District 250 87.5b7,984,375 Gluch, 2010

Totals 595 19,002,813

a

Estimate taken from TVRDS (Etymezian et al., 2002).

b

Assumed equivalent to Atlanta Highway District since these data were not available.

c

Estimated based on average length of unpaved roadway per population identified for other cities.

A dry emissions potential value of 11.9 grams/VMT/mph from TVRDS was used across 

all unpaved roads.

Unpaved road dust precipitation related control estimates were based directly on TVRDS 

observations (Etymezian et al., 2002). Table 3-7 shows the adjustment factors used to account 

for precipitation. It should be noted that although precipitation events might have an effect on 

unpaved roadway activity, data were not available to estimate the influence of such an effect. 

Therefore, while unpaved roadway VMT activity was adjusted for seasonality as described in 

Section 3.2.4, the specific effect that precipitation events may have on unpaved roadway activity 

was not accounted for. Accounting for seasonality as described above is typical for regional 

unpaved road dust emission inventories.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-13

Table 3-7. Unpaved Road Dust Precipitation Adjustments

Month

Fractional 

discount due to 

snow

Fractional discount due 

to precipitation effects

Total fractional 

discount

Dry emissions 

multiplier

January 0.118 0.120 0.237 0.763 

February 0.118 0.113 0.231 0.769 

March 0.118 0.098 0.215 0.785 

April 0.000 0.133 0.133 0.867 

May 0.000 0.119 0.119 0.881 

June 0.000 0.095 0.095 0.905 

July 0.000 0.038 0.038 0.962 

August 0.000 0.038 0.038 0.962 

September 0.000 0.057 0.057 0.943 

October 0.000 0.090 0.090 0.910 

November 0.000 0.161 0.161 0.839 

December 0.000 0.176 0.176 0.824 

Based upon the TVRDS, the PM2.5 fraction of PM10 was estimated to be 0.057 

(Etymezian et al., 2002).

Elmore County

For Elmore County, the AP-42 methodology (U.S. EPA, 2010a) was used to estimate 

unpaved road dust emissions as shown below:

Where:

E = particulate emission factor (lb/VMT);

k, a, c, d = empirical constants;

s = road surface silt content (%);

M = road surface moisture content (%);

S = mean vehicle speed (mph);

C = emission factor for 1980's vehicle fleet exhaust, brake wear and tire wear

(g/VMT);

P = number of days with at least 0.01 inch of precipitation; and

N = number of days in the averaging period.

   

 



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 









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







 













N

N P

C

M

k s S

E

c

a d

0.5

12 30
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-14

The summer and winter road surface material silt content estimates were taken from the 

TVRDS and annual silt content was assumed to be the average of winter and summer silt content 

(Table 3-8). The AP-42 empirical constants, brake and tire wear emission factor estimates, and 

road surface moisture content defaults were used and are shown in Table 3-9.

Table 3-8. Elmore County Unpaved Road Surface Silt Content

Description Silt Content (%)

Summer 3.5

Winter 1.4

Annual average 2.45

Table 3-9. Unpaved Emissions Estimation Parameters

Parameter AP-42 Default

k – PM10 (lb/VMT) 1.8

k – PM2.5 (lb/VMT) 0.18

a 1

d 0.5

c 0.2

M (%) 0.5

C – PM10 (g/VMT) 0.00047

C – PM2.5 (g/VMT) 0.00036

The days of precipitation greater than 0.01 inches estimated for Elmore County paved 

roads (see Table 3-4) was also used for Elmore County unpaved roads. 

The resultant emission estimates by county are presented in Table 3-10. Elmore County 

contains the highest unpaved roadway mileage and therefore has the highest unpaved road dust 

emission estimates of the three counties in the Treasure Valley.

Table 3-10. 2008 Annual Unpaved Road Dust Emission Estimates

County

Annual (TPY)

PM10 PM2.5

Ada 966 55

Canyon 165 9

Elmore 2,648 262

Totals 3,779 327

3.1.5 Commercial Cooking

The commercial cooking category includes five subcategories: conveyerized (or chaindriven) charbroiling, under-fired charbroiling, deep fat frying, flat griddle frying, and clamshell 

griddle frying. 
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-15

Commercial cooking emissions were estimated using the methodology (e.g., national 

average number of equipment pieces, meat cooking quantities, etc.) and associated emission 

factors presented in the 2002 National Emissions Inventory documentation (U.S. EPA, 2006). 

The number of county-level establishments was obtained from 2007 County Business Patterns

(U.S. Census, 2009a). The types of restaurant were determined from the 2002 Economic Census 

(U.S. Census, 2005a).

The equation for estimating emissions from each of the commercial cooking 

subcategories is the following is:

Where:

Ep = Emissions for pollutant p (tons/year);

EFp = Emission factor for pollutant p (lbs/ton meat cooked);

EQ = Number of pieces of equipment; and

M = Annual meat cooked per piece of equipment (tons meat cooked/equipment-year).

A sample calculation using this equation for estimating annual VOC emissions from

chain-driven charbroilers is as follows:

EFVOC = 4 lbs VOC/ton meat cooked

EQ = 892 chain-driven charbroilers

M = 1,623.6 lbs meat/equipment-week × 52 weeks = 84,427.2 lbs/equipment-year

EVOC = 892 × 84,427.2 lbs/equipment-year × 4 lbs VOC/ton meat × (1 ton VOC/2,000 

lbs VOC) = 75.3 tons VOC

3.1.6 Construction

County-level residential building permit data were obtained from the U.S. Census (U.S. 

Census, 2010). Construction durations and construction dust emission factors were obtained 

from the 2002 NEI methodology document for the following residence types: single family, two 

family, three and four family, and five or more family units (U.S. EPA, 2006). Discussions with 

government agencies that issue building permits indicated that industrial and commercial 

building activity during 2008 was minimal and that relevant activity data were not available

(Webb, 2009; Radek, 2009; Hunter, 2009; Winterfield, 2009).



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   

2,000 lbs

1 ton Ep EFp EQ M
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-16

3.1.7 Architectural Surface Coatings

The architectural surface coatings category was estimated following the hybrid approach 

outlined in the 2002 NEI methodology document (U.S. EPA, 2006). The hybrid approach 

utilized national-level emissions that were scaled down using both county-level population and 

county-level employee statistics. The scaling was weighted 40 percent for population and 60 

percent for employees. The employee portion of the scaling was conducted in the same manner 

as industrial surface coating (Section 3.1.9), degreasing (Section 3.1.10), and other per employee 

source categories (Section 3.1.11) and was based on employee counts for NAICS 238320 

(Painting and Wall Covering Contractors).

3.1.8 Traffic Markings

Usage quantities of traffic markings within the three-county area, as well as relevant 

material safety data sheets (MSDS) and product specifications, were obtained through telephone 

contacts with nine different government agencies (i.e., Idaho Transportation Department, county 

highway departments, city public works departments, and local highway districts). The 

identified traffic marking usage quantities were 45,250 gallons for Ada County, 40,381 gallons 

for Canyon County, and 6,590 gallons for Elmore County. The MSDSs and product 

specifications indicated various VOC contents; however, 150 grams per liter (g/l) was the most

prevalent. Therefore, this VOC content was used for the estimating emissions. Emissions were 

calculated using the methodologies identified in the EIIP guidance document (EIIP, 1997b).

3.1.9 Industrial Surface Coating

The industrial surface coating category consists of 13 subcategories (e.g., factory finished 

wood, wood furniture, plastic products, etc.) that were inventoried for the Treasure Valley 

inventory. These subcategories were all estimated by ratioing emission estimates from the 2002 

NEI. Each of the 13 industrial surface coating subcategories were assigned a specific NAICS 

code for which county-level employee data for 2002 and 2007 were obtained from County 

Business Patterns (U.S. Census, 2009a). Employee data were not available for 2008, so it was 

assumed that 2007 employee data were a reasonable approximation of 2008 employee data.

The specific county-level NAICS code assignments for the 13 industrial surface coating 

subcategories are shown in Table 3-11. The 2007 employee data were adjusted downward based 
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-17

upon employee counts obtained from telephone contacts with permitted point sources having 

NAICS codes relevant to the industrial surface coating area source category. These adjustments 

are also indicated in Table 3-11. 

Table 3-11. NAICS Code Assignments for Industrial Surface Coating 

Subcategories

Industrial Surface Coating Subcategory NAICS Codes

Factory Finished Wood 321XXX (Wood Product Manufacturing)a

Wood Furniture 337XXX (Furniture and Related Product Manufacturing)b

Metal Furniture 337XXX (Furniture and Related Product Manufacturing)b

Paper 322XXX (Paper Manufacturing)c

Plastic Products 326XXX (Plastics and Rubber Products Manufacturing)

Miscellaneous Finished Metals 332XXX (Fabricated Metal Product Manufacturing)b

Machinery and Equipment 333XXX (Machinery Manufacturing)

Electronic and Other Electrical 334XXX (Computer and Electronic Product Manufacturing)a

Motor Vehicles 3362XX (Motor Vehicle Body and Trailer Manufacturing)c

Aircraft 3364XX (Aerospace Products and Parts Manufacturing)

Marine 3366XX (Ship and Boat Building)

Railroad 3365XX (Railroad Rolling Stock Manufacturing)b

Miscellaneous Manufacturing 31XXXX (Manufacturing)

aEmployee counts adjusted downward for Ada and Canyon counties.

bEmployee counts adjusted downward for Ada County.

aEmployee counts adjusted downward for Canyon County.

The Area Source Matrix previously presented in the IPP/QAP indicated that emission 

factors from EIIP guidance would be used for all industrial surface coating subcategories. As 

discussed for other categories above, it was felt that the per capita factors from the 2002 NEI 

documentation would be more representative of current conditions associated with industrial 

surface coating since the EIIP guidance is from 1997. 

The general equation used to estimate emissions for the industrial surface coating 

subcategories was:

Where:

E2007 = Emissions for 2007 inventory year (tons/year);

E2002 = Emissions for 2002 inventory year (tons/year);

EM2007 = Employees for 2007 inventory year (adjusted for point source employment, if 

necessary) (people); and

EM2002 = Employees for 2002 inventory year (people).

















 

2002

2007

2007 2002 EM

EM

E E
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-18

A sample calculation using this equation for estimating annual VOC emissions from 

factory finished wood industrial surface coating in Ada County is as follows:

E2002 = 79.9 tons VOC

EM2002 = 883 people

EM2007 = 1,029 people

E2007 = 79.9 tons VOC × (1,029 people/883 people) = 93.1 tons VOC

3.1.10 Degreasing

The degreasing category consists of open top degreasing and cold cleaning for 13 sectors 

(e.g., furniture and fixtures, primary metal industries, fabricated metal products, etc.) for a total of 26 

subcategories that were inventoried for the Treasure Valley inventory. As with industrial surface 

coating, these subcategories were estimated by ratioing emission estimates from the 2002 NEI with 

employee count data. Each of the 26 degreasing subcategories were assigned a specific NAICS code 

for which county-level employee data for 2002 and 2007 were obtained from County Business 

Patterns (U.S. Census, 2009a). Employee data were not available for 2008, so it was assumed that 

2007 employee data were a reasonable approximation of 2008 employee data.

The specific county-level NAICS code assignments for the 26 degreasing subcategories are 

shown in Table 3-12. The 2007 employee data were adjusted downward based upon employee 

counts obtained from telephone contacts with permitted point sources having NAICS codes relevant 

to the degreasing area source categories. These adjustments are also indicated in Table 3-12.

Table 3-12. NAICS Code Assignments for Degreasing 

Degreasing Subcategory

(Open Top Degreasing and Cold Cleaning) NAICS Codes

Furniture and Fixtures 337XXX (Furniture and Related Product Manufacturing)a

Primary Metal Industries 331XXX (Primary Metal Manufacturing)

Secondary Metal Industries 331XXX (Primary Metal Manufacturing)

Fabricated Metal Products 332XXX (Fabricated Metal Product Manufacturing)a

Industrial Machinery and Equipment 333XXX (Machinery Manufacturing)

Electronic and Other Electrical 334XXX (Computer and Electronic Product Manufacturing)b

335XXX (Electrical Equipment, Appliance, and Component Manufacturing)

Transportation Equipment 336XXX (Transportation Equipment Manufacturing)b

Instruments and Related Products 3345XX (Navigational, Measuring, Electromedical and Control Instruments 

Manufacturing)

Miscellaneous Manufacturing 339XXX (Miscellaneous Manufacturing)

Transportation Maintenance Facilities 488XXX (Support Activities for Transportation)

Automotive Dealers 4411XX (Automobile Dealers)

Auto Repair Services 8111XX (Automotive Repair and Maintenance)a

Miscellaneous Repair Services 811XXX (Repair and Maintenance) except

8111XX (Automotive Repair and Maintenance)

aEmployee counts adjusted downward for Ada County.

bEmployee counts adjusted downward for Ada and Canyon counties.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-19

The Area Source Matrix previously presented in the IPP/QAP indicated that emission 

factors from EIIP guidance would be used for all of the degreasing subcategories. As discussed 

for other categories above, it was felt that the per capita factors from the 2002 NEI 

documentation would be more representative of current conditions associated with degreasing 

since the EIIP guidance is from 1997. 

The general equation used to estimate emissions for the degreasing subcategories was:

Where:

E2007 = Emissions for 2007 inventory year (tons/year);

E2002 = Emissions for 2002 inventory year (tons/year);

EM2007 = Employees for 2007 inventory year (adjusted for point source employment, if 

necessary) (people); and

EM2002 = Employees for 2002 inventory year (people).

A sample calculation using this equation for estimating annual VOC emissions from 

furniture and fixture open top degreasing in Ada County is as follows:

E2002 = 12.6 tons VOC

EM2002 = 325 people

EM2007 = 566 people

E2007 = 12.6 tons VOC × (566 people/325 people) = 21.9 tons VOC

3.1.11 Other Per Employee Emission Factor Source Categories

In addition to industrial surface coating and degreasing, there were three other area 

source categories that were estimated using employee counts and per employee emission factors. 

These categories were autobody refinishing, industrial refrigeration/cold storage (NH3), and 

graphic arts.

County-level employee data were obtained from County Business Patterns (U.S. Census, 

2009a) for 2007; employee data were not available for 2008, so it was assumed that 2007 

employee data were a reasonable approximation of 2008 employee data. The specific countylevel NAICS code assignments for autobody refinishing, industrial refrigeration/cold storage, 

and graphic arts are shown in Table 3-13. For autobody refinishing and graphic arts, the 2007 

employee data were adjusted downward based upon employee counts obtained from telephone 



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





 

2002

2007

2007 2002 EM

EM

E E
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-20

contacts with permitted point sources having relevant NAICS codes. These adjustments are also 

indicated in Table 3-13.

Table 3-13. NAICS Code Assignments for Autobody Refinishing, Industrial 

Refrigeration/Cold Storage, and Graphic Arts Categories

Category NAICS Codes

Autobody Refinishing 492XXX (Couriers and Messengers)

5321XX (Automotive Equipment Rental and Leasing)

8111XX (Automotive Repair and Maintenance)a

Industrial Refrigeration/

Cold Storage

31132X (Chocolate and Confectionery Manufacturing from Cacao Beans)

31133X (Confectionery Manufacturing from Purchase Chocolate)

3114XX (Fruit and Vegetable Preserving and Specialty Food Manufacturing)

3115XX (Dairy Product Manufacturing)

3116XX (Animal Slaughtering and Processing)

3117XX (Seafood Product Preparation and Packaging)

31181X (Bread and Bakery Product Manufacturing)

311991 (Perishable Prepared Food Manufacturing)

311999 (Other Miscellaneous Food Manufacturing)

3121XX (Beverage Manufacturing)

325211 (Plastics Material and Resin Manufacturing)

493120 (Refrigerated Warehousing and Storage)

Graphic Arts 3222XX (Converted Paper Product Manufacturing)b

32311X (Printing)

aEmployee counts adjusted downward for Ada County.

bEmployee counts adjusted downward for Canyon County.

For autobody refinishing and graphic arts, the per employee emission factors were 

obtained from the 2002 NEI documentation (U.S. EPA, 2006). The Area Source Matrix 

previously presented in the IPP/QAP indicated that emission factors from EIIP guidance would 

be used for these categories (i.e. per employee factors for autobody refinishing and per capita 

factors for graphic arts). As discussed for other categories above, it was felt that the per capita 

factors from the 2002 NEI documentation would be more representative of current conditions. 

The per employee emission factor for industrial refrigeration/cold storage was obtained from 

EIIP ammonia guidance for anthropogenic nonagricultural sources (EIIP, 2004). 

The general equation used to estimate emissions for categories using per employee 

emission factors was:













  

2,000 lbs

1 ton E EF EM
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Final, August 31, 2010

3-21

Where:

E = Emissions (tons/year);

EF = Per capita emission factor (lbs/person-year); and

EM = Employees (people).

A sample calculation using this equation for estimating annual NH3 emissions from Ada 

County cold storage is as follows:

EM = 635 people

EF = 30 lbs NH3/person

E = 635 people × 30 lbs NH3/person × (1 ton/2,000 lbs) = 9.5 tons NH3

3.1.12 Bakeries and Consumer Solvents

Two source categories were estimated using per capita emission factors. These 

categories were bakeries and consumer solvents (e.g., personal care products, household 

products, etc.).

County-level population data were obtained from the U.S. Census (U.S. Census, 2009b). 

For bakeries, an annual per capita bread consumption rate of 70 lbs of bread/person was 

combined with an emission factor of 5 lbs VOC per 1,000 lbs of sponge-dough bread produced. 

Both the emission factor and the consumption rate were obtained from EIIP guidance (EIIP, 

1999). The per capita emission factors for consumer solvents were obtained from the 2002 NEI 

documentation (U.S. EPA, 2006). The Area Source Matrix previously presented in the IPP/QAP 

indicated that the per capita emission factors from EIIP guidance would be used for consumer 

solvents; however, the EIIP guidance for consumer solvents is from 1996 and it was felt that the 

per capita factors from the 2002 NEI documentation would be more representative of current 

conditions associated with consumer solvents.

The general equation used to estimate emissions for categories using per capita emission 

factors was:

Where:

E = VOC emissions (tons/year);

EF = VOC per capita emission factor (lbs/person-year); and

P = Population (people).



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



  

2,000 lbs

1 ton E EF P
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Final, August 31, 2010

3-22

A sample calculation using this equation for estimating annual VOC emissions from Ada 

County consumer products (personal care products) is as follows:

P = 380,920 people

EF = 2.04 lbs VOC/person

E = 380,920 people × 2.04 lbs VOC/person × (1 ton/2,000 lbs) = 388.5 tons VOC

3.1.13 Dry Cleaning

Activity data for dry cleaning were collected using a mail-out survey (included as

Appendix C) that was sent to dry cleaners located in Ada, Canyon, and Elmore counties in 

October 2009. Additional follow-up was conducted via phone during in January 2010. A total 

of 24 dry cleaners were identified as conducting on-site cleaning in the three counties. Of these 

24 dry cleaners, 13 exclusively used perchloroethylene, 10 exclusively used petroleum solvents, 

and 1 used both perchloroethylene and petroleum solvents. Since perchloroethylene is not a 

VOC species, it was not included in the emission calculations. The petroleum solvents used by 

the 11 petroleum solvent dry cleaners included Stoddard solvent, ECOSOLV, and DF-2000. A 

total of 1,815 gallons of petroleum solvent were identified for Ada County; while a total of 600 

gallons of petroleum solvent were identified for Canyon County. Only two dry cleaners 

identified solvent being sent off-site; for both of these facilities, the off-site quantities exceeded 

the purchase statistics, so the purchase statistics for these facilities were excluded. Solvent 

densities were obtained from material safety data sheets (MSDSs) provided by the dry cleaners. 

It was assumed that purchase statistics were equal to emissions (i.e., all purchased solvent was 

used and subsequently evaporated). 

3.1.14 Asphalt Application

Usage quantities of asphalt within the three-county area, as well as relevant material 

safety data sheets (MSDS) and product specifications, were obtained through telephone contacts 

with 11 different government agencies. These government agencies included the following:

 Idaho Transportation Department (ITD), District 3 (Morrison, 2010a)

 Highway districts:

 Ada County Highway District (including City of Boise) (Nobel, 2010)

 Nampa (Canyon County) Highway District No. 1 (Kennedy, 2010)

 Notus-Parma (Canyon County) Highway District No. 2 (Bowman, 2010b)

 Golden Gate (Canyon County) Highway District No. 3 (Norris, 2010b)
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-23

 Canyon (Canyon County) Highway District No. 4 (Richard, 2010c)

 Mountain Home (Elmore County ) Highway District (Tindall, 2010b)

 City public works departments:

 City of Caldwell Streets Department (Caldwell, 2010)

 City of Middleton Public Works Department (Green, 2010)

 City of Mountain Home Public Works Department (Harvel, 2010)

 City of Nampa Public Works Department (Barr, 2010)

Usage quantities were collected for hot mix asphalt, emulsified asphalt, and cutback 

asphalt. However, based upon the survey-based methodologies identified in EIIP guidance 

documents (EIIP, 2001a), emissions were only estimated for emulsified asphalt and cutback 

asphalt (i.e., emissions are typically not estimated for hot mix asphalt and an appropriate 

methodology was not identified). 

Most of the asphalt applied in the three-county area is hot mix asphalt. Five agencies 

(i.e., ITD District 3, Nampa Highway District No. 1, City of Middleton, City of Mountain Home, 

and City of Nampa) used hot mix asphalt exclusively. Only two agencies (i.e., Golden Gate 

Highway District No. 3 and Mountain Home Highway District) identified any cutback asphalt 

usage with a total of only 75 tons. Emulsified asphalt usage was identified in four agencies (i.e., 

Ada County Highway District, Golden Gate Highway District No. 3, Canyon Highway District 

No. 4, and Mountain Home Highway District) with a total of 7,875 tons.

Asphalt usage could not be obtained from Notus-Parma Highway District No. 2 and the 

City of Caldwell. Consideration was given to gap fill the missing data for these two agencies, 

but a reasonable approach could not be identified. For the City of Caldwell, asphalt data from 

the other three cities contacted was limited to hot mix asphalt, so there was no basis for 

extrapolation of cutback or emulsified asphalt. For Notus-Parma Highway District No.2, data 

from the three other highway districts in Canyon County were examined. However, these three 

highway districts did not provide a reasonable set of data to base a gap filling extrapolation upon 

(i.e., hot mix asphalt only for Nampa Highway District No. 1, emulsified and cutback asphalt for 

Golden Gate Highway District No. 3, and emulsified asphalt only for Canyon Highway District 

No. 4.). 
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

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A number of assumptions from the EIIP guidance were used to calculate emissions (EIIP, 

2001a). The cutback asphalt was assumed to be medium cure cutback and the emulsified asphalt 

was assumed to be medium set emulsified. In addition, asphalt densities of 7.8 lb/gal and 8.34 

lb/gal were assumed for cutback and emulsified, respectively. Likewise, diluent densities of 6.67 

lb/gal (cutback) and 8.34 lb/gal (emulsified) were also assumed. It was assumed that the diluent 

content of cutback asphalt was 35 percent (EIIP, 2001a), while recent research has indicated that 

the diluent content of emulsified asphalt is approximately 12 percent (Midwest, 2006). Finally, 

it was assumed that 75 percent of the cutback diluent evaporated, while 100 percent of the 

emulsified diluent evaporated.. 

Ozone seasonal daily emissions were estimated by dividing annual emissions by the 

number of days in the ozone season (i.e., 214 days). All of the agencies contacted indicated that 

asphalt application is typically not conducted during the PM season, so PM seasonal daily 

emissions were not calculated.

3.1.15 Pesticide Application

Emissions from agricultural pesticide application were estimated as indicated in the 

IPP/QAP Area Source Matrix. Planted crop acreage data were obtained from the 2007 Census of 

Agriculture (USDA, 2009). Pesticide application information (i.e., fraction of acreage applied, 

quantity of active ingredient per acre, and applications per year) were obtained from crop 

profiles: however, only 11 crop profiles were available (i.e., apples, barley, dry beans, sweet 

corn, lentils, mint, dry peas, green peas, potatoes, sugar beets, and wheat) (IPM Center, 2010). 

Only pesticides with application rates in terms of pounds per acre were considered; pesticides 

with unusual application rates (e.g., ounces per hundredweight of seed, ounces per linear row, 

etc.) were not included. Emissions were estimated using the methodology outlined in the EIIP 

guidance (EIIP, 2001c). Typical pesticide characteristics (i.e., percent active ingredient and 

formulation type) were obtained from a pesticide database (PAN, 2010). Wherever possible, the 

product names and/or formulation types indicated by the IPM Center crop profiles were 

followed. If assumptions were made for specific pesticides, then pesticides with an active U.S. 

product regulatory status were selected.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-25

Emissions were estimated using the methodology outlined in the EIIP guidance (EIIP, 

2001c). Typical pesticide characteristics (i.e., percent active ingredient and formulation type) 

were obtained from a pesticide database (PAN, 2010). Wherever possible, the product names 

and/or formulation types indicated by the IPM Center crop profiles were followed. If 

assumptions were made for specific pesticides, then pesticides with an active U.S. product 

regulatory status were selected.

The equation for estimating emissions from pesticide application was as follows:

Where:

Ep,t = Total emissions from pesticide p (tons VOC/year);

Ep,a = Emissions from active ingredient of pesticide p (tons VOC/year);

Ep,i = Emissions from inert ingredient of pesticide p (tons VOC/year);

Rp = Application rate of pesticide p (lbs/acre-year);

Ap = Harvested acreage that had application of pesticide p (acres);

ap = Percent of active ingredient in pesticide p (%);

EFp = Emission factor for active ingredient in pesticide p (lbs/ton);

ip = Percent of inert ingredient in pesticide p (%); and

Vp = Volatile content of inert fraction of pesticide p (%). 

A sample calculation using this equation for estimating annual VOC emissions from the 

application of Bravo 500 (active ingredient chlorothalonil) on potatoes in Elmore County is as 

follows:

Rp = 9.282 lbs/acre-year

Ap = 8,967 acres × 0.60 (application fraction) = 5,380.2 acres

ap = 40.4 percent active ingredient

ip = 59.6 percent inert ingredient

Vp = 56 percent volatile content of inert ingredient

EFp = 1,160 lbs VOC/ton active ingredient applied (vapor pressure 1 × 10-3 mmHg)

Ep,a = 9.282 lbs/acre-year × 5,380.2 acres × 0.404 × 1,160 lbs VOC/ton active 

ingredient applied × 1 ton VOC/2,000 lbs VOC = 5.85 tons VOC

Ep,I = 9.282 lbs/acre-year × 5,380.2 acres × 0.596 × 0.56 × 1 ton VOC/2,000 lbs VOC 

= 8.34 tons VOC

Ep,t = Ep,a + Ep,i = 5.85 tons VOC + 8.34 tons VOC = 14.19 tons VOC



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     

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





      

2,000 lbs

1 ton R A i V

2,000 lbs

1 ton Ep,t Ep,a Ep,i Rp Ap

ap EFp p p p p
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-26

3.1.16 Gasoline Distribution

State-level gasoline consumption statistics were obtained from the Idaho Tax 

Commission (Walters, 2010). These state-level gasoline statistics were disaggregated down to 

the individual county-level based upon 2008 population estimates (U.S. Census, 2009b). 

Although 24 gasoline stations were identified as exceeding DEQ’s point source thresholds, all 

gasoline stations were kept in the gasoline distribution area source category in order to avoid 

potential modeling difficulty.

Emission factors for underground tank filling (Stage I), breathing and emptying losses, 

and tank truck transit losses were obtained from EIIP guidance (EIIP, 2001b). It was assumed 

that the Stage I underground tank filling was submerged fill throughout Ada, Canyon, and 

Elmore counties. Refueling (Stage II) emission factors were developed from MOBILE6 input 

files used by ENVIRON in their on-road motor vehicle analysis (Grant, 2010).

The equation for estimating emissions from gasoline distribution is as follows:

Where:

E = Emissions (tons VOC/year);

EF = Emission factor (lbs/gal throughput); and

T = Annual fuel throughput (gal/year).

A sample calculation using this equation for estimating annual VOC emissions from Ada 

County Stage I underground tank filling is as follows:

T = 151,687,674 gallons (or 151,687.674 × 103gallons)

EF = 7.3 lbs VOC/103gallons

E = 151,687.674 × 103gallons × 7.3 lbs VOC/103gallons × (1 ton/2,000 lbs) = 553.7

tons VOC

3.1.17 Wastewater Treatment

Activity data for wastewater treatment were collected using a mail-out survey (included 

as Appendix C) was that sent to wastewater treatment facilities located in Ada, Canyon, and 

Elmore counties in October 2009. A total of 17 surveys were mailed out of which 14 surveys 

were returned that identified the monthly quantities of wastewater treated. Additional follow-up 



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  

2,000 lbs

1 ton E EF T
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-27

was attempted for the three non-respondent facilities (i.e., Glenns Ferry, Kuna, and Notus), but 

contact could not be made. Since these non-respondent facilities are located in small 

communities, they are likely comparatively small facilities and their missing data is unlikely to 

affect the overall uncertainty of the emission estimates. In addition, the wastewater quantities 

from the Eagle Sewer District Treatment Plant were not included since effluent from that facility 

is pumped to the West Boise Wastewater Treatment Plant for further processing. The emission 

factors were obtained from the 2002 NEI documentation report (U.S. EPA, 2006).

It should be noted that the WATER9 model was identified as the wastewater treatment 

source category methodology in the IPP/QAP Area Source Matrix. However, further 

investigation revealed that the collection of the activity data needed to run WATER9 was

extensive and it would be infeasible to collect for all of the wastewater treatment facilities 

located in Ada, Canyon, and Elmore counties. Therefore, the alternate emission factor 

methodology described above was used to estimate emissions from wastewater treatment.

3.1.18 Landfills

Landfill gas is generated by microorganism within the landfill under anaerobic 

conditions. The primary landfill gas constituents are methane (CH4) and carbon dioxide (CO2); 

however, lesser amounts of VOC are also generated either from decomposition products or the 

volatilization of biodegradable wastes.

Activity data for landfills were collected using a mail-out survey (included as Appendix

C) that was sent to landfills located in Ada, Canyon, and Elmore counties in October 2009. A 

total of 14 surveys were mailed out. However, not all locations identified as landfills were 

actually landfills (e.g., slash piles, illegal dump sites, etc.). Only 3 surveys were returned: Ada 

County Landfill (i.e., Hidden Hollow), Pickles Butte Sanitary Landfill (Canyon County), and 

Mountain Home AFB (Elmore County). Emissions calculations for these three landfills 

confirmed that none of them exceed the VOC point source threshold of 10 tpy VOC. Therefore, 

emissions from these landfills were inventoried as an area source.

Emissions were estimated using the methodology outlined in Section 2.4 of AP-42 (U.S. 

EPA, 2010). This methodology is based on a theoretical first-order kinetic model of CH4

production.
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Final, August 31, 2010

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The equations for estimating emissions from landfills are as follows:

Where:

QCH4 = Methane generation rate at time t (m3/yr);

Lo = Methane generation potential (m3 CH4/Mg) (default value of 100 m3 CH4/Mg);

R = Average annual refuse acceptance rate during active life (Mg/yr);

k = Methane generation rate constant (yr-1) (default value of 0.02);

c = Time since landfill closure (years); and

t = Time since the initial refuse placement (years).

Where:

QVOC = Emission rate of VOC (m3/yr);

CVOC = Concentration of VOC in landfill gas (ppmv) (default value of 835 ppmv); and

CCH4 = Concentration of CH4 in landfill gas (assumed to be 50% expressed as 0.5).

Where:

UMVOC = Uncontrolled mass emissions of VOC (kg/yr);

QVOC = Emission rate of VOC (m3/yr);

MWVOC = Molecular weight of VOC (g/gmol) (default value of 86.18 as hexane); and

T = Temperature of landfill gas (°C).

A sample calculation using these equations for estimating annual VOC emissions from 

the Ada County Landfill is as follows:

Lo = 100 m3 CH4/Mg

R = 299,420 Mg refuse/year

k = 0.02

c = 0 years (active landfill)

t = 35 years

QCH4 = 1.3(100 m3 CH4/Mg)( 299,420 Mg refuse/year)(e-[0.02 × 0]– e

-[0.02 × 35]) = 

19,595,216 m3/yr CH4

 

kc kt

CH o Q L R e e

 

4 1.3   

(1 10 )

6

4

4

 





CH

CH VOC

VOC C

Q C

Q

 

(273 T)

kg

1000 g

gmol - K

0.00008205 m - atm

1atm

3

  

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 

VOC

VOC VOC

MW

UM Q
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

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CVOC = 835 ppmv

CCH4 = 0.5

QVOC = (19,595,216 m3/yr CH4 × 835 ppmv)/(0.5 × 1,000,000) = 32,724 m3 VOC/yr

MWVOC = 86.18 g/gmol

T = 25 °C

UMVOC = [(32,724 m3 VOC/yr)( 86.18 g/gmol)(1 atm)]/{(0.00008205 m3-atm/gmolK)(1000 g/1 kg)(273 + 25K)} = 5,038 kg VOC/yr = 5.6 ton VOC/yr

3.1.19 Open Burning (Yard Waste and Household Waste)

The methodology identified in the IPP/QAP Area Source Matrix was tentatively 

identified as a mass balance approach which incorporates waste generation rates and local 

landfilling and recycling rates. Some landfilling information was available; however, in general, 

it was not possible to positively distinguish between local landfill material (i.e., originating in 

Ada, Canyon, or Elmore counties) and landfill material originating outside of the three-county 

area. In addition, conversations with Ada County Solid Waste Management Department staff 

indicate that open burning activity, as reflected by public nuisance complaints, has dramatically 

decreased in recent years. Furthermore, concerns over air quality and fire hazards have also 

affected the public acceptance level of open burning (Hutchinson, 2010). Therefore, an 

alternative methodology was used to estimate open burning emissions.

The city and county codes were examined for all government entities located within Ada, 

Canyon, and Elmore counties. The codes were examined for mandatory residential waste 

collection requirements and prohibitions of household and/or yard waste burning. This 

examination was greatly facilitated by the availability of city/county codes on-line. The Boise city 

code was available from the City of Boise website (Boise, 2010). The city/county codes for 14 

other government entities (i.e., Caldwell, Eagle, Garden City, Greenleaf, Kuna, Meridian, 

Middleton, Mountain Home, Nampa, Parma, Star, Wilder, Ada County, and Canyon County) were 

maintained on-line by a codifying company (Sterling, 2010). The city/county codes for only four 

government entities (i.e., Glenns Ferry, Melba, Notus, and Elmore County) could not be identified. 

Based on the review of these city/county codes, the following information was determined:

 Mandatory residential waste collection

 Required in most areas located within Ada, Canyon, and Elmore counties

 Not explicitly required in Glenns Ferry, Greenleaf, Melba, Notus, Parma, Star, 

and the unincorporated portions of Canyon and Elmore counties
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 Household waste burning

 Explicitly banned in most areas located within Ada, Canyon, and Elmore 

counties

 Not explicitly banned in Glenns Ferry, Greenleaf, Melba, Notus, and the 

unincorporated portion of Elmore County

 Yard waste burning

 Explicitly banned in only a few areas (i.e., Boise, Caldwell, Meridian, Nampa, 

and the unincorporated portion of Ada County)

 Allowed in the other areas subject to necessary burn permits (typically from local 

fire agencies) and sufficiently low air quality index (AQI) values.

It was assumed that household waste (i.e., municipal solid waste) and yard waste burning 

was conducted in all areas without explicit codified bans. National per capita waste generation 

rates for 2008 were derived from national statistics (U.S. EPA, 2009a). The per capita yard 

waste generation was reduced by 50 percent to account for the grass clippings portion which is 

typically not burned. These per capita waste generation rates were applied to the populations in 

the non-ban areas (i.e., 18,691 for household waste burning and 139,846 for yard waste burning). 

Based upon the methodology used in the 2002 NEI, it was assumed that 28 percent of the 

household and yard waste generated was actually burned (U.S. EPA, 2006). Emission factors for 

the residential and yard waste burning were obtained from the documentation from the 2002 

National Emissions Inventory (U.S. EPA, 2006).

The equation for estimating emissions open burning (household waste or yard waste) is:

Where:

Ep = Emissions for pollutant p (tons/year);

BF = Fraction of generated waste burned;

W = Per capita waste generation rate (tons/person-day);

P = Population (people); and 

EFp = Emission factor for pollutant p (lbs/ton).

A sample calculation using this equation for estimating annual VOC emissions from 

Elmore County household waste burning is as follows:

BF = 28% of generated waste is burned

W = 3.18 lbs waste/day

P = 16,615 people without household waste burning bans 

  











    

2,000 lbs

1 ton Ep BF W P EFp
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Final, August 31, 2010

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EFp = 30 lbs VOC/ton waste

E = 0.28 × 3.18 lbs waste/person-day × 16,615 people × 366 days/year × 1 ton 

waste/2,000 lbs waste × 30 lbs VOC/ton waste × (1 ton/2,000 lbs) = 40.6 tons 

VOC

3.1.20 Agricultural Tilling and Harvesting

Emissions from both agricultural tilling and agricultural harvest operations were 

estimated using per-acre emission factors developed by the California Air Resources Board 

(CARB, 2003a; CARB, 2003b). It was assumed that these per-acre emission factors provide a 

reasonable approximation of conditions in the Treasure Valley. Planted and harvested crop 

acreage data were obtained from the 2007 Census of Agriculture (USDA, 2009).

The equation for estimating emissions from agricultural tilling and harvest activities is as 

follows:

Where:

Ec = Emissions for crop c (tons PM10/year);

EFc = Emission factor for crop c (lbs PM10/acre planted/harvested); and

Ac = Acres planted/harvested for crop c (acres/year). 

A sample calculation using this equation for estimating annual PM10 emissions from 

sugarbeet tilling in Ada County household waste burning is as follows:

EFc = 22.8 lbs PM10/acre planted

Ac = 1,976 planted acres of sugarbeets 

E = 1,976 acres × 22.8 lbs PM10/acre × 1 ton/2,000 lbs = 22.5 tons PM10

3.1.21 Agricultural Burning – Fields

As part of the recently implemented Crop Residue Burning Program, agricultural field 

burning was only allowed between September 1 and October 31, 2008. County-level field 

burning acreage statistics for the Southwest Idaho Burn Management Area were obtained from 

DEQ staff (Pettit, 2009). Field burning acreage was limited to 29.2 acres of cereal grains in Ada 

County and 202 acres of other crops in Canyon County. For estimation purposes, backfired 

wheat fuel loading and emission factors were assumed for the Ada County cereal grain acreage. 

Likewise, backfired alfalfa loading and emission factors were assumed for the Canyon other 













  

2,000 lbs

1 ton Ec EFc Ac
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acreage. Fuel loadings and emissions were estimated using appropriate emission factors from 

AP-42 (U.S. EPA, 2010a).

The equation for estimating emissions from agricultural open burning is as follows:

Where:

Ep,c = Emissions for pollutant p and crop c (tons/year);

ABc = Acreage burned for crop c (acres/year);

FLc = Fuel loading for crop c (tons/acre); and

EFp,c = Emission factor for pollutant p and crop c (lbs/ton).

A sample calculation using this equation for estimating annual CO emissions from field 

burning of other crops in Canyon County is as follows:

AB = 202 acres other crops (assumed to be alfalfa)

FL = 0.8 tons/acre 

EFp,c = 119 lbs CO/ton

E = 202 acres × 0.8 tons/acre × 119 lbs CO/ton × 1 ton/2,000 lbs = 9.6 tons CO

3.1.22 Agricultural Burning – Irrigation Ditches

An additional source of agricultural burning that was not identified in the IPP/QAP Area 

Source Matrix was the burning of weeds in irrigation canals and ditches. The weeds in the ditch 

bottoms are typically burned during the month of March just before the irrigation water is first 

released in the spring. Although the ditch width is quite variable (i.e., from 3 feet to over 70 

feet), a typical ditch width was assumed to be 5 feet. The ditch length within a given irrigation 

district or ditch company can be quite extensive, but not necessarily well quantified. For 

instance, it was roughly estimated within the Nampa & Meridian Irrigation District that there 

were 500 to 600 miles of ditches (Anderson, 2010). A total of 56 irrigation districts and ditch 

companies have been identified by the Idaho Department of Water Resources in Ada and Canyon 

counties (IDWR, 2006; IDWR, 2007). Therefore, it was not feasible to contact all of the 

irrigation districts and ditch companies. An alternative data source for ditch lengths was 

identified in the U.S. Geological Service’s National Hydrography Dataset (USGS, 2010); ditch 

lengths were derived from a data layer of canals and ditches. Based on the National 

Hydrography Dataset, the county ditch lengths were estimated to be 796.28 kilometers (km) for 













   

2,000 lbs

1 ton Ep,c ABc FLc EFp,c
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Ada County, 1,980.25 km for Canyon County, and 366.00 km for Elmore County. Emissions 

were estimated using appropriate fuel loadings (assumed to be unspecified weeds) and emission 

factors from AP-42 (U.S. EPA, 2010a). The emission estimation equation is identical to that 

used for agricultural field burning. 

3.1.23 Beef Cattle Feedlots

This category includes PM10 and PM2.5 emissions from beef cattle feedlots and VOC 

emissions from all cattle and calves; NH3 emissions are addressed under the livestock ammonia 

category in Section 3.1.26. 

The total number of cattle and calves was obtained from the 2007 Census of Agriculture

(USDA, 2009). In addition, the number of cattle on feed was also obtained from the same data 

source. The population of cattle on feed for Canyon County was explicitly reported; however, 

the population of cattle on feed for Ada County and Elmore County were not presented due to

confidentiality reporting requirements. The overall population of cattle on feed for those 

counties in Idaho with confidentiality “shielded” data (including Ada and Elmore) was 

determined by subtracting known county populations of cattle on feed from the overall state 

population of cattle on feed resulting in the state shielded population. The state shielded 

population of cattle on feed was then allocated to the shielded counties based upon the reported 

quantity of other cattle (i.e., not beef cows or milk cows). The total number of cattle and calves 

was 66,476 head for Ada County, 129,561 head for Canyon County, and 109,065 head for 

Elmore County. The total number of cattle on feed was 13,770 head for Ada County, 7,221 head 

for Canyon County, and 24,862 head for Elmore County.

The emission factors were obtained from the California Air Resources Board (CARB, 

2004). The PM10 emission factor was 28.9 lbs/1000 head-day, while the VOC emission factor 

was 12.8 lbs/head-year. Since the PM10 emission factor was units of lbs/head-day, it was 

necessary to determine how long each head of cattle on feed is typically present in the feedlot. A 

typical residence time of 136 days was obtained from a feedlot cattle behavioral study (Stanford 

et al., 2009). The annual VOC emissions were calculated for all cattle and calves regardless of 

whether or not they were located on a feedlot. 

The equation for estimating emissions from beef cattle feedlots is as follows:
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Where:

E = Emissions (tons/year);

EF = Emission factor (lbs/head); and

BC = Beef cattle population (head). 

A sample calculation using this equation for estimating annual VOC emissions from Ada 

County is as follows:

BC = 66,476 head

EF = 12.8 lbs VOC/head-year

E = 66,476 head × 12.8 lbs VOC/head-year × (1 ton/2,000 lbs) = 425.4 tons VOC

3.1.24 Other Fires

The other fire source category includes structural fires and vehicle fires. County-level 

structural and vehicle fire statistics were obtained from the Idaho State Fire Marshal’s Idaho Fire 

Incident Reporting System (IFIRS) (Karnowski, 2009). Review of the statistics indicates nearly 

100 percent reporting by the fire districts located in Ada, Canyon, and Elmore counties. Based 

on the IFIRS summary data, the assignment of fire types to the structural and vehicle sources 

categories is shown in Table 3-14. The specific county-level employee data obtained were for 

the following NAICS codes:

Table 3-14. Fire Code Assignments for the Structural Fire and Vehicle Fire 

Source Categories

Category IFIRS Codes

Structural Fires 111 (Building fire)

112 (Fire in structures other than buildings)

120 (Fire in mobile property used as a fixed structure)

121 (Fire in mobile home used as fixed residence) 

122 (Fire in motor home, camper, recreational vehicle used as fixed residence )

123 (Fire in portable building at a fixed location)

Vehicle Fires 130 (Mobile property/vehicle fire)

131 (Passenger vehicle fire)

132 (Road freight or transport vehicle fire)

134 (Water vehicle fire)

137 (Camper or recreational vehicle fire)

138 (Off-road vehicle or heavy equipment fire)

Emission factors for structural fires and vehicle fires were obtained from EIIP guidance 

documents (EIIP, 2001c; EIIP, 2000). Based on the EIIP guidance documents, a fuel loading of 



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

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

  

2,000 lbs

1 ton E EF BC
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1.15 tons/fire was assumed for structural fires and a fuel loading of 0.25 tons/fire was assumed 

for vehicle fires.

The general equation for estimating emissions from structural and vehicle fires is as 

follows:

Where:

Ep = Emissions for pollutant p (tons/year);

F = Annual structural or vehicle fires (fires/year);

FL = Fuel loading (tons material/fire); and

EFp = Emission factor for pollutant p (lbs/tons material).

A sample calculation using this equation for estimating annual CO emissions from Ada 

County structural fire is as follows:

F = 150 fires

FL = 1.15 tons material/fire

EF = 60 lbs CO/ton material

E = 150 fires × 1.15 tons/fire × 60 lbs CO/person × (1 ton/2,000 lbs) = 5.2 tons CO

3.1.25 Windblown Dust

The windblown fugitive dust emissions for the Treasure Valley Airshed were developed 

using the estimation methodology developed for the Western Regional Air Partnership (WRAP) by a 

team of contractors led by ENVIRON (ENVIRON, 2004a) and subsequently revised by Mansell and 

others (Mansell, 2003a; 2003b; Mansell, et al. 2004). The methodology was based upon the results 

of wind tunnel studies and a detailed characterization of vacant lands. Windblown dust emissions 

were estimated hourly on a gridded modeling domain using hourly averaged wind speeds and other 

meteorological parameters. Hourly emission estimates were developed for each hour in 2008. The 

methodology involves application of wind speed- and soil-dependent emission factors to estimate 

emissions rates on a gridded modeling domain. Land use characteristics were used to estimate 

threshold friction velocities, based on gridded meteorological data, to determine the potential for 

wind erosion. Additional agricultural adjustments were applied to capture the impacts of cropspecific planting and harvesting practices. A detailed description of the windblown dust model 

estimation methodology and implementation is provided below.













   

2,000 lbs

1 ton Ep F FL EFp
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Final, August 31, 2010

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While the Treasure Valley Airshed emissions inventory is limited to Ada, Canyon, and 

Elmore counties, the implementation of the modeling system for the development of windblown 

fugitive dust PM emissions requires the use of a larger Cartesian modeling grid domain. As 

such, the emission estimates described below include additional Idaho counties, as well as 

neighboring counties in Oregon. Figure 3-1 displays the modeling domain for which 

windblown dust PM emissions were estimated. In addition, the model requires hourly gridded 

meteorological data and generates emission estimates for each hour for the entire time period 

considered. For the DEQ inventory, these estimates are aggregated to counties and summed 

across all hours of calendar year 2008, as described below.

258 278 298 318 338 358 378 398 418 438 458 478 498

-666

-646

-626

-606

-586

-566

-546

-526

-506

-486

-466

-446

IDEQ 4-km Modeling domain

 (258,-666) -- (510,-442)

 nx=63; ny=56

 LCP (30,60,-121,49)

Figure 3-1. DEQ 4-km Modeling Domain for Windblown Dust Emissions 

Development
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Data Collection

Input data required by the model include:

 Soil characteristics;

 Land use/land cover data; 

 Crop-specific agricultural data; and

 Meteorology

Soil Characteristics

Application of the emission factor relations, described below, requires the 

characterization of soil texture in terms of the four soil groups considered by the model. The 

characteristics or type of soil is one of the parameters of primary importance for the application 

of the emission estimation relations derived from wind tunnel study results. 

The windblown dust model utilized the Soil Survey Geographic Database (SSURGO) 

available from the USDA (USDA, 2010). In some parts of the country, the SSURGO data are 

incomplete. Alternatively, the State Soil Geographic Database (STATSGO) was used to gap-fill 

the SSURGO data for the modeling domain (USDA, 1994). The STATSGO database provides 

detailed information concerning the taxonomy of the soils, including soil texture class, 

percentage of sand, silt and clay, and the available water capacity of the soil. Figure 3-2 displays 

the final merged soil texture data, which combines the SSURGO and STATSGO databases, as 

used in the windblown dust model.

Land Use-Land Cover

Land use-land cover (LULC) data required for the windblown dust model was derived 

from crop-specific GIS data layers obtained from the USDA NASS Cropland Data Layer (CDL) 

Program and represent agricultural, as well as non-agricultural, lands throughout the region 

based on data for calendar year 2007 (NASS, 2007). The primary purpose of the CDL Program

is to use satellite imagery to provide acreage estimates to the Agricultural Statistics Board for the 

state’s major commodities and produce digital, crop-specific, categorized geo-referenced output 

products. These data were reviewed and processed for use in the windblown dust model. Figure 

3-3 presents a display of the final land use/land cover data for the 4-km modeling domain.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

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Figure 3-2. Merged Soil Texture Data from the SSURGO and STATSGO Databases
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Final, August 31, 2010

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Figure 3-3. Land Use/Land Cover Data Used for the DEQ Windblown Dust PM 

Emissions Inventory Development
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Final, August 31, 2010

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Agricultural Data 

Unlike other types of vacant land, windblown dust emissions from agricultural land are 

subject to a number of non-climatic influences, including irrigation and seasonal crop growth. 

As a result, several non-climatic correction or adjustment factors were developed for 

applicability to the agricultural wind erosion emissions. These factors included:

 Long-term effects of irrigation (i.e., soil “clodiness”);

 Crop canopy cover;

 Post-harvest vegetative cover (i.e., residue);

 Bare soil (i.e., barren areas within an agriculture field that do not develop crop 

canopy for various reasons, etc.); and

 Field borders (i.e., bare areas surrounding and adjacent to agricultural fields).

The methodology used to develop individual non-climatic correction factors was based 

upon previous work performed by the California Air Resources Board in their development of 

California-specific adjustment factors for the USDA’s Wind Erosion Equation (CARB, 1997).

In order to apply the agricultural adjustments described above, crop information, 

including types of crops and planting schedules, were required. These crop data (i.e., crop types, 

tilling and harvesting practices, crop calendars, and planting and harvesting schedules) were 

obtained from the National Agricultural Statistics Service and the U.S. Department of 

Agriculture (NASS, 2009b; USDA, 1997; USDA, 2009). In the windblown dust model, specific 

crop types were mapped to those recognized by the model, based on the Conservation 

Technology Information Center (CTIC) crop database, in order to provide a link between 

specific crop planting and harvesting schedules, tilling and irrigation practices, and canopy 

growth curves. Table 3-15 summarizes the Idaho-specific crop types and the mapping between 

DEQ’s data and the CTIC crop types. 

The windblown dust model used the percentage of canopy cover for each crop type as 

crops are grown throughout the year to apply various adjustments to the estimated hourly wind 

blown dust emissions. For the 2008 inventory, the crop canopy cover data, developed from 
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

3-41

crop report data (NASS, 2009b; USDA, 1997), are summarized in Table 3-16, which provides 

the percentage of canopy cover for each crop type in 15-day increments throughout the year. 

Table 3-17 presents the Idaho crop canopy information regarding planting and harvesting dates 

by crop type and region used in combination with the canopy growth curves shown in Table 3-

16. These data are available for broad regions within the State of Idaho including the Central 

(C), Southwestern (SW) and South Central (SC) regions of the state, as indicated in Table 3-17.

Table 3-15. DEQ and CTIC Crop Type Mapping and Descriptions

DEQ Crop Code Description

CTIC Crop 

Name

CTIC Crop

Code

FD01 Barley (grain) Barley BAR01

FD02 Corn (grain) Corn COR01

FD03 Dry edible beans (excluding limas) Peas/Beans BEA01

FD04 Dry lima beans Peas/Beans BEA01

FD05 Dry edible peas Peas/Beans BEA01

FD06 Mustard seed Canola POT01

FD07 Oats (grain) Oats OAT01

FD08 Safflower Canola POT01

FD09 Sugarbeets (sugar) Sugar Beets SUG01

FD10 Triticale Wheat WHE02

FD11 Winter wheat (grain) Wheat WHE02

FD12 Durum wheat (grain) Wheat WHE01

FD13 Spring wheat (grain) Wheat WHE01

SH01 All grass seeds Forage Crops HAY01

SH02 Hay (alfalfa) Forage Crops ALF01

SH03 Hay (small grain) Forage Crops HAY01

SH04 Hay (other tame) Forage Crops HAY01

SH05 Hay (wild) Forage Crops HAY01

SH06 Corn (silage and greenchop) Corn COR01

OT01 Hops n/a n/a

OT02 Mint for oil (peppermint) Canola POT01

OT03 Mint for oil (spearmint) Canola POT01

OT04 Sweet corn (for seed) Corn COR01

VG01 Onions, Dry Vegetables ONI01

VG02 Peas, Chinese (sugar and snow) Vegetables PEA01

VG03 Potatoes Potatoes POT01

VG04 Sweet Corn Corn COR01

FR01 Apples n/a n/a

FR02 Cherries, Sweet n/a n/a

FR03 Grapes n/a n/a

FR04 Peaches n/a n/a

FR05 Plums and Prunes n/a n/a
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Table 3-16. Idaho Crop Canopy Cover by Crop Type and Julian Day Since 

Planting (%)

% canopy cover (CC)

Canopy_Spr or Canopy_Fall 0 15 30 45 60 75 90 105 120 135 150 165 180 195 210 225 240 255 270 285 300 315 330 345 360

BAR01 0 1 15 55 95 95 95 95 95 95 95

OAT01 0 10 35 60 85 95 95 95

SUG01 0 5 10 20 30 40 60 80 90 95

POT01 0 10 25 40 55 65 80 70

WHE01 0 5 10 30 75 95 95 95 95 95 95

WHE02 0 5 10 20 25 25 25 25 25 25 25 25 30 30 40 65 95 95 95 95 95

COR01 0 5 10 50 75 95 95 95 95 95 85 65

BEA01 0 5 15 40 65 75 75 60 30

ONI01 1 5 7 10 15 20 15 10

HAY01 43 50 63 78 90 80 75 90 95 80 75 90 95 75 67 75 80 75 67 57 50 50 53 58 43

ALF01 47 55 67 25 47 67 82 92 95 42 48 53 48 43 40 37 35 35 35 35 37 38 45 55 47

Day
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Table 3-17. Idaho Planting and Harvesting Dates (Julian Day) and Crop Canopy 

Crop Type

Crop 

Code Crop Description Region Plant_Spr Harv_Spr Plant_Fall Harv_Fall Canopy_Spr

Canopy_

Fall

FD01 Barley (grain) SW 91 218 BAR01

FD01 Barley (grain) SC 102 228 BAR01

FD01 Barley (grain) E 129 251 BAR01

FD02 Corn (grain) SW 134 299 COR01

FD02 Corn (grain) SC 134 299 COR01

FD02 Corn (grain) E 134 299 COR01

FD03 Dry edible beans SW 148 261 BEA01

FD03 Dry edible beans SC 148 261 BEA01

FD03 Dry edible beans E 148 261 BEA01

FD04 Dry lima beans SW 148 261 BEA01

FD04 Dry lima beans SC 148 261 BEA01

FD04 Dry lima beans E 148 261 BEA01

FD05 Dry edible peas SW 133 235 BEA01

FD05 Dry edible peas SC 133 235 BEA01

FD05 Dry edible peas E 133 235 BEA01

FD06 Mustard seed SW 116 207 POT01

FD06 Mustard seed SC 116 207 POT01

FD06 Mustard seed E 116 207 POT01

FD07 Oats (grain) SW 118 242 OAT01

FD07 Oats (grain) SC 118 242 OAT01

FD07 Oats (grain) E 118 242 OAT01

FD08 Safflower SW 116 269 POT01

FD08 Safflower SC 116 269 POT01

FD08 Safflower E 116 269 POT01

FD09 Sugarbeets (sugar) SW 99 303 SUG01

FD09 Sugarbeets (sugar) SC 107 300 SUG01

FD09 Sugarbeets (sugar) E 114 295 SUG01

FD10 Triticale SW 268 217 WHE02

FD10 Triticale SC 265 225 WHE02

FD10 Triticale E 269 233 WHE02

FD11 Winter wheat (grain) SW 268 217 WHE02

FD11 Winter wheat (grain) SC 265 225 WHE02

FD11 Winter wheat (grain) E 269 233 WHE02

FD12 Durum wheat (grain) SW 83 220 WHE01

FD12 Durum wheat (grain) SC 90 227 WHE01

FD12 Durum wheat (grain) E 118 246 WHE01

FD13 Spring wheat (grain) SW 83 220 WHE01

FD13 Spring wheat (grain) SC 90 227 WHE01

FD13 Spring wheat (grain) E 118 246 WHE01

FR01 Apples SW

FR01 Apples SC

FR01 Apples E

FR02 Cherries, Sweet SW

FR02 Cherries, Sweet SC

FR02 Cherries, Sweet E

FR03 Grapes SW

FR03 Grapes SC

FR03 Grapes E

FR04 Peaches SW

FR04 Peaches SC

FR04 Peaches E

FR05 Plums and Prunes SW

FR05 Plums and Prunes SC

FR05 Plums and Prunes E
Table 3-20. Continued

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3-44

Crop 

Code Crop Description Region Plant_Spr Harv_Spr Plant_Fall Harv_Fall Canopy_Spr

Canopy_

Fall

OT01 Hops SW

OT01 Hops SC

OT01 Hops E

OT02 Mint for oil (peppermint) SW

OT02 Mint for oil (peppermint) SC

OT02 Mint for oil (peppermint) E

OT03 Mint for oil (spearmint) SW

OT03 Mint for oil (spearmint) SC

OT03 Mint for oil (spearmint) E

OT04 Sweet corn (for seed) SW 131 233 COR01

OT04 Sweet corn (for seed) SC 131 233 COR01

OT04 Sweet corn (for seed) E 131 233 COR01

SH01 All grass seeds SW 106 105 HAY01

SH01 All grass seeds SC 106 105 HAY01

SH01 All grass seeds E 106 105 HAY01

SH02 Hay (alfalfa) SW 122 121 ALF01

SH02 Hay (alfalfa) SC 122 121 ALF01

SH02 Hay (alfalfa) E 122 121 ALF01

SH03 Hay (small grain) SW 106 105 HAY01

SH03 Hay (small grain) SC 106 105 HAY01

SH03 Hay (small grain) E 106 105 HAY01

SH04 Hay (other tame) SW 106 105 HAY01

SH04 Hay (other tame) SC 106 105 HAY01

SH04 Hay (other tame) E 106 105 HAY01

SH05 Hay (wild) SW 106 105 HAY01

SH05 Hay (wild) SC 106 105 HAY01

SH05 Hay (wild) E 106 105 HAY01

SH06 Corn (silage/greenchop) SW 134 277 COR01

SH06 Corn (silage/greenchop) SC 134 277 COR01

SH06 Corn (silage/greenchop) E 134 277 COR01

VG01 Onions, Dry SW 96 263 ONI01

VG01 Onions, Dry SC 96 263 ONI01

VG01 Onions, Dry E 96 263 ONI01

VG02 Peas, Chinese SW 106 172 PEA01

VG02 Peas, Chinese SC 106 172 PEA01

VG02 Peas, Chinese E 106 172 PEA01

VG03 Potatoes SW 112 257 POT01

VG03 Potatoes SC 116 278 POT01

VG03 Potatoes E 133 280 POT01

VG04 Sweet Corn SW 131 233 COR01

VG04 Sweet Corn SC 131 233 COR01

VG04 Sweet Corn E 131 233 COR01
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Meteorological Data 

Gridded hourly meteorological data, required for the dust estimation methodology, were 

based on MM5/WRF model simulation results provided by DEQ (Zhang, 2009). Required data 

fields included wind speeds, precipitation rates, soil temperatures and ice/snow cover. These 

data were obtained from DEQ and then reviewed and formatted for use in the windblown dust 

model. 

Emissions Calculation 

As noted above, the windblown fugitive dust PM emissions for the Treasure Valley 

Airshed were developed for each day of 2008 using the estimation methodology previously 

developed for the WRAP and were estimated hourly on a gridded modeling domain using hourly 

averaged meteorology, surface characteristics (soil and land use) and crop-specific agricultural 

information as described above. The windblown dust model estimation methodology was 

developed based on a review of wind tunnel studies which noted that the two important components 

to characterize the dust emission process from an erodible surface were the threshold friction velocity 

that defines the inception of the emission process as a function of the wind speed and as influenced 

by the surface characteristics, and the strength of the emissions that follow the commencement of 

particle movement. The two critical factors affecting emission strength are the wind speed (wind 

friction velocity) that drives the saltation system, and the soil characteristics. 

Friction Velocities

Surface friction velocities are determined from the aerodynamic surface roughness 

lengths and wind speeds derived from the MM5/WRF model simulations. Friction velocity, u*, 

is related to the slope of the velocity versus the natural logarithm of height through the 

relationship:

Where:

uz = wind velocity at height z (m/s);

u* = friction velocity (m/s);

 = von Karman’s constant (0.4); and

z0 = aerodynamic roughness height (m).

o

z

z

z

u

u

ln 1

* 


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The threshold friction velocities, u*t, are determined using empirical relationships that are 

functions of the aerodynamic surface roughness length, z0 (Marticorena et al., 1997). Surface 

friction velocities, including the threshold friction velocity, are a function of the aerodynamic 

surface roughness lengths. The surface friction velocities are, in turn, dependent upon surface 

characteristics, particularly land use/land cover. The empirical relationships implemented in the 

model are shown in Figure 3-4.

Figure 3-4. Comparison Between the Marticorena et al. (1997) Modeled 

Relationship of Threshold Friction Velocity and Aerodynamic Roughness Length 

and Wind Tunnel Data from Gillette et al. (1980, 1982), Gillette (1988) and Nickling 

and Gillies (1989)

Emission Fluxes 

Emission fluxes, or emission rates, are determined as a function of surface friction 

velocity and soil texture. Key relationships were established between the 12 soil types in the 

classical soil texture triangle and their four dry soil types (i.e., silt [FSS], sandy silt [FS], silty 

sand [MS], and sand [CS]) (Chatenet et al., 1996). Dust emission fluxes were estimated using 

relationships developed for each of the soil texture groups (Alfaro and Gomes, 2001; Alfaro et 

u*t = 0.31e7.44x(Zo)

R

2

 = 0.60

u*t = 0.30e7.22x(Zo)

0

0.5

1

1.5

2

2.5

3

0.00001 0.0001 0.001 0.01 0.1 1

zo (cm)

u*t (m s-1

)

wind tunnel data Marticorena et al. 1997

Expon. (wind tunnel data) Expon. (Marticorena et al. 1997)
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al., 2004). These relationships are presented in Figure 3-5. The mapping used to relate the soil 

textures to the soil groups are presented in Table 3-18.

Figure 3-5. The Emission Flux as a Function of Friction Velocity Predicted by the 

Alfaro and Gomes (2001) Model Constrained by the Four Soil Geometric Mean 

Diameter Classes of Alfaro et al. (2004)

Table 3-18. Soil Texture and Soil Group Codes

Soil Texture Soil Texture Code Soil Group Soil Group Code

No Data 0 N/A 0

Sand 1 CS 4

Loamy Sand 2 CS 4

Sandy Loam 3 MS 3

Silt Loam 4 FS 2

Silt 5 FSS 1

Loam 6 MS 3

Sandy Clay Loam 7 MS 3

Silty Clay Loam 8 FSS 1

Clay Loam 9 MS 3

Sandy Clay 10 MS 3

Silty Clay 11 FSS 1

Clay 12 FS 2

FFS

F = 2.45x10-6 (u*)

3.97

FS

F = 9.33x10-7 (u*)

2.44

MS

F = 1.243x10-7(u*)

2.64

CS

F = 1.24x10-7 (u*)

3.44

0.000000001

0.00000001

0.0000001

0.000001

0.00001

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Friction Velocity (m s-1) Emission Flux (F, g cm-2 s-1

)

FSS

FS

MS

CS

Power (FSS)

Power (FS)

Power (MS)

Power (CS)
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Surface Roughness Lengths

Surface roughness lengths can vary considerably for a given land type, and are assigned 

as a function of land use type based on a review of information reported in the literature. The 

disturbance level of various surfaces has the effect of altering the surface roughness lengths, 

which in turn impact the potential for vacant lands to emit dust from wind erosion.

An examination of the relationship between the threshold surface friction velocity and the 

aerodynamic surface roughness length, reveals that for surface roughness lengths larger than 

approximately 0.1 cm, the threshold friction velocities increase rapidly above values that can be 

realistically expected to occur in the meteorological data used in the model implementation. 

Therefore to simplify the model implementation, only those land types with roughness length 

less than or equal to 0.1 cm are considered as potentially erodible surfaces.

For a given surface roughness, as determined by the land use type, the threshold friction 

velocity has a constant value. Thus, the land use data is mapped to an internal dust code used 

within the model to minimize computer resource requirements and coding efforts. The mapping 

of land use types to dust codes 3 (agricultural), 4 (grassland), 6 (shrubland), and 7 (barren) is 

presented in Table 3-19; dust codes 1 (water/wetlands), 2 (forest/urban), and 5 

(orchards/vineyards) are not included.

Table 3-19. Surface Characteristics by Dust Code and Land Use Category

Dust Code 3 4 6 7

Land use category Agricultural Grassland Shrubland Barren

Surface roughness length, Z0 (cm) 0.031 0.1 0.05 0.002

Threshold friction velocity (m/s) 3.72 6.17 4.30 3.04

Threshold wind velocity at 10 

meter height (m/s [mph])

13.2

[29.5]

19.8

[44.3]

14.6

[32.8]

12.7

[28.5]

Soil Reservoir Characteristics

Soil reservoirs are classified as limited for stable land parcels and unlimited for unstable 

land parcels. Classification of soil reservoirs as limited or unlimited has implications with 

respect to the duration of time over which the dust emissions are generated. In general, soil 

reservoirs should be classified in terms of the type of soils, the depth of the soil layer, soil 

moisture content and meteorological parameters. Finally, the time required for a soil reservoir to 
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3-49

recharge following a wind event is influenced by a number of factors, including precipitation and 

snow events and freezing conditions of the soils. A recharge time of 24 hours was assigned to all 

surfaces. In addition, it was assumed that no surface will generate emissions for more than 10 

hours in any 24-hour period.

The duration and amount of precipitation and snow and freeze events will also affect the 

dust emissions from wind erosion. A set of conditions were developed for treating these events 

based on seasons, soil characteristics and the amounts of rainfall and snow cover (Barnard, 

2003). In addition, the time necessary to re-initiate wind erosion after a precipitation event 

ranges from 1 to 10 days, depending on the soil type, season of the year, and whether the 

precipitation event rainfall amount exceeds 2 inches.

Soil Disturbance 

The disturbance level of a surface has the effect of lowering the threshold surface friction 

velocity. Except for agricultural lands, which are treated separately in the model as described 

below, vacant land parcels are typically undisturbed unless some activity is present such as to 

cause a disturbance (e.g., off-road recreational vehicle activity in desert lands, animal grazing on 

rangelands, etc.). It was assumed that all non-agricultural land types were undisturbed, since 

there is no a priori information to indicate otherwise for the regional scale modeling domain. 

Other Adjustments 

Two other adjustments to modeled air quality impacts related to fugitive dust transportability 

and partitioning between fine and coarse fractions of PM10. Transport fractions as a function of land 

use were assigned to all emission estimates (Pace, 2003; Pace, 2005). In addition, new fine fraction 

values developed from controlled wind tunnel studies of western soils were applied to determine the 

fine and coarse fractions of wind-generated fugitive dust emissions (MRI, 2005).

Model Application 

The windblown fugitive dust model was applied for the entire calendar year 2008 at a 

spatial resolution of 4-km on a modeling domain encompassing the Treasure Valley Airshed. 

The model generates estimates of PM10 dust emissions. The fine fraction of dust is obtained by 
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using a PM2.5/PM10 ratio of 0.10 (MRI, 2005). Gridded emissions estimates were allocated to 

counties using GIS processing techniques and are summarized below. 

Emission Results for 2008 

Annual 2008 windblown dust emissions are presented in Table 3-20 for Ada, Canyon and 

Elmore counties. Annual emissions were calculated by summing hourly emission estimates 

across all days in calendar year 2008. 

Table 3-20. 2008 Annual Windblown Fugitive PM Dust Emissions for Ada, Canyon 

and Elmore Counties (Tons/Year)

Annual 2008 (tpy)

County FIPS PM10 (tpy) PM2.5 (tpy)

Ada 16001 8,606 861

Canyon 16027 888 89

Elmore 16039 17,720 1,772

Total 27,214 2,721

3.1.26 Ammonia Emissions 

Ammonia emissions come from a variety sources including: livestock, agricultural 

fertilizer application, natural soils, domestic sources, wild animals, and ammonia from cold 

storage/industrial refrigeration. With the exception of ammonia from cold storage/industrial 

refrigeration (see Section 3.1.11), emissions have been developed using a GIS-based ammonia 

emissions modeling system developed for the WRAP (Chitjian and Mansell, 2003a; Chitjian and 

Mansell, 2003b; Mansell, 2005). The activity and emission factor data and sources are described 

below. A description of the emission estimation methodology, as well as summaries of the 

ammonia emission estimates are also provided.

Like the windblown dust model, the implementation of the modeling system for the 

development of ammonia emissions for the Treasure Valley Airshed emissions inventory requires the 

use of a Cartesian modeling grid domain that is larger than Ada, Canyon, and Elmore counties. As 

such, the emission estimates described below include additional Idaho counties, as well as neighboring 

counties in Oregon. Figure 3-6 displays the modeling domain for which ammonia emissions were 

estimated. In addition, the model requires hourly gridded meteorological data and generates emission 

estimates for each hour for the entire time period considered. For the DEQ inventory, these estimates 

are aggregated to counties and summed across all hours of calendar year 2008, as described below.
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258 278 298 318 338 358 378 398 418 438 458 478 498

-666

-646

-626

-606

-586

-566

-546

-526

-506

-486

-466

-446

IDEQ 4-km Modeling domain

 (258,-666) -- (510,-442)

 nx=63; ny=56

 LCP (30,60,-121,49)

Figure 3-6. DEQ 4-km Modeling Domain for Ammonia Emissions Development

Data Collection

Input data required by the model for each subcategory (i.e., livestock, fertilizer 

application, natural soil, domestic sources, wild animals, etc.) include:

 Activity data;

 Emission factors; and

 Temporal variations.

In addition, land use/land cover data and meteorology data for the inventory domain were 

used to run the model.
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Livestock Activity Data

Ammonia emissions from livestock were developed using county-level head counts and 

dairy and beef cattle feedlot estimates provided by the DEQ (Strachan, 2009). The DEQ

obtained these data (i.e., headcounts for dairy cattle and beef cattle on feedlots, including specific 

locations of dairies and feedlots) from the Idaho State Department of Agriculture. However, in 

order to avoid disclosure of detailed information regarding any particular dairy or feedlot, DEQ

subsequently aggregated these data to the 4-km grid cells within the modeling domain. The 

gridded dairy and beef cattle data for all Idaho counties were then used to spatially allocate 

county-level headcounts for 2008, obtained from the USDA National Agricultural Statistics 

Service (NASS, 2009a). All other livestock ammonia emissions (i.e., poultry, swine, sheep and 

horses) within Idaho were estimated based on 2007 county-level head counts, which were 

obtained from the 2007 Census of Agriculture (USDA, 2009) and spatially allocated using 

gridding surrogates. For the portions of the two Oregon counties (i.e., Baker and Malheur) 

within the domain, livestock emissions were developed based on county-level activity data 

obtained from the USDA National Agricultural Statistics Service and spatially allocated as 

described below. Estimates for sheep, poultry and swine were obtained from NASS (NASS, 

2009a). Table 3-21 summarizes the county-level livestock activity data for calendar year 2008.

Livestock Emission Factors

The approach used in the WRAP ammonia model does not treat the individual processes 

leading to ammonia emissions from various manure management practices, as has been the 

subject of recent research in the emission inventory development community. Instead, emission 

factors based on a “whole animal” approach are used. The emission factors are based on a recent 

literature review and are presented in Table 3-22 (Chinkin et al., 2003).

 
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Table 3-21. 2008 Annual County-Level Livestock Head Counts

County Beef Cattle Dairy Cattle Swine Poultry Sheep Horses

Ada 10,065 56,411 1,837 1,948 1,806 3,904

Adams 6,175 6,543 41 206 609 749

Blaine 8,042 7,700 11 67 13,789 915

Boise 1,827 457 0 144 0 338

Camas 3,938 1,287 0 57 0 100

Canyon 13,908 115,653 1,534 6,737 19,627 6,525

Custer 18,057 8,008 99 218 481 1,625

Elmore 23,904 85,971 56 654 717 1,161

Gem 10,939 11,799 74 911 6,138 2,831

Gooding 11,035 270,877 160 459 0 1,826

Jerome 10,231 209,322 282 298 1,081 1,386

Lincoln 8,701 61,162 0 301 537 1,182

Owyhee 36,586 109,786 149 687 5,228 2,687

Payette 9,095 53,598 332 887 1,289 2,410

Twin Falls 25,898 146,861 0 982 14,007 2,457

Valley 3,024 3,545 18 196 120 235

Washington 19,154 28,522 300 400 15,532 1,551

Baker (OR) 46,608 34,273 111 663 5,509 4,211

Malheur (OR) 70,562 142,763 311 811 10,104 5,825

Table 3-22. Ammonia Emission Factors for Livestock

Source Category Emission Factor

(kg/animal-yr)

Beef Cattle 9.0

Dairy Cattle 25.0

Poultry 0.1

Swine 7.0

Horses 8.0

Sheep 1.34

Livestock Temporal Variations

A review of current literature reveals a lack in consistency of results quantifying temporal 

variations in ammonia emissions from livestock (Chitjian and Mansell, 2003a). However, a 

preponderance of the studies cited concluded that ammonia emissions from livestock display 

both a seasonal and diurnal variation consistent, in general, with increased ammonia emissions 

associated with warmer temperatures. 

Seasonal allocation factors have been developed using inverse modeling results (Chinkin 

et al., 2003; Gilliland et al., 2003). The factors were further adjusted to reflect the current ORD-
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recommended emission factors, which were not available when the initial modeling methodology 

was developed (U.S. EPA, 2002a), which were not available at the time the modeling was 

performed by Gilliland et al. The adjusted factors are shown on Table 3-23, which indicates over 

a threefold increase in emissions during the warmest months and minimum emissions during the 

late fall, as opposed to the coldest months. The minimum in the fall is explained by the 

relatively dry conditions at that time of the year. 

Table 3-23. Monthly Livestock Allocation Factors

Month Temporal Allocation Factor

January 67

February 75

March 75

April 82

May 126

June 164

July 183

August 154

September 115

October 73

November 51

December 51

The diurnal variation of livestock ammonia emissions was also previously investigated 

(Chitjian and Mansell, 2003a). In general, the literature reports an increase in daytime emissions 

relative to nighttime emissions. A theoretical equation (i.e., Russell and Cass equation) was 

developed to predict diurnal emission variations as a function of meteorological data (Russell 

and Cass, 1986). The Russell and Cass equation relates hourly ammonia emission rates to 

temperature and wind speed as follows:

Where:

Ei = emission rate at hour i from animal waste decomposition;

A = daily total emission rate for ammonia from animal waste =  Ei;

Ti = ambient temperature in degrees Kelvin at hour i; and 

Vi = wind speed in meters per second (m/s) at hour i (a minimum wind speed of 0.1 

m/s).

  Ei  2.36 Ti 273/10 Vi A
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Although the seasonal and diurnal variations presented above are empirically based, they 

are consistent with the theory that greater temperatures and greater wind speeds will result in 

larger ammonia volatilization rates. 

For the 2008 DEQ inventory, the Russell and Cass equation was used to provide the 

diurnal variation of livestock ammonia emissions. This approach is consistent with first principal 

assumptions and with measurements showing increased ammonia release with increased 

temperature and wind speed. The monthly livestock allocation factors shown in Table 3-23 were 

used to allocate annual emission estimates to each month of the year. 

Fertilizer Application Activity 

Although the Idaho State Department of Agriculture (ISDA) was contacted in order to 

obtain local county-level data, ISDA only maintains these data at a state-wide basis. Additionally, 

ISDA’s state-wide data did not include details on the specific types of fertilizers applied, as 

required by the WRAP GIS NH3 model. Therefore, ammonia emissions from fertilizer application 

were developed using monthly county-level fertilizer activity data obtained from the Carnegie 

Mellon University (CMU) Ammonia Model input database developed from the USDA’s National 

Agricultural Statistics Survey (NASS) (Strader et al., 2004). Table 3-24 summarizes the annual 

county-level fertilizer activity data used for modeling of the Treasure Valley inventory domain.

Fertilizer Emission Factors 

Emission factors for ammonia emissions from fertilizer application were based upon data 

from the European Environment Agency (EEA, 2002) as recommended by the WRAP model 

methodology (Chitjian and Mansell, 2003b). Emission factors for fertilizer application are 

presented in Table 3-25. As discussed in the WRAP model methodology (Chitjian and Mansell, 

2003a), fertilizer emission factors were adjusted as a function of the soil pH. Based upon recent 

research, the emission factors are scaled according to the following relation as a function of the 

soil pH (Potter et al., 2001):

a  0.3125 pH 1.01
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Final, August 31, 2010

Table 3-24. 2008 Annual Fertilizer Application Data by Type and County (kg/year)

County State

Anhydrous 

Ammonia

Aqueous 

Ammonia

Nitrogen 

Solutions Urea

Ammonium 

Nitrate

Ammonium 

Sulfate

Ammonium 

Thiosulfate

Ammonium 

Phosphates

Calcium 

Ammonium 

Nitrate

Potassium 

Nitrate

Ada Idaho 313,638 14,867 332,092 898,450 300,150 284,480 48,777 3,050,300 325 34

Adams Idaho 12,072 571 12,766 34,549 11,540 10,930 1,876 117,230 12 1

Blaine Idaho 107,032 5,077 113,318 306,690 102,476 97,060 16,658 1,041,600 111 11

Boise Idaho 4,426 210 4,690 12,698 4,243 4,020 689 43,076 4 0

Camas Idaho 60,099 2,845 63,575 172,068 57,507 54,452 9,336 584,340 62 6

Canyon Idaho 1,562,920 74,098 1,655,040 4,478,000 1,495,900 1,416,830 243,278 15,191,000 1,622 169

Custer Idaho 34,458 1,632 36,479 98,748 32,971 31,237 5,365 334,960 35 3

Elmore Idaho 541,010 25,648 572,460 1,549,100 517,810 490,700 84,235 5,257,700 561 58

Gem Idaho 94,452 4,472 99,886 270,264 90,382 85,546 14,695 917,980 97 10

Gooding Idaho 446,610 21,192 473,140 1,281,720 428,290 405,640 69,552 4,348,700 464 48

Jerome Idaho 669,030 31,704 707,470 1,916,560 640,480 606,120 104,098 6,502,500 695 72

Lincoln Idaho 151,368 7,163 160,234 432,790 144,836 137,088 23,523 1,473,100 157 16

Owyhee Idaho 432,650 20,498 457,880 1,239,260 413,780 392,120 67,301 4,206,700 449 47

Payette Idaho 259,124 12,298 274,398 741,760 248,242 235,088 40,327 2,519,900 269 28

Twin Falls Idaho 1,131,320 53,482 1,201,180 3,269,500 1,091,410 1,038,610 177,732 11,252,000 1,151 124

Valley Idaho 19,078 904 20,181 54,558 18,260 17,288 2,968 185,470 20 2

Washington Idaho 193,948 9,191 205,400 555,660 185,754 175,930 30,170 1,884,600 201 21

Baker Oregon 177,090 6,235 301,240 796,800 97,240 155,110 8,280 623,200 1,487 538

Malheur Oregon 1,320,700 46,564 2,248,600 5,944,000 726,000 1,157,000 61,724 4,651,400 11,087 4,011
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Table 3-25. Ammonia Emissions Factors for Fertilizer Application

Fertilizer Type %N volatized as NH3 kg NH3/kg fertilizer applied

Anhydrous ammonia 4 0.04857

Aqueous ammonia 2.4 0.02914

Nitrogen solutions 8 0.09714

Urea 15 0.18214

Ammonium nitrate 2 0.02428

Ammonium sulfate 10 0.12143

Calcium ammonium nitrate 2 0.02428

Ammonium thiosulfate 2.4 0.02914

Other straight nitrogen 2.4 0.02914

Ammonium phosphates 5 0.06071

N-P-K 2 0.02428

Potassium nitrate 2.4 0.02914

Soil pH scalars were not applied to urea emission factors as research has indicated that 

urea emissions are not affected by initial soil pH. Soil pH data used for the Treasure Valley 

emissions inventory are described below.

Fertilizer Temporal Variation

Emissions from fertilizer application were temporally allocated monthly based on the 

monthly activity data. Diurnal variations in fertilizer emissions are expected as temperature and 

wind speed affect ammonia production and volatilization. The Russell and Cass equation, 

described above, was used to temporally allocate daily emissions to each hour of the day as a 

function of temperature and wind speed, as was done for livestock emissions. 

Natural Soil Activity

Ammonia emissions from natural soils are based on land use/land cover acreages. The 

same database used for the windblown dust model was used for the estimation of ammonia 

emissions from natural soils. Land use-land cover (LULC) data required for the windblown dust 

model was derived from crop-specific GIS data layers obtained from the USDA NASS Cropland 

Data Layer (CDL) Program and represent agricultural, as well as non-agricultural, lands 

throughout the region based on data for calendar year 2007 (NASS, 2007). The primary purpose 

of the CDL Program is to use satellite imagery to provide acreage estimates to the Agricultural 

Statistics Board for the state’s major commodities and produce digital, crop-specific, categorized 

geo-referenced output products. These data were reviewed and processed for use in the 
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windblown dust model. Figure 3-3 (windblown dust section) presents a display of the final land 

use/land cover data for the 4-km modeling domain.

Natural Soil Emission Factors:

Natural soil ammonia emissions were estimated based on emission factors developed 

from recent research (Battye et al., 2003; Chinkin et al., 2003); these emission factors are 

presented in Table 3-26. 

Table 3-26. Ammonia Emission Factors for Native Soils

Land type Emission Factor (kg/km2-yr)

Urban 10

Barren/Desert land 10

Deciduous Forest 174

Evergreen Forest 54

Mixed Forest 114

Shrubland 400

Grasslands 400

Fallow 205

Urban/Recreational Grasses 400

Wetlands 400

A previous study estimated ammonia emissions from native soils based on several 

environmental variables including monthly rainfall, surface air temperature, solar radiation, soil 

texture, land cover type and vegetative type (Potter et al., 2001). The model first calculated the 

available mineral nitrogen substrate for ammonia emissions and then modified this value by 

applying scalars for soil surface temperature (Ts), pH, and soil moisture content (M). The scalars 

are of the form:

where ‘c’ is a constant, which determines the sensitivity to pH. The study authors used ‘c’ 

values of 1.3 (i.e., consistent with measurements made) and 10 (i.e, to produce results with 

minimal pH effects). The emission factors presented in Table 3-26 were modified for 

temperature and pH effects using these scalars using a ‘c’ value of 1.3. Soil temperature and soil 

moisture content are taken from the meteorological data used for the project as discussed below. 

 

 M 

p H c

Ts

 







































 





















1

1 10

1

273.1 6

2729.9 2 0.09018
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Natural Soil Temporal Variation

The temporal allocation of native soil ammonia emissions were calculated using the 

emission factor scalars described above, which are temporally resolved based on the hourly 

meteorological data.

Domestic Sources Activity Data

Domestic sources of ammonia emissions considered in the current inventory include 

human respiration and perspiration, disposable and cloth diapers and domestic pets (cats and 

dogs). Ammonia emissions from domestic sources use county-level populations as activity data. 

County-level populations were obtained from the U.S. Census (U.S. Census, 2009c). Estimates 

of total county-level populations are needed for human perspiration and respiration. The number 

of cats and dogs are scaled based on total population. County-level estimates of infant 

populations are used to estimate ammonia emissions from cloth and disposable diapers. The 

2008 county-level population estimates are presented in Table 3-27 for all counties within the 4-

km modeling domain used for the project.

Table 3-27. 2008 County-Level Population Estimates

County State Total Population Infant Population

Ada Idaho 380,920 29,211

Adams Idaho 3,499 184

Blaine Idaho 21,731 1,437

Boise Idaho 7,504 314

Camas Idaho 1,126 85

Canyon Idaho 183,939 17,764

Custer Idaho 4,254 180

Elmore Idaho 28,997 2,594

Gem Idaho 16,513 1,113

Gooding Idaho 14,295 1,212

Jerome Idaho 20,468 1,955

Lincoln Idaho 4,503 417

Owyhee Idaho 10,877 852

Payette Idaho 22,966 1,694

Twin Falls Idaho 74,284 6,008

Valley Idaho 8,862 531

Washington Idaho 10,206 659

Baker Oregon 15,983 791

Malheur Oregon 30,907 2,192

Total 861,834 69,193
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Domestic Source Emission Factors

Domestic source emissions were estimated based on emission factors recommended by 

recent studies (Chitjian et al., 2000; Chitjian and Mansell, 2003a). Table 3-28 presents the 

emission factors used for the project.

Table 3-28. Ammonia Emission Factors for Domestic Ammonia Sources

Source Emission Factor Unit

Cats 0.348 lb N/cat-yr

Dogs 2.17 lb N/dog-yr

Human Perspiration 0.55 lb NH3/person-yr

Human Respiration 0.0035 lb NH3/person-yr

Cloth Diapers 6.9 lb NH3/infant-yr

Disposable Diapers 0.36 lb NH3/infant-yr

Domestic Sources Temporal Variation

The ammonia emissions from domestic sources were assumed to be temporally invariant. 

Wild Animal Activity Data

Although ammonia emissions from wild animals constitute a comparatively small portion 

of the overall ammonia emission inventory, these emissions were included given the availability 

of activity data. Ammonia emissions from wild animals are based upon estimates of the number 

of animals at the county level. These data were obtained from the Carnegie Mellon University 

(CMU) Ammonia Model input database (Strader et al., 2004). It should be noted that countylevel wild animal populations are obtained from state-level data allocated to counties based on 

surrogates. Consequently, the county-level populations may result in fractional numbers, 

particularly for those animals with relatively small overall populations.

Wild Animal Emission Factors

Ammonia emissions from wild animals were estimated using emission factors obtained 

from the CMU NH3 model (Strader, et al., 2004) and are presented in Table 3-29. 
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Table 3-29. Ammonia Emission Factors for Wild Animal Ammonia Sources

Wild Animal Temporal Variations 

The ammonia emissions from wild animals were assumed to be temporally invariant. 

Land Use/Land Cover Data

The Land Use/Land Cover (LULC) data used for the ammonia inventory were developed 

from the NASS CDL database described above (NASS, 2007). LULC data is directly used for 

estimating natural soil ammonia emissions, as well as for spatial allocation of livestock and 

fertilizer application emissions, as described below. The land use classifications available in the 

CDL database are presented in Table 3-30. Figure 3-7 displays the CDL data for the 4-km DEQ

modeling and are summarized at the county-level in Table 3-31.

Soil pH is used in the ammonia model for applying adjustments to emission factors for 

natural soil and fertilizer application emissions. The State Soil Geographic Database 

(STATSGO) was used to specify the soil pH necessary for the development of the emission 

inventory for the project (USDA, 1994). Figure 3-8 displays the mean soil pH for the DEQ

modeling domain.

Meteorology

Gridded hourly meteorological data required for the model include wind speeds, ambient 

temperatures, soil temperatures and soil moisture and are based on the MM5/WRF model 

simulation results provided by DEQ (Zhang, 2009). 

Emission Calculation

Model Application 

A GIS-based modeling system was used to generate the gridded ammonia emissions 

inventory incorporating various improvements as implemented for the WRAP (Chitjian and 

Source Emission Factor Unit

Black bears 4.536 kg NH3/animal-yr

Grizzly bears 4.536 kg NH3/animal-yr

Elk 24.48 kg NH3/animal-yr

Deer 4.536 kg NH3/animal-yr
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Table 3-30. CDL Classifications and NH3 Model Cross-References

CDL Code NH3 Code Crop Description LU Description

1 10 Corn Row Crops

2 10 Cotton Row Crops

3 10 Rice Row Crops

4 10 Sorghum Row Crops

5 10 Soybeans Row Crops

6 10 Sunflowers Row Crops

10 10 Peanuts Row Crops

11 10 Tobacco Row Crops

21 10 Barley Grains/Hays/Seeds

22 10 Durum Wheat Grains/Hays/Seeds

23 10 Spring Wheat Grains/Hays/Seeds

24 10 Winter Wheat Grains/Hays/Seeds

25 10 Other Small Grains Grains/Hays/Seeds

26 10 Winter Wheat/Soybeans Double-Cropped Grains/Hays/Seeds

27 10 Rye Grains/Hays/Seeds

28 10 Oats Grains/Hays/Seeds

29 10 Millet Grains/Hays/Seeds

30 10 Speltz Grains/Hays/Seeds

31 10 Canola Grains/Hays/Seeds

32 10 Flaxseed Grains/Hays/Seeds

33 10 Safflower Grains/Hays/Seeds

34 10 Rape seed Grains/Hays/Seeds

35 10 Mustard Grains/Hays/Seeds

36 10 Alfalfa Grains/Hays/Seeds

37 10 Other Hays Grains/Hays/Seeds

41 10 Sugarbeets Other Crops

42 10 Dry Beans Other Crops

43 10 Potatoes Other Crops

44 10 Other Crops Other Crops

45 10 Sugarcane Other Crops

46 10 Sweet Potatoes Other Crops

47 10 Miscellaneous Vegetables & Fruit Other Crops

48 10 Watermelon Other Crops

50 10 Pickles Other Crops

51 10 Chick Peas Other Crops

52 10 Lentils Other Crops

53 10 Peas Other Crops

58 10 Clover/Wildflowers Other Crops

61 12 Fallow/Idle Cropland Open Non-Crop

62 9 Grass/Pasture/Non-agricultural Open Non-Crop

63 5 Woodland Open Non-Crop

64 6 Shrubland Open Non-Crop

65 2 Barren Open Non-Crop

67 10 Peaches Tree Crops

68 10 Apples Tree Crops

69 10 Grapes Tree Crops
Table 3-30. Continued

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CDL Code NH3 Code Crop Description LU Description

70 10 Christmas Trees Tree Crops

71 10 Other Tree Nuts & Fruit Tree Crops

72 10 Citrus Tree Crops

73 10 Other Tree Fruit Tree Crops

80 10 Other Non-Tree Fruit Tree Crops

81 13 Clouds Other Non-Crops

82 1 Urban/Developed Other Non-Crops

83 13 Water Other Non-Crops

87 8 Wetlands Other Non-Crops

92 13 Aquaculture Other Non-Crops

111 13 NLCD-Open Water NLCD Non-Crop

112 13 NLCD-Perennial Ice/Snow NLCD Non-Crop

121 1 NLCD-Developed/Open Space NLCD Non-Crop

122 1 NLCD-Developed/Low Intensity NLCD Non-Crop

123 1 NLCD-Developed/Medium Intensity NLCD Non-Crop

124 1 NLCD-Developed/High Intensity NLCD Non-Crop

131 2 NLCD-Barren NLCD Non-Crop

141 3 NLCD-Deciduous Forest NLCD Non-Crop

142 4 NLCD-Evergreen Forest NLCD Non-Crop

143 5 NLCD-Mixed Forest NLCD Non-Crop

152 6 NLCD-Shrubland NLCD Non-Crop

171 7 NLCD-Grassland Herbaceous NLCD Non-Crop

181 9 NLCD-Pasture/Hay NLCD Non-Crop

182 10 NLCD-Cultivated Crop NLCD Non-Crop

190 8 NLCD-Woody Wetlands NLCD Non-Crop

195 8 NLCD-Herbaceous Wetlands NLCD Non-Crop
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Figure 3-7. Land Use/Land Cover Data Used for the DEQ Ammonia Emissions 

Inventory Development
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Table 3-31. Land Use Summary by Category and County for the 4-Km Modeling 

Domain (Acres) 

County State

Urban 

Land

Forest 

Land/Wetlands

Agricultural 

Lands Grasslands Shrublands

Barren 

Lands

Ada Idaho 100,990 7,539 46,682 354,735 157,842 2,327

Adams Idaho 2,078 113,107 494 18,003 152,634 0

Blaine Idaho 655 170,408 140 59,807 81,215 2,988

Boise Idaho 4,690 676,163 279 152,293 375,662 1,147

Camas Idaho 5,950 167,759 29,348 196,542 257,873 1,346

Canyon Idaho 80,459 3,183 186,583 83,998 9,364 4,942

Custer Idaho 1,730 840,939 185 200,777 254,396 10,205

Elmore Idaho 34,270 388,334 74,469 721,049 734,830 4,836

Gem Idaho 10,231 51,890 23,639 117,980 153,711 309

Gooding Idaho 23,664 844 107,229 104,031 226,637 556

Jerome Idaho 5,171 0 21,756 7,751 4,025 62

Lemhi Idaho 0 39,380 0 8,521 10,170 0

Lincoln Idaho 2,093 0 6,552 12,035 50,050 62

Owyhee Idaho 20,011 86,658 104,867 411,322 1,174,541 4,633

Payette Idaho 12,667 2,612 39,963 159,559 41,392 1,173

Twin Falls Idaho 5,831 453 33,579 50,096 30,445 310

Valley Idaho 3,577 735,764 124 75,919 214,516 0

Washington Idaho 9,404 117,440 30,869 199,095 549,927 611

Baker Oregon 6,354 41,817 3,818 48,107 418,567 0

Malheur Oregon 40,403 24,951 126,640 491,460 1,626,267 29,037

Domain Total 370,227 3,469,242 837,215 3,473,078 6,524,066 64,545

 

Figure 3-8. Mean Soil pH for the DEQ Modeling Domain from the STATSGO 

Database
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Mansell, 2003a; Chitjian and Mansell, 2003b; Mansell, 2005). The county level activity data were 

used in conjunction with the emission factors and environmental factors described above to 

generate a gridded inventory of ammonia emissions on the DEQ 4-km resolution modeling domain. 

The gridded emission inventory was temporally resolved hourly.

The modeling system applied gridding surrogates (described below) to the county-level 

emission estimates on an annual basis (or monthly for fertilizer application emissions). The 

effects of soil pH on the emission factors for fertilizer application were applied to the annual 

gridded ammonia emission estimates. Other environmental factors were incorporated in the 

temporal allocation modules since these factors impact the diurnal variation of emissions through 

gridded, hourly temperatures and wind speeds. For natural soil emissions estimates, the effects 

of soil conditions (pH and moisture) and meteorological data were both incorporated in the 

emissions estimates during the temporal allocation process.

Spatial Surrogate

The GIS model used for estimating ammonia emissions applied gridded spatial surrogates 

to county-level activity and emission factor data to generate gridded hourly emission estimates. 

Spatial surrogates were developed based on population and land use/land cover data. The land 

use data used for the project was processed for developing spatial surrogates through aggregation 

of individual land use classes into more broadly defined classes for spatial allocation of 

emissions. The spatial surrogate codes, associated land use classes and descriptions, as used in 

the model, are presented in Table 3-32 and displayed graphically in Figure 3-7 above. Each 

ammonia emission source category considered was then cross-referenced to the appropriate 

spatial surrogate code (both primary and secondary surrogate assignments), as shown in Table 3-

33. It should be noted that for beef and dairy cattle emissions, spatial surrogates were only used 

for the portions of the domain within Washington. Within Idaho, beef and dairy cattle were 

spatially allocated based on the gridded distribution of dairies and feedlots, as discussed above. 
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Table 3-32. Land Use/Surrogate Cross-Reference

Surrogate Number CDL Classes Description

1 1 Urban 

2 2 Barren 

3 3 Deciduous Forest 

4 4 Evergreen Forest 

5 5 Mixed Forest 

6 6 Shrublands 

7 7 Grasslands 

8 8 Wetlands 

9 9 Grass + Pasture 

10 10 Agricultural 

11 3-10,12 Rural 

12 12 Fallow 

13 13 Water 

14 3-5,7 Forest + Shrub + Grasslands 

Table 3-33. Source Category/Surrogate Cross-Reference

Source category

Primary Surrogate

Code and Description

Secondary Surrogate

Code and Description

Fertilizers 10 – Agricultural 11 – Rural

Livestock – Dairy & Beef Cattle 9 – Grass + Pasture 11 – Rural

Livestock – Other 9 – Grass + Pasture 11 – Rural

Domestic Respiration Population Population

Native Soils – Urban 1 – Urban 1 – Urban

Native Soils – Barren 2 – Barren 2 – Barren

Native Soils – Deciduous Forest 3 – Deciduous Forest 3 – Deciduous Forest

Native Soils – Evergreen Forest 4 – Evergreen Forest 4 – Evergreen Forest

Native Soils – Mixed Forest 5 – Mixed Forest 5 – Mixed Forest

Native Soils – Shrubland 6 – Shrublands 5 – Mixed Forest

Native Soils – Grassland 7 – Grasslands 7 – Grasslands

Native Soils – Fallow 12 – Fallow 12 – Fallow

Native Soils – Urban Grass 1 – Urban 1 – Urban

Native Soils – Wetlands 8 – Wetlands 8 – Wetlands

Wild Animals 14 – Forest + Shrub + Grasslands 14 – Forest + Shrub + Grasslands

Emission Results 

The GIS NH3 model was applied using the data as described above for each day in 

calendar year 2008 on the 4-km modeling domain. For reporting purposes, the hourly, gridded 

emissions were aggregated to the county level using a GIS processing approach. For each county 

border-line grid cell, emissions were distributed among the counties intersecting the grid cell in 

proportion to the area of each of these counties within the grid cell.
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Annual 2008 ammonia emissions by source category are presented in Table 3-34 for Ada, 

Canyon and Elmore counties. Annual emissions were calculated by summing hourly emission 

estimates across all days in calendar year 2008. A comparison with previous inventories 

developed for calendar year 2010 by ERG/ENVIRON (ENVIRON and ERG, 2002) shows that 

the 2008 annual ammonia emission estimates for the Ada and Canyon counties are relatively 

consistent with the current estimates based on the WRAP GIS-based NH3 model (11,535 tpy

from all sources or 8,040 tpy from all non-soil sources versus 6,228 tpy based on previous work 

not inclusive of soils). Likely reasons for the 30 percent increase in emission estimates are

differences in activity data and methodologies.

3.2 Emissions Calculation Methodologies – Ozone and PM Season 

After the annual area source emissions were estimated using the methodologies described 

in the various subsections of Section 3.1, the daily ozone season and PM season emission 

estimates were developed. The ozone season extends from April 1 through October 31 (i.e., 214 

days), while the PM season is from November 1 through February 29 (2008 was a leap year) 

(i.e., 121 days). Wherever possible, Idaho-specific activity/surrogate data were used to develop

temporal allocation profiles. If Idaho-specific data were not available, then U.S. EPA’s default 

temporal allocation profiles from its emissions modeling clearinghouse were used instead (U.S. 

EPA, 2002b).

3.2.1 Fuel Combustion

As part of the fuel survey mailed out to fuel dealers and distributors, monthly fuel 

quantity data were requested. In general, fuel respondents were able to furnish relevant monthly 

statistics. In a few cases, respondents were contacted by phone to clarify the appropriate 

seasonal distribution. These monthly fuel quantity data were used to develop seasonal fuel 

quantities which were then divided by the number of days in the season resulting in seasonal 

daily fuel use. As pointed out by several respondents, it should be noted that the monthly fuel 

quantity data were based upon fuel deliveries and not actual consumption. As a result, the 

reported monthly fuel quantity data probably lead consumption by a few weeks (i.e., fuel would 

ordered and stockpiled prior to the winter heating season).
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Table 3-34. 2008 Annual Ammonia Emissions for Ada, Canyon, and Elmore 

Counties by Source Category (Tons/Year)

2008 Annual Ammonia Emissions (tpy)

SCC Description Ada Canyon Elmore

2805023300 Dairy Cattle 1,554.56 3,187.14 2,369.17

2805003100 Beef Cattle 99.85 137.98 237.15

2805025000 Swine 14.17 11.84 0.43

2805030000 Poultry 0.21 0.74 0.07

2805035000 Horses 34.43 57.54 10.24

2805040000 Sheep 2.67 28.99 1.06

Total Livestock 1,705.9 3,424.2 2,618.1

9999101002 Native Soils – Urban 26.41 27.04 14.54

9999101003 Native Soils – Barren 0.00 0.00 0.24

9999101004 Native Soils – Deciduous Forest 0.19 0.00 0.02

9999101005 Native Soils – Evergreen Forest 4.92 0.45 103.55

9999101006 Native Soils – Mixed Forest 0.47 0.00 0.00

9999101007 Native Soils – Shrubland 49.55 3.10 100.11

9999101008 Native Soils – Grassland 127.48 22.80 173.45

9999101009 Native Soils – Fallow 19.45 31.57 19.30

9999101010 Native Soils – Urban Grass 1,056.44 1,081.63 581.46

9999101011 Native Soils – Wetlands 6.90 30.11 13.04

Total Native Soils 1,291.8 1,196.7 1,005.7

8888101001 Wild Animals – Black bears 1.26 0.12 4.58

8888101002 Wild Animals – Grizzly bears 0.00 0.00 0.01

8888101003 Wild Animals – Elk 35.08 3.32 127.37

8888101004 Wild Animals – Deer 2.07 0.20 7.55

Total Wild Animals 38.4 3.6 139.5

6906950001 Domestic – Respiration 0.66 0.32 0.05

6906950002 Domestic – Perspiration 104.75 50.58 7.97

6906950006 Domestic – Cloth Diapers 100.78 61.29 8.95

6906950007 Domestic – Disposable Diapers 5.26 3.20 0.47

6906950008 Domestic – Cats 6.43 3.10 0.49

6906950010 Domestic – Dogs 59.72 28.84 4.55

Total Domestic 277.6 147.3 22.5

2801700001 Fertilizer – Anhydrous Ammonia 21.52 109.18 39.05

2801700002 Fertilizer – Aqueous Ammonia 0.61 3.11 1.11

2801700003 Fertilizer – Nitrogen Solutions 45.57 231.23 82.63

2801700004 Fertilizer – Urea 180.39 899.07 311.02

2801700005 Fertilizer – Ammonium Nitrate 10.29 52.24 18.68

2801700006 Fertilizer – Ammonium Sulfate 48.80 247.45 88.54

2801700007 Fertilizer – Ammonium Thiosulfate 2.01 10.20 3.65

2801700009 Fertilizer – All Ammonium Phosphates 261.59 1,326.44 474.30

2801700011 Fertilizer – Calcium Ammonium Nitrate 0.01 0.06 0.02

2801700012 Fertilizer – Potassium Nitrate 0.00 0.01 0.00

Total Fertilizers 570.8 2,879.0 1,019.0

Grand Total 3,884 7,651 4,805
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3.2.2 Residential Wood Combustion

Annual residential wood quantities were allocated to the ozone and PM seasons based 

upon results from the residential wood combustion survey (Aurora, 2010). The seasonal 

fractions were derived from survey responses concerning the number of times a particular device 

(i.e., fireplace, woodstove, insert, or pellet stove) was used each month. Seasonal fractions were 

estimated for each county and device type. These seasonal fractions were then multiplied by the 

annual residential wood quantities resulting in seasonal wood quantities. Finally, these seasonal 

wood quantities were then divided by the number of days in each season.

3.2.3 Paved Road Dust

The temporal allocation factors developed for on-road motor vehicles using traffic 

counter data were also used for paved road dust emissions. This is discussed further in 

Apppendix E of the Northern Ada County PM10 Limited Maintenance Plan Ten-Year Update.

Nonwinter “ubiquitous” silt loadings were assumed for the ozone season, while winter season 

“ubiquitous” silt loadings were assumed for the PM season to reflect the higher silt that results 

from roadway sanding. Precipitation adjustment factors were estimated for each month based 

on the number of days with at least 0.01 inches of rain.

Seasonal emission estimates by county are shown in Table 3-35. As shown, emissions are 

higher in the winter PM season than the summer ozone season due to silt loadings that were 

generally higher in winter than in non-winter. Although precipitation factors and temporal 

activity factors have the effect of decreasing emissions in the PM season relative to the ozone 

season, differences in silt loading, relating to antiskid treatments, cause higher emissions in the 

PM season relative to the ozone season.

3.2.4 Unpaved Road Dust

Temporal allocation of unpaved road dust emissions was performed in the same way as 

described in Section 3.2.3 for paved road dust. Although it is possible that unpaved road dust 

temporal allocations may differ from paved road dust allocations, there were no seasonal activity 

data available specific to unpaved roads. Therefore, paved road temporal allocations were 

assumed. Summer and winter road surface material silt content estimates taken from the 

TVRDS were used for the ozone and winter season, respectively.
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Emission estimates by county are presented in Table 3-36. As noted in Section 3.1.4, 

Elmore County contains the highest unpaved roadway mileage and the highest unpaved road dust 

emission estimates of all counties in the Treasure Valley. Ozone season emission estimates are 

considerably higher than PM season emission estimates due to seasonal precipitation adjustments 

and higher estimated activity levels in the ozone season.

Table 3-35. 2008 Seasonal Paved Road Dust Emission Estimates

Roadway Type PM Season (TPD) Ozone Season (TPD)

PM10 PM2.5 PM10 PM2.5

Ada Countya34.8 2 10.4 0.6

Canyon Countya34.8 2 10.4 0.6

Elmore Countyb5.1 1.2 1.7 0.3

a Ada and Canyon counties paved road dust updated by DEQ in 2012; see Appendix E of the Northern Ada 

County PM10 Limited Maintenance Plan Ten-Year Update.

b Elmore County road dust original estimates. Elmore County emissions were not needed for the Northern Ada 

County PM10 Limited Maintenance Plan Ten-Year Update and were not updated.

Table 3-36. 2008 Seasonal Unpaved Road Dust Emission Estimates

County

PM Season (TPD) Ozone Season (TPD)

PM10 PM2.5 PM10 PM2.5

Ada 1.65 0.09 3.03 0.17

Canyon 0.28 0.02 0.52 0.03

Elmore 3.44 0.34 12.20 1.21

Totals 5.36 0.45 15.75 1.41

3.2.5 Commercial Cooking

No definite seasonality could be established for the five commercial cooking 

subcategories. Therefore, it was assumed that emissions were equally distributed throughout the 

year, so seasonal daily emissions were calculated by dividing annual emissions by 366.

3.2.6 Construction

Inclement weather can possibly affect construction activities in the winter. The seasonal 

profile for construction activities was developed using precipitation adjustment factors based on 

the number of days with at least 0.01 inches of rain. For any day with precipitation, it was 

assumed that either construction activity did not occur or that the construction activities did 

occur did not have emissions due to wet soil.
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3.2.7 Architectural Surface Coatings

Idaho-specific temporal usage patterns were not identified for architectural surface 

coatings. Therefore, the U.S. EPA’s default temporal allocation profiles from its emissions 

modeling clearinghouse were used for architectural surface coating (U.S. EPA, 2002b). This 

temporal allocation profile is shown in Table 3-37.

Table 3-37. Temporal Allocation Profile Assignment for Architectural Surface 

Coating

Category

Profile 

ID Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Ozone 

Factor

PM 

Factor

Architectural 

Surface 

Coating

199 82 82 81 81 81 85 85 85 85 85 85 82 0.5876 0.3313

3.2.8 Traffic Markings

Local staff at the Idaho Transportation Department and the Canyon Highway District 

were contacted regarding the seasonality of traffic marking application (Morrison, 2010b; 

Newlun, 2010; Richard, 2010c). These staff indicated that generally traffic marking application 

corresponds with the ozone season months and is not conducted during the winter (i.e., PM 

season). Therefore, daily ozone season traffic marking emissions were calculated by dividing 

annual emissions by the number of days in the ozone season (i.e., 214 days).

3.2.9 Industrial Surface Coating

Idaho-specific temporal usage patterns were not identified for industrial surface coating. 

Therefore, the U.S. EPA’s default temporal allocation profiles from its emissions modeling 

clearinghouse were used for the 13 industrial surface subcategories (U.S. EPA, 2002b). The 

assignment of these temporal allocation profiles is shown in Table 3-38. The monthly values 

shown in Table 3-38 represent the monthly fractional value out of an annual total of 1,000. The 

ozone season and PM season factors are calculated by summing up the monthly fractional values 

for the respective seasons and then dividing by 1,000.

Table 3-38. Temporal Allocation Profile Assignments for Industrial Surface 

Coating Subcategories

Subcategory

Profile 

ID Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Ozone 

Factor

PM 

Factor

Factory 

Finished Wood 173 81 81 82 82 82 86 86 86 85 85 85 81 0.5908 0.3273

Wood Furniture 287 84 84 79 79 79 84 84 84 86 86 86 84 0.5826 0.3383

Metal Furniture 287 84 84 79 79 79 84 84 84 86 86 86 84 0.5826 0.3383

Paper 257 83 83 82 82 82 84 84 84 84 84 84 83 0.5846 0.3333
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Subcategory

Profile 

ID Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Ozone 

Factor

PM 

Factor

Plastic Products 200 82 82 81 81 81 86 86 86 85 85 85 82 0.5888 0.3303

Miscellaneous 

Finished Metals 253 83 83 81 81 81 84 84 84 85 85 85 83 0.5846 0.3343

Machinery and 

Equipment 253 83 83 81 81 81 84 84 84 85 85 85 83 0.5846 0.3343

Electronic and 

Other Electrical 253 83 83 81 81 81 84 84 84 85 85 85 83 0.5846 0.3343

Motor Vehicles 140 80 80 79 79 79 87 87 87 87 87 87 80 0.5936 0.3273

Aircraft 169 81 81 80 80 80 87 87 87 86 86 86 81 0.5918 0.3283

Marine 266 83 83 83 83 83 84 84 84 83 83 83 83 0.5846 0.3323

Railroad 169 81 81 80 80 80 87 87 87 86 86 86 81 0.5918 0.3283

Miscellaneous 

Manufacturing 260 83 83 82 82 82 85 85 85 85 85 85 83 0.5861 0.3323

3.2.10 Degreasing

Idaho-specific temporal usage patterns were not identified for degreasing. Therefore, the 

U.S. EPA’s default temporal allocation profiles from its emissions modeling clearinghouse were 

used for degreasing (U.S. EPA, 2002b). Unlike industrial surface coating, the same temporal 

allocation profile was assigned to all of the degreasing subcategories. This temporal allocation 

profile is shown in Table 3-39.

Table 3-39. Temporal Allocation Profile Assignment for Degreasing

Category

Profile 

ID Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Ozone 

Factor

PM 

Factor

Degreasing 253 83 83 81 81 81 84 84 84 85 85 85 83 0.5846 0.3343

3.2.11 Other Per Employee Emission Factor Source Categories

No Idaho-specific seasonality could be established for two of the per employee emission 

factor source categories (i.e., autobody refinishing and industrial refrigeration/cold storage). 

Therefore, it was assumed that emissions were equally distributed throughout the year, so 

seasonal daily emissions were calculated by dividing annual emissions by 366.

For graphic arts, the U.S. EPA’s default temporal allocation profiles from its emissions 

modeling clearinghouse were used (U.S. EPA, 2002b). This temporal allocation profile is shown 

in Table 3-40.

Table 3-40. Temporal Allocation Profile Assignment for Graphic Arts

Category

Profile 

ID Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Ozone 

Factor

PM 

Factor

Graphic 

Arts 257 83 83 82 82 82 84 84 84 84 84 84 83 0.5846 0.3333
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3.2.12 Bakeries and Consumer Solvents

No Idaho-specific seasonality could be established for the per capita emission factor 

source categories (i.e., consumer bakeries and solvents). Therefore, it was assumed that 

emissions were equally distributed throughout the year, so seasonal daily emissions were 

calculated by dividing annual emissions by 366.

3.2.13 Dry Cleaning

Although the dry cleaning survey included a question regarding month-to-month 

variations, almost all of the dry cleaning facilities that returned the survey did not respond to this 

question. Therefore, the U.S. EPA’s default temporal allocation profiles from its emissions 

modeling clearinghouse were used for dry cleaning (U.S. EPA, 2002b). This temporal allocation 

profile is shown in Table 3-41.

Table 3-41. Temporal Allocation Profile Assignment for Dry Cleaning

Category

Profile 

ID Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Ozone 

Factor

PM

Factor

Dry 

Cleaning 199 82 82 81 81 81 85 85 85 85 85 85 82 0.5876 0.3313

3.2.14 Asphalt Application

Local staff at the Idaho Transportation Department and the Canyon Highway District 

were contacted regarding the seasonality of asphalt application (Morrison, 2010b; Newlun, 2010; 

Richard, 2010b). These staff indicated that generally asphalt application corresponds with the 

ozone season months and is not conducted during the winter (i.e., PM season). Therefore, daily 

ozone season asphalt emissions were calculated by dividing annual emissions by the number of 

days in the ozone season (i.e., 214 days).

3.2.15 Pesticide Application

As discussed below in Section 3.2.20, it was assumed that all tilling and harvesting 

activities occur during the ozone season. Based upon this assumption, it is also reasonable to 

assume that most pesticide application also occurs during the ozone season (i.e., between tilling 

and harvesting). The crop profiles examined during the development of the annual pesticide 

application emissions indicate only minimal amounts of pre-planting or off-season pesticide use. 

Daily emissions were calculated by dividing annual emissions by the number of days in the 

ozone season (i.e., 214 days).
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3.2.16 Gasoline Distribution

The gasoline distribution statistics were originally provided on a monthly basis. These 

monthly gasoline quantities were then used to develop seasonal gasoline quantities which were 

then divided by the number of days in the season resulting in seasonal daily gasoline use.

3.2.17 Wastewater Treatment

As part of the fuel survey mailed out to wastewater treatment facilities, monthly 

treatment quantities were requested. In general, the treatment facilities were able to furnish 

relevant monthly statistics. In a few cases, respondents were contacted by phone to clarify the 

appropriate seasonal distribution. These monthly treatment quantities were used to develop 

seasonal treatment quantities which were then divided by the number of days in the season 

resulting in seasonal daily treatment quantities.

3.2.18 Landfills

Although emissions from landfills are affected by the landfill gas temperature, it was not 

clear what the relationship between landfill gas temperature and ambient temperature was. 

Therefore, it was assumed that emissions were equally distributed throughout the year, so 

seasonal daily emissions were calculated by dividing annual emissions by 366.

3.2.19 Open Burning (Yard Waste and Household Waste)

No definite seasonality could be established for the open burning of yard waste and 

household waste. Therefore, it was assumed that emissions were equally distributed throughout 

the year, so seasonal daily emissions were calculated by dividing annual emissions by 366. It is 

possible that an announced burn ban might prevent open burning on a particular day with poor 

air quality, but the open burning would likely only be postponed to the next allowable burn day 

and would not significantly affect the overall temporal profile. It is also possible that an 

announced burn ban might also be ignored.

3.2.20 Agricultural Tilling and Harvesting

Based upon the Idaho Crop Progress and Condition Reports issued by the National 

Agricultural Statistics Service (NASS, 2009b), the weekly crop progress (from April 6 to 

October 28) was identified. These weekly progress reports indicate regional climate, crop 

growth progress, and percent planted and harvested for the primary Idaho crops in four different 
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regions. Nearly all of the Idaho crops within Ada, Canyon, and Elmore counties are planted and 

harvested during the crop progress reporting period. Since the crop progress reporting period 

very closely corresponds to the ozone season, it was assumed that all tilling and harvesting 

activities occur during the ozone season. Daily emissions were calculated by dividing annual 

emissions by the number of days in the ozone season (i.e., 214 days).

3.2.21 Agricultural Burning – Fields

As indicated in Section 3.1.21, agricultural field burning was only allowed between 

September 1 and October 31, 2008. Daily emissions were calculated by dividing annual 

emissions by the number of days in the ozone season (i.e., 214 days).

3.2.22 Agricultural Burning – Irrigation Ditches

As indicated in Section 3.1.22, irrigation ditch burning is typically conducted during the 

month of March. Since March is not included in either the ozone season or PM season, no daily 

seasonal emissions were calculated.

3.2.23 Beef Cattle Feedlots

No definite seasonality could be established for beef cattle feedlots. Therefore, it was 

assumed that emissions were equally distributed throughout the year, so seasonal daily emissions 

were calculated by dividing annual emissions by 366.

3.2.24 Other Fires

The Idaho Fire Incident Reporting System (IFIRS) did not provide any seasonal 

distribution of structure fires or vehicles. Therefore, it was assumed that emissions were equally 

distributed throughout the year, so seasonal daily emissions were calculated by dividing annual 

emissions by 366.

3.2.25 Windblown Dust

As discussed in Section 3.1.25, annual emissions were calculated by summing hourly 

emission estimates across all days in calendar year 2008. Ozone season day emissions were 

calculated by summing all hourly estimates across all days in the season (April through October) 

and dividing by the total number of days in the ozone season. Similarly, PM season emission 
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Final, August 31, 2010

3-77

estimates were obtained by summing across all hours from November through February and 

dividing by the total number of days in the PM season.

3.2.26 Ammonia Emissions

As discussed in Section 3.1.26, the GIS NH3 model was run for each day in the 2008 

calendar year on the 4-km modeling domain. Annual emissions were calculated by summing 

hourly emission estimates across all days in calendar year 2008. Ozone season day emissions 

were calculated by summing all hourly estimates across all days in the season (April through 

October) and dividing by the total number of days in the ozone season. Similarly, PM season 

emission estimates were obtained by summing across all hours from November through February 

and dividing by the total number of days in the PM season.

3.3 Emission Results

The 2008 annual area source emissions are presented in Table 3-42 (all counties), 3-43

(Ada County), 3-44 (Canyon County), and 3-45 (Elmore County). These emissions have been 

presented for aggregated source categories. Detailed 2008 annual area source emission 

inventories are presented in Appendix G. The paved road dust PM10 and PM2.5 emissions were 

updated by DEQ in 2012, as described in Appendix E of the Northern Ada County PM10 Limited 

Maintenance Plan Ten-Year Update.
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Table 3-42. Summarized 2008 Annual Area Source Emissions – All Counties

Aggregated Source 

Category

NOx

(tpy)

SO2

(tpy)

VOC 

(tpy)

CO

(tpy)

PM10

(tpy)

PM2.5

(tpy)

NH3

(tpy)

Industrial Combustion 269 2 13 194 19 17 9

Commercial/Institutional 

Combustion 311 11 15 226 22 22 4

Residential Combustion 

(excluding wood) 689 5 39 280 53 52 129

Residential Wood 

Combustion 269 33 2,760 14,774 2,712 2,712 0

Commercial Cooking 0 0 191 600 1,201 1,133 0

Other Industrial 

Activitiesa 0 0 104 0 161 16 51

Industrial Surface 

Coating 0 0 3,235 0 0 0 0

Other Surface Coatingb0 0 1,245 0 0 0 0

Degreasing 0 0 7,383 0 0 0 0

Consumer Solvents 0 0 2,142 0 0 0 0

Other Solvent 

Applicationc 0 0 1,541 0 0 0 0

Gasoline Transport and 

Distribution 0 0 1,397 0 0 0 0

Open Burning 9 2 70 262 87 82 0

Other Fires 1 0 5 23 7 7 0

Waste Disposald0 0 88 0 0 0 1

Agricultural Burning 0 0 20 174 31 31 0

Other Agriculturale0 0 1,953 0 1,408 387 0

Paved Road Dustf0 0 0 0 12,908 949 0

Unpaved Road Dust 0 0 0 0 3,779 327 0

Windblown Dust 0 0 0 0 27,214 2,722 0

Ammonia - Fertilizer 0 0 0 0 0 0 4,469

Ammonia - Livestock 0 0 0 0 0 0 7,748

Ammonia - Domestic 

Ammonia 0 0 0 0 0 0 447

Ammonia - Wild 

Animals 0 0 0 0 0 0 182

Ammonia - Soils 0 0 0 0 0 0 3,494

Totalf1,547 52 22,201 16,533 49,602 8,457 16,534

a

Includes bakeries, construction, and industrial refrigeration.

b

Includes architectural surface coating, autobody refinishing, and traffic markings.

c

Includes dry cleaning, graphic arts, asphalt application, and pesticides application.

d

Includes landfills and wastewater treatment.

e

Includes agricultural tilling, agricultural harvesting, and beef cattle feedlots.

fPaved road dust emissions for Ada and Canyon counties (PM10 and PM2.5) were revised in 2012.
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3-79

Table 3-43. Summarized 2008 Annual Area Source Emissions – Ada County

Aggregated

Source Category

NOx

(tpy)

SO2

(tpy)

VOC 

(tpy)

CO

(tpy)

PM10

(tpy)

PM2.5

(tpy)

NH3

(tpy)

Industrial Combustion 110 1 5 80 8 7 4

Commercial/Institutional 

Combustion 225 8 11 168 16 16 2

Residential Combustion (excluding 

wood) 463 3 27 194 37 37 94

Residential Wood Combustion 122 15 1,239 6,713 1,208 1,208 0

Commercial Cooking 0 0 145 455 912 860 0

Other Industrial Activitiesa0 0 67 0 94 9 10

Industrial Surface Coating 0 0 2,229 0 0 0 0

Other Surface Coatingb0 0 889 0 0 0 0

Degreasing 0 0 4,749 0 0 0 0

Consumer Solvents 0 0 1,374 0 0 0 0

Other Solvent Applicationc0 0 837 0 0 0 0

Gasoline Transport and Distribution 0 0 887 0 0 0 0

Open Burning 0 0 9 47 10 10 0

Other Fires 0 0 3 13 4 4 0

Waste Disposald0 0 63 0 0 0 1

Agricultural Burning 0 0 5 44 8 8 0

Other Agriculturale0 0 425 0 185 49 0

Paved Road Dustf0 0 0 0 7,501 428 0

Unpaved Road Dust 0 0 0 0 966 55 0

Windblown Dust 0 0 0 0 8,606 861 0

Ammonia - Fertilizer 0 0 0 0 0 0 571

Ammonia - Livestock 0 0 0 0 0 0 1,706

Ammonia - Domestic Ammonia 0 0 0 0 0 0 278

Ammonia - Wild Animals 0 0 0 0 0 0 38

Ammonia - Soils 0 0 0 0 0 0 1,292

Totalf921 27 12,963 7,715 19,555 3,552 3,995

a

Includes bakeries, construction, and industrial refrigeration.

b

Includes architectural surface coating, autobody refinishing, and traffic markings.

c

Includes dry cleaning, graphic arts, asphalt application, and pesticides application.

d

Includes landfills and wastewater treatment.

e

Includes agricultural tilling, agricultural harvesting, and beef cattle feedlots.

fPaved road dust emissions for Ada and Canyon counties (PM10 and PM2.5) were revised in 2012.
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3-80

Table 3-44. Summarized 2008 Annual Area Source Emissions – Canyon County

Aggregated

Source Category

NOx

(tpy)

SO2

(tpy)

VOC 

(tpy)

CO

(tpy)

PM10

(tpy)

PM2.5

(tpy)

NH3

(tpy)

Industrial Combustion 156 1 7 112 11 10 5

Commercial/Institutional 

Combustion 71 2 3 51 5 5 1

Residential Combustion (excluding 

wood) 195 2 10 74 14 13 31

Residential Wood Combustion 123 14 1,269 6,670 1,251 1,251 0

Commercial Cooking 0 0 39 123 246 232 0

Other Industrial Activitiesa0 0 32 0 59 6 39

Industrial Surface Coating 0 0 905 0 0 0 0

Other Surface Coatingb0 0 327 0 0 0 0

Degreasing 0 0 2,403 0 0 0 0

Consumer Solvents 0 0 663 0 0 0 0

Other Solvent Applicationc0 0 539 0 0 0 0

Gasoline Transport and Distribution 0 0 428 0 0 0 0

Open Burning 1 0 16 73 19 19 0

Other Fires 0 0 2 8 3 3 0

Waste Disposald0 0 22 0 0 0 0

Agricultural Burning 0 0 13 111 20 20 0

Other Agriculturale0 0 829 0 720 206 0

Paved Road Dustf0 0 0 0 4,154 237 0

Unpaved Road Dust 0 0 0 0 165 9 0

Windblown Dust 0 0 0 0 888 89 0

Ammonia - Fertilizer 0 0 0 0 0 0 2,879

Ammonia - Livestock 0 0 0 0 0 0 3,424

Ammonia - Domestic Ammonia 0 0 0 0 0 0 147

Ammonia - Wild Animals 0 0 0 0 0 0 4

Ammonia - Soils 0 0 0 0 0 0 1,197

Totalf546 19 7,508 7,222 7,555 2,100 7,727

a

Includes bakeries, construction, and industrial refrigeration.

b

Includes architectural surface coating, autobody refinishing, and traffic markings.

c

Includes dry cleaning, graphic arts, asphalt application, and pesticides application.

d

Includes landfills and wastewater treatment.

e

Includes agricultural tilling, agricultural harvesting, and beef cattle feedlots.

fPaved road dust emissions for Ada and Canyon (PM10 and PM2.5) were revised in 2012.
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3-81

Table 3-45. Summarized 2008 Annual Area Source Emissions – Elmore County

Aggregated

Source Category

NOx

(tpy)

SO2

(tpy)

VOC 

(tpy)

CO

(tpy)

PM10

(tpy)

PM2.5

(tpy)

NH3

(tpy)

Industrial Combustion 3 0 0 2 0 0 0

Commercial/Institutional 

Combustion 14 1 0 7 1 1 0

Residential Combustion 

(excluding wood) 30 0 2 12 2 2 4

Residential Wood 

Combustion 25 3 252 1,391 254 254 0

Commercial Cooking 0 0 7 22 44 41 0

Other Industrial 

Activitiesa0 0 5 0 8 1 3

Industrial Surface 

Coating 0 0 102 0 0 0 0

Other Surface Coatingb0 0 29 0 0 0 0

Degreasing 0 0 231 0 0 0 0

Consumer Solvents 0 0 105 0 0 0 0

Other Solvent 

Applicationc0 0 165 0 0 0 0

Gasoline Transport and 

Distribution 0 0 82 0 0 0 0

Open Burning 8 1 46 142 57 53 0

Other Fires 0 0 0 2 0 0 0

Waste Disposald0 0 4 0 0 0 0

Agricultural Burning 0 0 2 19 3 3 0

Other Agriculturale0 0 698 0 502 133 0

Paved Road Dust 0 0 0 0 1,253 284 0

Unpaved Road Dust 0 0 0 0 2,648 262 0

Windblown Dust 0 0 0 0 17,720 1,772 0

Ammonia - Fertilizer 0 0 0 0 0 0 1,019

Ammonia - Livestock 0 0 0 0 0 0 2,618

Ammonia - Domestic 

Ammonia 0 0 0 0 0 0 22

Ammonia – Wild 

Animals 0 0 0 0 0 0 140

Ammonia - Soils 0 0 0 0 0 0 1,006

Total 80 6 1,730 1,596 22,492 2,806 4,812

a

Includes bakeries, construction, and industrial refrigeration.

b

Includes architectural surface coating, autobody refinishing, and traffic markings.

c

Includes dry cleaning, graphic arts, asphalt application, and pesticides application.

d

Includes landfills and wastewater treatment.

e

Includes agricultural tilling, agricultural harvesting, and beef cattle feedlots.

3.4 QA/QC Procedures

For the area source inventory development, the procedures described in the project 

IPP/QAP (ERG and ENVIRON, 2009) were used to check, and correct when necessary, the area 

source emission estimates. Area source emissions were estimated using calculational 

spreadsheets. Separate spreadsheets were developed for each area source category; these 
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3-82

category-specific spreadsheets were then linked to a summary spreadsheet. The calculation 

spreadsheets were well-documented and clearly identify the source of various activity data. All 

emission calculations were internally checked by senior ERG staff and reviewed by the project 

QA/QC manager. Special attention was paid to the source categories for which a survey was 

conducted (i.e., fuel dealers and distributors, dry cleaners, wastewater treatment, and landfills). 

After obtaining the returned survey forms in scanned PDF format, ERG manually transcribed the 

data into an Access database using a front-end form. All input data were checked against the 

returned survey forms by senior ERG staff for accuracy. 
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4-1

4.0 2008 ON-ROAD MOTOR VEHICLE SOURCE EMISSIONS INVENTORIES

On-road mobile source emission estimates prepared by Environ and DEQ in 2010 for 

this emission inventory were originally developed using U.S. EPA’s MOBILE6.2 vehicle

emissions model. U.S. EPA recently (December 2010) released an entirely new vehicle 

emissions model, the Motor Vehicle Emission Simulator 2010, Version a or MOVES2010a (U.S. 

EPA, 2010c ). Referred to generically as “MOVES,” this model is now the official U.S. EPA 

vehicle emissions model required to be used in all SIP modeling and conformity determinations. 

MOVES will completely replace its predecessor model, MOBILE6.2, after March 2013, which is

the end of the grace period for SIPs that were already in progress at the time of the new model’s 

release. Because the conformity requirements will be based on the MOVES model by March 

2013, it became necessary for the purposes of the Northern Ada County PM10 Limited 

Maintenance Plan Ten-Year Update to establish new motor vehicle emission budgets (MVEB)

based on the same model. As a result, DEQ proceeded with MOVES modeling to update the onroad mobile portion of this emissions inventory. DEQ used approximately the same 

methodologies originally used by Environ for processing Travel Demand Model outputs from 

COMPASS and detailed traffic count data and motor vehicle registration data from the Idaho 

Transportation Department in the preparation of local inputs for the MOVES2010a model. The 

sources of information and methods for processing the data into the MOVES input database are

described in Appendix E of the Northern Ada County PM10 Limited Maintenance Plan Ten-Year 

Update, entitled “Development of the Base- and Future-Year Mobile Source Emission 

Inventories for the Treasure Valley, Idaho.” Results from the updated MOVES modeling 

conducted by DEQ for Ada and Canyon counties are summarized in Table 4-1. All subsequent 

tables in this report summarizing on-road and area source emissions are updated to reflect the 

revised MOVES modeling and road dust emissions computations prepared by DEQ after 

ERG/Environ completed the emissions inventories in 2010. In all updated tables, DEQ-revised 

values based on the updated MOVES and paved road dust computations are shown in italic.
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4-2

Table 4-1. 2008 On-road Emissions Summary (Tons/Year and Tons/Day)

a

Averaging Period County NOX SO2 VOC CO PM10 PM2.5 NH3

Annual

Ada 9,775.4 67.4 4,182.3 47,168.3 412.7 330.4 152.9

Canyon 5,847.8 35 3,202.1 36,404.4 258.2 212.1 81.8

Elmore 576.6 3.1 529.8 5,460.8 14.7 9.3 30.7

Average Ozone Season 

Day

Ada 28.5 0.2 10.9 110.9 1.09 0.86 0.45

Canyon 16.7 0.1 8.4 87.9 0.65 0.52 0.24

Elmore 1.5 0.0 1.5 11.0 0.0 0.0 0.1

Average PM Season 

Day

Ada 24 0.16 12.3 156.4 1.19 0.98 0.38

Canyon 14.8 0.09 9.28 117.1 0.8 0.67 0.2

Elmore 1.6 0.0 1.1 17.2 0.0 0.0 0.1

a

On-road emission estimates were revised in 2012 for the Northern Ada County PM10 Limited Maintenance 

Plan Ten-Year Update using the MOVES2010a model. Ada and Canyon counties on-road emissions values are 

from Appendix E of the Ten-Year Update, entitled “Development of the Base- and Future-Year Mobile Source 

Emission Inventories for the Treasure Valley, Idaho." Elmore County emissions based on the MOBILE6.2 

model were not revised. Table values revised in 2012 are shown in italic.
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5-3

5.0 2008 NONROAD MOBILE SOURCE EMISSIONS INVENTORY

Nonroad mobile sources encompass a wide variety of equipment types that either move 

under their own power or are capable of being moved from site to site. Nonroad mobile 

equipment sources, not licensed or certified as highway vehicles, are defined as those that move 

or are moved within a 12 month period and are covered under the U.S. EPA's emissions 

regulations as nonroad mobile sources. There are three types of nonroad mobile sources: 

nonroad equipment, locomotives, and aircraft 

5.1 Emission Calculation Methodologies – Annual 

The methodologies used to calculate annual nonroad mobile source emissions for the 

2008 base year are presented in this section. Methods pertaining to nonroad equipment, aircraft, 

and locomotives are discussed. 

5.1.1 Nonroad Equipment 

The largest group of nonroad mobile sources are nonroad equipment that are estimated 

with the NONROAD2008 model (U.S. EPA, 2009b). The NONROAD model estimates 

emissions from nonroad equipment in the categories shown below; Treasure Valley emissions 

from all listed categories but airport ground support equipment were estimated using the 

NONROAD model.

 Agricultural equipment (e.g., tractors, combines, balers, etc.)

 Airport ground support (e.g., terminal tractors, etc.)

 Construction equipment (e.g., graders, backhoes, etc.)

 Industrial and commercial equipment (e.g., forklifts, sweepers, etc.)

 Recreational vehicles (e.g., all-terrain vehicles, off-road motorcycles, etc.)

 Residential and commercial lawn and garden equipment (e.g., lawnmowers, leaf 

blowers, snow blowers, etc.)

 Logging equipment (e.g., shredders, large chain saws, etc.)

 Recreational equipment (e.g., off-road motorbikes, snowmobiles, etc.)

 Recreational marine vessels (e.g., power boats, etc.).
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5-4

Data Collection

Key inputs for determining nonroad equipment emissions using the NONROAD model 

are equipment population and activity data, and allocation factors. Nonroad equipment 

population by county is estimated in the model by geographically allocating national engine 

population through the use of econometric indicators, such as construction valuation. U.S. EPA 

encourages state and local agencies to develop local data from surveys, but such work is 

expensive and difficult to carry out, and only a few agencies in the country have done so. 

However, some local information for Idaho populations was available and these data were used 

to update the NONROAD model data as described below.

Pleasure Craft and Recreational Equipment Population 

Pleasure craft and recreational equipment population data were collected from the Idaho 

Department of Parks and Recreation (IDPR, 2009a; IDPR, 2009b). The state registration data 

were assumed to be equal to the state total pleasure craft and recreational equipment population. 

Although county-level registration data were available, county-level data were not used for 

county allocation purposes. Registration is not considered to be a suitable surrogate for pleasure 

craft or recreational equipment activity because these types of equipment are often used in 

counties other than where they are registered. The current U.S. EPA NONROAD allocation 

method uses water surface area for pleasure craft and the number of RV parks and recreational 

camps (NAICS code 72121X) from County Business Patterns because they are considered to be 

better indications of actual usage in each area.

Table 5-1 shows a comparison of NONROAD model default and Parks and Recreation 

derived by-county population estimates for 2008. 

Table 5-1. 2008 Pleasure Craft and Recreational Equipment Populations

NONROAD Default Revised

Equipment Type Ada Canyon Elmore Ada Canyon Elmore

Pleasure Craft

Inboards 94 242 396 100 256 420

Outboards 379 976 1599 412 1060 1737

Personal watercraft 51 132 216 56 143 235

Recreational Equipment

All terrain vehicles 12539 1567 3135 10113 1264 2528

Motorcycles: off-road 3033 379 758 3093 387 773
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5-5

One potential source of double-counting could not be eliminated in the recreational 

marine data. The Idaho Department of Parks and Recreation does not make a distinction in its 

boat registrations for boats that are completely non-motorized (i.e., sailboats with no on-board 

engines). Although these boats do not contribute to emissions, there was no way to determine 

the fraction of the registered boats that fit this category. It was assumed that these nonmotorized sailboats comprise a negligible portion of the recreational marine population.

Agricultural Equipment Population 

Agricultural equipment population estimates obtained from the 2007 Census of 

Agriculture (USDA, 2009) were used to modify the NONROAD default population files. Table 

5-2 shows the NONROAD model default and revised agricultural equipment populations. Given 

the large differences in agricultural tractor population estimates between the NONROAD model 

and the Census of Agriculture, it is important to note that the Census of Agriculture statistics may 

not be fully compatible with the NONROAD model activity estimates (hours per year). 

NONROAD equipment population estimates may consider only those pieces of equipment that 

are active, while the Census of Agriculture counts all equipment types including those pieces of 

equipment that are rarely used. In the NONROAD model, agricultural equipment population 

estimates are derived by allocating the nationwide population to the state level according to the 

fraction of harvested cropland within each state; statewide population is then allocated to the 

county level using the same metric. The advantage of using the Census of Agriculture is that it 

contains actual population estimates for specific types of agricultural equipment in each county, 

as opposed to the NONROAD model, which relies on the scaling of nationwide data to the 

county level.

Table 5-2. NONROAD Model Default and Revised Agricultural Equipment 

Populations

Equipment Type

NONROAD Default Revised

Ada Canyon Elmore Ada Canyon Elmore

Agricultural Equipment

2-Wheel tractors 1 4 2 14 23 4

Agricultural tractors 320 971 482 1921 4335 878

Combines 65 196 97 59 201 34
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5-6

Agricultural Equipment Temporal Profile 

Areas of harvested crop acreage and crop budgets were obtained from the National 

Agricultural Statistics Service (NASS) (NASS, 2009a; NASS, 2009b). This information was 

used to develop the monthly agricultural equipment usage profile shown in Figure 5-1. Similar 

to the default profile, the local profile shows high activity for agricultural equipment in the 

summer, and it also incorporates higher activity in spring and fall months due to planting and 

harvesting operations which occur during these seasons.

Agricultural Temporal Profile

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Local

NR default

Note: Two activities cause increased activity in Oct relative to Sep:

1) disking and plowing in Oct/Nov for winter wheat, with no Sep activity for this crop, 

and 

2) completion of all activity in August for some crops 

Figure 5-1. Local Off-Road Agricultural Equipment Monthly Temporal Profile

Construction Equipment Temporal Profile

Telephone interviews were conducted with municipal government staff located within the

inventory domain with knowledge of various types of construction (McCain, 2010; Winterfeld, 

2010; Walter, 2010; Chase, 2010; Girard, 2010). Based on employee input, local construction 

equipment monthly temporal profiles were estimated as shown in Figure 5-2. Similar to the 

default profile, the local profile shows high activity for construction equipment in the summer, 

and it incorporates higher activity in the late spring months relative to the default profile.
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5-7

Construction Compare

0.000

0.020

0.040

0.060

0.080

0.100

0.120

0.140

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Ada

Canyon

Elmore

NONROAD Default

Figure 5-2. Local Construction Equipment Monthly Temporal Profile

Lawn and Garden Equipment Temporal Profiles

Lawn and garden equipment temporal profiles were developed using a methodology 

similar to what was applied to develop lawn and garden equipment temporal profiles for the 

Lake Michigan Air Directors Consortium (ECR, 2005). Lawn and garden equipment was 

divided into four usage associations: lawn-related, soil-related, leaf-related, and wood-related, 

the details of these usage associations are shown in Table 5-3. 

Staff from the City of Boise Park and Recreational Service Department (Woodward, 

2010; Teddicken, 2010), Ada County Highway District (Mills, 2010) and the City of Nampa 

Parks (Moran 2010) were contacted regarding monthly temporal profiles for the usage of each of 

these types of equipment. Based upon these local data, local lawn and garden equipment 

seasonal usage profiles were estimated as shown in Figures 5-3 and 5-4. The NONROAD 

default temporal profile is a single profile applied to all types of lawn and garden equipment and

shows the highest activity in the summer and relatively lower activity in the spring and fall and 

very little activity in the winter. Local data indicated that lawn-related equipment usage was 

highest in the summer, as expected, with activity in the spring slightly higher than activity in the 

autumn and very low activity in the winter. For soil-related equipment, the highest activity was 
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5-8

associated with the spring and fall due to activities such as planting and plant removal which 

occur during these seasons. Wood-related equipment activity was estimated to be the highest in 

the spring due to wood cutting activity that occurs during this season.

Table 5-3. Lawn and Garden Equipment Temporal Profile Groupings

Equipment Type Usage Association

Front mowers

Lawn

Lawn & garden tractors

Lawn mowers

Other lawn & garden equipment

Rear engine riding mowers

Trimmers/edgers/brush cutters

Leafblowers/vacuums Leaf

Commercial turf equipment Soil Rotary tillers < 6 HP

Chain saws < 6 HP

Wood Chippers/stump grinders

Shredders < 6 HP

Wood splitters

L&G lawn, soil, and leaf related

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

NONROAD Default

Lawn-related

Soil-related

Leaf-related

Figure 5-3. Local Lawn-, Soil-, and Leaf-Related Lawn and Garden Equipment 

Monthly Temporal Profiles 
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5-9

L&G wood related

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

NONROAD Default

Wood-related

Figure 5-4. Local Wood-Related Lawn and Garden Equipment Monthly Temporal 

Profile

Emission Calculation Methodology

In order to incorporate seasonal changes in climate and fuels, annual emissions were 

estimated by running the NONROAD model for each of the four seasons, then summing the 

seasonal emissions to generate annual emissions. Seasonal average maximum, minimum, and 

mean temperatures were based on period of record monthly averages from the Western Regional 

Climate Center for the following stations: Boise WSFO Airport (Ada County), Nampa Sugar 

Factory (Canyon County), and Mountain Home (Elmore County) (WRCC, 2009). Gasoline Reid 

vapor pressure (RVP) consistent with on-road MOBILE6 inputs by county and season are shown 

in Table 5-4. Gasoline was assumed to have a fuel sulfur content of 30 parts per million, 

consistent with on-road gasoline, while diesel fuel was assumed to have a fuel sulfur content of 

500 parts per million per the federal Tier 4 nonroad diesel rule.

Table 5-4. 2008 Gasoline RVP (psi) by Season

Season Ada County Canyon County Elmore County

Winter 15 15 15

Spring 15 15 13.5

Summer 8.6 8.6 9

Autumn 8.6 8.6 11.5
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5-10

Annual base year 2008 nonroad equipment emissions are shown in Table 5-5 and Table 

5-6 by county and equipment type, respectively. A majority of the nonroad equipment emissions 

for all pollutants were emitted in Ada County. Like most nonroad emission inventories, the 

primary source of VOC and CO emissions was lawn and garden equipment which is primarily 

made up of gasoline fueled equipment. The highest contributors to NOx, PM10, PM2.5, SO2, and 

NH3 emissions were agricultural and construction equipment, which are primarily diesel-fueled 

equipment.

Table 5-5. 2008 Annual Nonroad Equipment Emissions by County

County VOC CO NOx PM10 PM2.5 SO2 NH3

Annual Total (tons/year)

Ada 1,946 23,923 2,402 236 226 66 2.5

Canyon 656 7,345 1,515 147 142 44 1.4

Elmore 316 1,566 328 35 34 9 0.3

Total 2,918 32,835 4,245 418 402 119 4.2

Table 5-6. 2008 Annual Nonroad Equipment Emissions by Equipment Type (Ada, 

Canyon, and Elmore Counties Combined)

Category VOC CO NOx PM10 PM2.5 SO2 NH3

Annual Total (tons/year)

Agricultural Equipment 146 1,040 1,254 130 126 38 1.0

Commercial Equipment 343 6,766 240 21 20 5 0.4

Construction and Mining 

Equipment 284 2,326 1,919 171 166 64 1.8

Industrial Equipment 141 2,336 552 21 20 8 0.2

Lawn and Garden Equipment 1,162 17,215 214 52 48 3 0.7

Logging Equipment 4 38 7 1 1 0 0.0

Pleasure Craft 261 829 35 5 4 0 0.1

Railroad Equipment 1 12 5 1 1 0 0.0

Recreational Equipment 576 2,273 19 17 16 0 0.1

Underground Mining Equipment 0 0 0 0 0 0 0.0

Total 2,918 32,835 4,245 418 402 119 4.2

5.1.2 Aircraft

Base year 2008 emissions from aircraft and associated equipment (i.e., auxiliary power 

units [APU] and airport ground support equipment [GSE], for 2008 were obtained from work 

performed to develop U.S. EPA’s 2008 National Emissions Inventory (NEI2008). Activity data 

for aircraft emissions are landing-takeoff cycles (LTOs), and emission factors are primarily from 

the Federal Aviation Administration (FAA) Emissions and Dispersion Modeling System 

(EDMS).
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The FAA EDMS model combines specified aircraft and activity levels with default 

emissions factors in order to estimate annual inventories for a specific airport. Aircraft activity 

levels in EDMS are expressed in terms of LTOs, which consist of the four aircraft operating 

modes: taxi and queue, take-off, climb-out, and landing. Default values for the amount of time a 

specific aircraft spends in each mode, or the time-in-modes (TIMs), are coded into EDMS.

Aircraft emissions were estimated for four aircraft categories:

 Air carriers (i.e., larger turbine-powered commercial aircraft with at least 60 seats or 

18,000 lbs payload capacity);

 Air taxis (i.e., commercial turbine or piston-powered aircraft with less than 60 seats 

or 18,000 lbs payload capacity); 

 General aviation aircraft (i.e., small piston-powered, non-commercial aircraft); and 

 Military aircraft. 

Airport GSE includes equipment such as fuel trucks, cabin service truck, baggage belt 

loaders, and pushback tugs and tractors. Auxiliary power units are used to power ventilation, 

cooling, and heating systems when an aircraft’s engine is off and to provide power to start the 

main aircraft engines.

Necessary LTO activity and emissions data in database format, as well as aircraft 

emissions documentation (ERG, 2010) were obtained from U.S. EPA’s NEI2008 website (U.S. 

EPA, 2010b).

The Boise airport was the only airport in the study region for which EDMS was run with 

airport specific activity data. For all other airports, LTO data were applied to average LTO timein-mode and emission factors. Additional calculations were performed to estimate ammonia 

emissions, which were not included in the NEI2008 data. For ammonia, air carriers and military 

aircraft were assumed to be dominated by turbine-powered aircraft running lean, thus producing 

a negligible amount of ammonia. For general aviation and air taxi piston engine aircraft LTOs, 

ammonia emissions were estimated using a fleet-average fuel consumption rate from the EDMS 

data for piston engines, operational mode-specific fuel flow rates weighted by the typical time 

spent in each mode, average hours of operation estimated from FAA data, and a grams per gallon 

emission factor for non-catalyst light-duty gasoline engines.
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Airport GSE and APU emissions were estimated for the NEI2008 by using EDMS 

activity defaults associated with commercial aircraft LTOs and time-in-mode. Airport GSE 

emission factors in EDMS are derived from EPA’s NONROAD2005 model. The main change 

to NONROAD2008 emission rates was incorporating recreational marine diesel and spark 

ignition engine standards; airport ground equipment emission rates did not undergo major 

changes. The NONROAD model estimates county level 2008 airport GSE populations by 

growing historic national population to 2008, and allocating national population according to 

2002 National Emission Inventory (NEI2002) NOx emissions. The NEI2008 airport GSE 

emission estimates were used because these emissions were based on actual 2008 commercial 

aircraft data rather than estimates based on growth projections and allocations used in the 

NONROAD model.

Aircraft associated emissions (including aircraft, APUs, and airport GSE) are presented 

by airport in Table 5-7 and graphically by emission source in Figure 5-5. Consistent with LTO 

activity distribution, Treasure Valley 2008 aircraft associated emissions were dominated by a 

few major airports: Boise Air Terminal/Gowen Field, Caldwell Industrial, and Nampa Muni. 

Together, these airports accounted for 80 percent or more of the aircraft emissions for all 

pollutants, except for NH3. NOx and SO2 emissions are dominated by commercial aircraft, while 

VOC, CO, PM10, PM2.5, and NH3 emissions are primarily from general aviation aircraft.

5.1.3 Locomotives

Locomotive emissions are a significant source of NOx and PM emissions. The 

overwhelming majority of locomotive activity in the United States is from a handful of Class 1 

freight railways, and only one of these, Union Pacific, operates in the Treasure Valley study region.

Railroads operate two types of locomotives – line-haul or switching. Line-haul 

locomotives pull trains over the main line rail system primarily between yards, but may also 

serve individual customers. Switching locomotives assemble and disassemble trains, and serve 

individual customers usually with small trains or individual cars. The line-haul locomotives are 

usually not based at any individual rail yard, and so can operate over a wide region, even across 

the entire country. Switching locomotives are based at individual rail yards for a longer period 

(i.e., 6 months or longer) and therefore operate close to that rail yard.
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Table 5-7. 2008 Aircraft Associated Emissions by Airport (Tons/Year)

Facility Name VOC NOx CO PM10 PM2.5 SO2 NH3

Ada County

Boise Air Terminal/Gowen Field 64.573 208.339 856.022 12.532 9.991 21.498 0.0111

Boise Plaza 0.080 0.005 0.847 0.017 0.012 0.001 0.0000

Green Acres 1.486 0.086 15.810 0.311 0.215 0.013 0.0006

Larkin 1.142 0.066 12.151 0.239 0.165 0.010 0.0005

Nampa Valley 0.080 0.005 0.847 0.017 0.012 0.001 0.0000

Peaceful Cove 1.371 0.079 14.590 0.287 0.198 0.012 0.0006

St. Alphonsus 0.080 0.005 0.847 0.017 0.012 0.001 0.0000

St. Luke’s Boise Medical Center 0.080 0.005 0.847 0.017 0.012 0.001 0.0000

Young 0.080 0.005 0.847 0.017 0.012 0.001 0.0000

Ada County Total 68.97 208.59 902.81 13.45 10.63 21.54 0.01

Canyon County

Caldwell Industrial 39.367 2.351 433.518 8.590 5.927 0.352 0.0170

Hubler Field 2.908 0.167 30.951 0.610 0.421 0.026 0.0012

Mercy 0.080 0.005 0.847 0.017 0.012 0.001 0.0000

Nampa Municipal 30.940 1.785 329.965 6.502 4.487 0.274 0.0132

Parma 0.960 0.055 10.212 0.201 0.139 0.009 0.0004

Sky Ranch North 1.075 0.062 11.436 0.225 0.155 0.010 0.0005

Sky Ranch South 1.075 0.062 11.436 0.225 0.155 0.010 0.0005

Snake River Skydiving 1.075 0.062 11.436 0.225 0.155 0.010 0.0005

Symms 0.960 0.055 10.217 0.201 0.139 0.009 0.0004

Whelan’s 0.080 0.005 0.847 0.017 0.012 0.001 0.0000

Canyon County Total 78.52 4.61 850.87 16.81 11.60 0.70 0.03

Elmore County

Atlanta 0.254 0.015 2.703 0.053 0.037 0.002 0.0001

Coyote Run 0.850 0.049 9.049 0.178 0.123 0.008 0.0004

Dorothy Roeber Memorial 0.080 0.005 0.847 0.017 0.012 0.001 0.0000

Elmore Medical Center 0.080 0.005 0.847 0.017 0.012 0.001 0.0000

Glenns Ferry Municipal 0.113 0.007 1.201 0.024 0.016 0.001 0.0000

Graham USFS 0.254 0.015 2.703 0.053 0.037 0.002 0.0001

Health Center 0.080 0.005 0.847 0.017 0.012 0.001 0.0000

Mountain Home AFB 3.601 1.464 38.188 0.757 0.526 0.112 0.0015

Mountain Home Municipal 5.613 0.373 68.615 1.370 0.946 0.054 0.0024

P and R Field 1.944 0.112 20.688 0.408 0.281 0.017 0.0008

Pine 0.395 0.023 4.205 0.083 0.057 0.004 0.0002

Red Baron Airpark 1.996 0.115 21.245 0.419 0.289 0.018 0.0009

Smith Prairie 0.339 0.020 3.604 0.071 0.049 0.003 0.0001

South Fork Ranch 3.544 0.204 37.715 0.743 0.513 0.031 0.0015

Weatherby USFS 0.212 0.012 2.253 0.044 0.031 0.002 0.0001

Elmore County Total 19.35 2.42 214.71 4.25 2.94 0.26 0.01

Treasure Valley Total 166.84 215.62 1968.38 34.52 25.17 22.49 0.06
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2008 %CAP Emission Contribution by Aircraft type

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

VOC CO NOX PM10-PRI PM25-PRI SO2 NH3

Pollutants

Fraction of Ttoal Emission(tons/yr)

APU 

Airport GSE

Military Aircraft

General Aviation

Air Taxi

Commercial Aircraft

Figure 5-5. 2008 Aircraft Associated Emissions Contributions

Data for the Idaho Treasure Valley study region was gathered from the railroads 

operating within the region and public sources. The line-haul activity data were obtained 

through the Federal Railroad Administration (FRA) with the permission of the Class 1 railroad 

(Union Pacific) in the region. Smaller railroads received a data request for 2008 line-haul and 

switching locomotive activity estimates. Switching data was gathered by requesting for the 

typical shift schedules within each rail yard. The activity data gathered is presented in the 

sections below along with the procedures used to estimate emissions for 2008 and future years.

Line-haul

The activity data used for the line haul emission calculations were gathered from the FRA 

and through data requests. The primary activity data collected under this program are gross 

tonnage (combines the weight of the locomotives, cars, and freight) that are combined with the 

rail link length to estimate gross ton-miles of freight movements (Wright, 2010). Permission was 

obtained from the Class 1 railroad Union Pacific to release the railroad specific activity data for 

2008 within the study domain. Public databases of rail activity for the National Transportation 

Atlas Database only provide link-level mainline activity in activity ranges (BTS, 2009), but the 

FRA data gathered specific activity for the purpose of estimating emission inventories. The FRA 
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data was developed as a result of the request of the Eastern Regional Technical Advisory 

Committee Rail Subgroup, a group of state air quality agencies, to provide accurate rail activity 

estimates.

The FRA dataset attributes are described in Table 5-8. The FRA dataset provided

information about rail links and nodes in the form of ArcGIS shapefiles that provide attribute 

information and location for all rail links at a 1:100,000 scale and was designed for use in 

regional network analysis applications. Rail links were spatially defined polylines that contain a 

large amount of attributes describing a link. The link data relevant to the project included the rail 

line spatial descriptions, as well as the specific activity. The node descriptions were latitude and 

longitude point estimates with actual sinuous link length between nodes. The rail owner field 

defined the primary owner and other railroads that operate on the link. The link status included

what type of track (i.e., main line, siding, or yard trackage), as well as whether the link is in 

operation or abandoned. The FRA dataset is more precise than the National Transportation Atlas 

Data public databases that only provide ranges of gross ton activity rather than the specific 

values used in this report. 

Table 5-8. FRA Rail Link Definitions

Data Field Description

FRA Link ID Numeric identifier

Link Node Descriptions Spatial description

Length Actual length of link

State

County

Rail Owner Primary and secondary

Link Status Operational, main line, etc.

Freight Density Specific annual gross tonnage

Rail ownership was described within the FRA shapefiles in three separate fields. The 

primary owner was assumed to be the first, and most populated, rail owner provided in the 

dataset. Link status provided a code value describing whether the rail link was abandoned, an 

active mainline, or an active non-mainline. Upon review of the active mainline and nonmainline links, it was determined that active mainline links were representative of line-haul 

tracks and non-mainline links were representative of switch or siding tracks. In addition to the 

link route data, the FRA link nodes file spatially described the beginning and end point 
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coordinates of every link. The detailed FRA freight tonnage data were cross-referenced with the 

mainline link route data. Figure 5-6 shows the network densities within the study domain. 

Figure 5-6. FRA Line-Haul Freight Density

The FRA data did not include the Idaho Northern Pacific Railroad (INPR) shortline activity 

that occurs between Boise and Nampa. INPR activity data were obtained through a data request to 

the company (Olmanson, 2010). The data received from INPR is provided in Table 5-9 below.

Table 5-9. Idaho Northern Pacific Railroad Activity Data

INPR Data Request

Locomotive model GP30s

Train count 1 train

Locomotives per train 2 locomotives

Weekly activity 5 days/week

Daily activity 9 hours/day

Fuel consumptiona

226 gal/day

Annual fuel consumption 44,070 gal/year

a

 Fuel consumption based on 24 hours of operation per day
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Line-haul

The 2008 line-haul emissions were estimated using the methodology described in the 

U.S. EPA final emission standards (U.S. EPA, 2009c). This method converted rail gross tonmiles to fuel consumption using railroad freight efficiency to estimate fuel consumption for each 

rail link. The U.S. EPA guidance provided fleet averaged emission factors in terms of grams per 

gallon. This calculation is as follows:

Where:

E = emissions (grams);

FT = freight tonnage (tons);

M = rail link mileage (miles);

FE = freight efficiency (gallons/ton-mile); and 

EF = emission factor (grams/gallons)

The U.S. EPA final emission standards included an analysis of the expected benefit of 

normal fleet turnover and the additional benefit of the U.S. EPA rule. The emission standards 

included both new engine and existing equipment retrofit standards. Existing Tier 0, 1, and 2 

engines will be subject to retrofit at the time of rebuild; so the engines will be rebuilt gradually 

throughout their remaining useful life. The emission standards and implementation dates are 

provided in Tables 5-10 and 5-11 for line-haul and switching locomotives; the emission standard 

values depend primarily upon the duty cycle (i.e., a schedule of time in modes).

The U.S. EPA final emission standards forecasted average emission factors for 

hydrocarbons (HC), carbon monoxide (CO), nitrogen oxides (NOx), and particulate matter (PM) 

in terms of grams per gallon for the calendar years from 2006 to 2040. These U.S. EPA 

forecasts included the impact of new engine emissions standards and the expected rates of new 

locomotive purchases and older locomotive retirements.

E  FT M FEEF
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Table 5-10. Locomotive Emission Standards for Line-haul (Duty Cycle) Engines

Emission Standard

Applicable 

Year

HC

(g/hp-hr)

CO

(g/hp-hr)

NOx

(g/hp-hr)

PM

(g/hp-hr)

Uncontrolled Emissions Pre-1973 0.48 1.28 13.0 0.32

Tier 0 – original 1973-2001 1.00 5.0 9.5 0.60

Tier 0 – finala2008/2010 1.00 5.0 8.0 0.22

Tier 1 – original 2002-2004 0.55 2.2 7.4 0.45

Tier 1 – finala 2008/2010 0.55 5.0 7.4 0.22

Tier 2 – original 2005 0.30 1.5 5.5 0.20

Tier 2 – finala2010/2013 0.30 1.5 5.5 0.10

Tier 3 2012-2014 0.30 1.5 5.5 0.10

Tier 4b2015 0.14 1.5 1.3 0.03

a

Retrofit standards at the time of rebuild and phased in as retrofit kit availability.

b

The Tier 4 NOx standard can be a 1.4 NOx + HC standard.

Table 5-11. Locomotive Emission Standards for Switching (Duty Cycle) Engines

Emission Standard

Applicable 

Year

HC

(g/hp-hr)

CO

(g/hp-hr)

NOx

(g/hp-hr)

PM

(g/hp-hr)

Uncontrolled Emissions Pre-1973 1.01 1.83 17.4 0.44

Tier 0 – original 1973-2001 2.10 8.0 14.00 0.72

Tier 0 – finala 2008/2010 2.10 8.0 11.80 0.26

Tier 1 – original 2002-2004 1.20 2.5 11.00 0.54

Tier 1 – finala 2008/2010 1.20 2.5 11.00 0.26

Tier 2 – original 2005 0.60 2.4 8.10 0.24

Tier 2 – finala 2010/2013 0.60 2.4 8.10 0.13

Tier 3 2012-2014 0.60 2.4 5.00 0.10

Tier 4b2015 0.14 2.4 1.30 0.03

a

These are retrofit standards at the time of rebuild and phased in as retrofit kit availability allows.

b

The Tier 4 NOx standard can be a 1.3 NOx + HC standard.

The U.S. EPA forecast emission factors were scaled from the 1999 uncontrolled emission 

factors (see Table 5-12) on a yearly basis (U.S. EPA, 1997b). The uncontrolled emission factors 

(g/hp-hr) are shown above in Table 5-10 and the 2008, 2015, and 2023 emission factors (g/gal) 

are provided in Table 5-13. The forecast emission factors were converted to grams per gallon of 

fuel using an average of 20.8 horsepower-hours per gallon of fuel for the larger Class 1 railroads 

and 18.2 horsepower-hours per gallon of fuel for other smaller Class 2/3 railroads as described in 

the U.S. EPA standards (U.S. EPA, 2009c). The CO emission rates were not predicted to change 

with the emission controls, so the CO emission rates remain 26.6 grams per gallon for Class 1 

and 23.3 grams per gallon for smaller railroads for all calendar years. The SO2 emission rates 

were determined by converting the fuel sulfur where the fuel sulfur level was assumed to be 351 
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ppm for 2008 based on the U.S. EPA standards (U.S. EPA, 2009c) and 15 ppm for 2015 and 

2023 based on the implementation schedule for locomotive fuel regulations. 

Table 5-12. Locomotive Emission Factors for Calendar Years 1999 and Earlier

Locomotive Type

HC

(g/hp-hr)

CO

(g/hp-hr)

NOx

(g/hp-hr)

PM

(g/hp-hr)

Fuel Consumption

(hp-hr/gallon)

Line-Haula0.48 1.28 13.0 0.32 20.8

aLine-haul locomotives over the line-haul duty-cycle.

Table 5-13. Average Line-Haul Locomotive Emission Factors

Class 1 Class 2/3 Line-Haul

Year

HC

(g/gal)

NOx

(g/gal)

PM

(g/gal)

HC

(g/gal)

NOx

(g/gal)

PM

(g/gal)

2008 9.0 169 5.1 11.7 242 5.7

2015 5.7 129 3.4 11.7 240 5.5

2023 3.0 84 1.9 11.7 223 5.2

In order to derive emission factors in terms of the gross tonnage activity, conversion 

factors from grams per gallon to grams per gross tonnage were estimated. Fuel usage and gross 

tonnage by railroad for the entire system-wide activity were obtained from the AAR (AAR, 

2009). Table 5-14 presents the average system-wide fuel efficiency as well as the individual 

system-wide fuel efficiency for the Class 1 railroad operating in the study region. Combining the 

emission factors in Table 5-13 with the fuel efficiency estimates in Table 5-14, emission factors 

in units of grams per gross ton-mile (GTM) were developed as shown in Table 5-15.

Table 5-14. Fuel Efficiency by Railroad

Railroad

Fuel

Gal/ (GTM)

Average Class 1 0.001020

UP 0.000971

Table 5-15. Class 1 Railroad Emission Factors for 2008

Year Railroad

HC

(g/GTM)

CO

(g/GTM)

NOx

(g/GTM)

PM

(g/GTM)

2008 Average 0.0092 0.027 0.172 0.0052

2008 UP 0.0087 0.026 0.164 0.0050

The emissions factors from Table 5-15 were applied to the FRA activity data by link and 

summed by county; the line-haul emissions results are shown in Table 5-16. 
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Table 5-16. 2008 Line-haul Locomotive Emissions (Tons/Year)

Railroad County HC VOC CO NOx PM10 SO2 NH3

UP Ada 14.68 15.46 43.43 275.70 8.32 3.06 0.19

Canyon 17.91 18.86 52.97 336.24 10.15 3.74 0.23

Elmore 31.11 32.76 92.03 584.18 17.63 6.49 0.40

Total 74.30 78.23 219.79 1395.13 42.10 15.50 0.96

INPR 

Shortline

Ada 0.41 0.43 0.82 8.52 0.20 0.004 0.07

Canyon 0.16 0.16 0.31 3.24 0.08 0.002 0.03

Total 0.57 0.60 1.13 11.76 0.28 0.01 0.09

Switching

Switching locomotives are used for a variety of tasks. The primary task for switchers is 

to break and assemble trains and shuttle rail cars around a rail yard; however, switchers also 

perform short haul duty that includes whole trains, sets of cars, and repositioning equipment 

along the mainline rail lines. The switching locomotives that reposition or short haul freight 

along the mainline were captured under the line-haul gross tonnage, so only the in-yard activity 

was considered for switching locomotive emissions estimates to avoid double counting the 

activity. 

Shift schedules or other estimates of the hours of operation for switching locomotives 

were requested in order to identify the total engine hours of operation at each yard. In general, 

typical shifts were eight or twelve hours using one or two locomotives in tandem. The number 

of hours for each shift was assumed to be the engine operating time; however, this could be an 

overestimate if the engines have idle reduction devices or operators are encouraged to shut off 

the engines during inactive periods of the shift.

At any given time, the roster of switching locomotives assigned to a given yard was 

usually available and was collected as part of the information request. The roster of these 

locomotives could change from week to week, but in general, a sample of the locomotive roster 

at any time in 2008 could be considered a relatively constant fleet mix. The reported switching 

engines ranged from 1,200 to 3,800 rated horsepower. The switching locomotive models were 

all either Tier 0 or precontrolled with no Tier 1 or 2 models. The data in Table 5-17 represented 

the switching activity data for the Nampa Yard obtained from the railroad survey. 
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Table 5-17. Switching Locomotive Activity Data for the Nampa Yard

Number

Days per 

Week Days per Year

Hours per 

Day Hours per Year

Switcher No. 1 5 260 4.5 1170

Switcher No. 2 5 260 7.5 1950

Switcher No. 3 5 260 8.0 2080

Switcher No. 4 1 52 7.5 390

Switcher No. 5 5 260 7.5 1950

Base emission factors and expected forecasted emission rates for switching locomotives 

were provided in U.S. EPA documentation (U.S. EPA, 2008) and are shown in Table 5-18. 

Table 5-18. Switching Locomotive Emission Factors

Year

HC

(g/gal)

CO

(g/gal)

NOx

(g/gal)

PM

(g/gal)

2008 14.5 27.8 243 5.5

2015 12.6 27.8 215 4.8

2023 9.5 27.8 172 3.7

A daily fuel consumption estimate of 226 gallons of fuel per day was provided by other 

U.S. EPA locomotive guidance documentation (U.S. EPA, 1992). The provided fuel 

consumption estimate assumes continuous 24 hour activity resulting in a per hour fuel 

consumption of 9.42 gallons. Annual fuel consumption can be estimated using the following 

equation:

Where:

FC = fuel consumption (gallons/year); 

A = activity (hours/year); and

C = fuel consumption per hour (9.42 gallons/hour).

The emission factors provided in Table 5-18 were combined with the engine-hours in 

Table 5-17 and 9.42 gallons per hour average fuel consumption rate to estimate per yard 

emissions as shown in Table 5-19. 

FC  AC
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Table 5-19. Estimated Switching Locomotive Emissions in 2008

Year

Fuel 

Consumption 

(gal)

HC

(tons)

VOC 

(tons)

CO

(tons)

NOX 

(tons)

PM10

(tons)

SO2

(tons)

NH3

(tons)

2008 71,002 0.92 0.96 1.82 18.94 0.45 0.01 0.15

PM2.5 emission estimates were estimated based on PM10 emission estimates. The 

percentage of PM10 emissions expected to be PM2.5 is assumed to be 97% for locomotives (U.S. 

EPA, 2009c)

In general, the county assignment for the rail yard emissions was straightforward because 

the switching locomotive activity was specific to a particular yard. However, Nampa operations 

could span up to two counties since most of the Nampa tracks are in Canyon County where the 

emissions were allocated, but the tracks may also reach into Ada County.

The 2008 annual emissions by source category are provided in Table 5-20.

Table 5-20. 2008 Annual Locomotive Emissions by Source Category

SCC SCC Description County FIPS

NOx

(tpy)

SO2

(tpy)

VOC 

(tpy)

CO 

(tpy)

PM10

(tpy)

PM2.5 

(tpy)

NH3

(tpy)

2285002006

Diesel Line Haul 

Locomotives: 

Class I operations Ada 16001 275.70 3.06 15.46 43.43 8.32 8.07 0.19

2285002006

Diesel Line Haul 

Locomotives: 

Class I operations Canyon 16027 336.24 3.74 18.86 52.97 10.15 9.84 0.23

2285002006

Diesel Line Haul 

Locomotives: 

Class I operations Elmore 16039 584.18 6.49 32.76 92.03 17.63 17.10 0.40

2285002007

Diesel Line Haul 

Locomotives: 

Class II/III operations Ada 16001 8.52 0.00 0.43 0.82 0.20 0.19 0.07

2285002007

Diesel Line Haul 

Locomotives: 

Class II/III operations Canyon 16027 3.24 0.00 0.16 0.31 0.08 0.07 0.03

2285002010 Diesel Yard Operations Canyon 16027 18.94 0.01 0.96 1.82 0.45 0.43 0.15
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5.2 Emission Calculation Methodologies – Ozone and PM Season

After the annual nonroad mobile source emissions were estimated using the 

methodologies described in Section 2.4.1, the daily ozone season and PM season emission 

estimates were developed. The ozone season extends from April 1 through October 31 (i.e., 214 

days), while the PM season is from November 1 through February 29 (2008 is a leap year) (i.e., 

121 days).

5.2.1 Nonroad Equipment 

Ozone and PM season daily emission estimates for nonroad equipment were based on 

NONROAD model runs for the summer and winter season, respectively. Fuel properties for the 

ozone and PM2.5 season were set to summer and winter season values, respectively, as described 

in Section 2.4.1.1. Climate inputs were derived based on ozone and PM season averages as 

obtained from the WRCC (WRCC, 2009). 

Seasonal base year 2008 nonroad equipment emissions are shown in Table 5-21 and 

Table 5-22 by county and equipment type, respectively. Since most equipment (except 

snowmobiles and snowblowers) were used more frequently in the summer compared to the 

winter, ozone season emissions are greater than PM season emissions in all counties.

Table 5-21. 2008 Seasonal Nonroad Equipment Emissions by County

County VOC CO NOx PM10 PM2.5 SO2 NH3

Ozone Season (tons/day)

Ada 6.97 82.83 8.70 0.87 0.84 0.24 0.009

Canyon 2.51 26.38 5.84 0.58 0.56 0.17 0.005

Elmore 1.56 7.18 1.35 0.15 0.14 0.04 0.001

Total 11.03 116.40 15.89 1.59 1.53 0.45 0.016

PM Season (tons/day)

Ada 4.24 60.18 4.21 0.36 0.35 0.10 0.005

Canyon 1.20 16.85 1.88 0.16 0.16 0.05 0.002

Elmore 0.34 2.36 0.32 0.03 0.03 0.01 0.000

Total 5.78 79.39 6.42 0.56 0.54 0.16 0.007
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

5-24

Table 5-22. 2008 Seasonal Nonroad Equipment Emissions by Equipment Type 

(Ada, Canyon, and Elmore Counties Combined)

Category VOC CO NOx PM10 PM2.5 SO2 NH3

Ozone Season (tons/day)

Agricultural equipment 0.59 4.26 5.12 0.53 0.52 0.15 0.004

Commercial equipment 0.93 18.69 0.64 0.06 0.05 0.01 0.001

Construction and mining 

equipment 1.07 8.86 7.27 0.65 0.63 0.24 0.007

Industrial equipment 0.46 7.64 1.80 0.07 0.07 0.03 0.001

Lawn and garden equipment 3.79 60.76 0.73 0.18 0.16 0.01 0.002

Logging equipment 0.01 0.11 0.02 0.00 0.00 0.00 0.000

Pleasure craft 1.52 5.16 0.22 0.03 0.03 0.00 0.000

Railroad equipment 0.00 0.03 0.01 0.00 0.00 0.00 0.000

Recreational equipment 2.65 10.89 0.08 0.08 0.07 0.00 0.001

Underground mining equipment 0.00 0.00 0.00 0.00 0.00 0.00 0.000

Total 11.03 116.40 15.89 1.59 1.53 0.45 0.016

PM Season (tons/day)

Agricultural equipment 0.10 0.69 0.84 0.09 0.08 0.03 0.001

Commercial equipment 0.90 18.30 0.70 0.06 0.05 0.01 0.001

Construction and mining 

equipment 0.43 3.48 2.92 0.26 0.25 0.10 0.003

Industrial equipment 0.32 5.20 1.24 0.05 0.05 0.02 0.001

Lawn and garden equipment 3.09 48.33 0.64 0.08 0.07 0.01 0.002

Logging equipment 0.01 0.10 0.02 0.00 0.00 0.00 0.000

Pleasure craft 0.15 0.44 0.02 0.00 0.00 0.00 0.000

Railroad equipment 0.00 0.03 0.01 0.00 0.00 0.00 0.000

Recreational equipment 0.78 2.81 0.03 0.02 0.02 0.00 0.000

Underground mining equipment 0.00 0.00 0.00 0.00 0.00 0.00 0.000

Total 5.78 79.39 6.42 0.56 0.54 0.16 0.007

5.2.2 Aircraft 

To estimate seasonal emission inventories, the monthly distribution of activity for the 

Boise airport in the Treasure Valley study region was obtained from the FAA’s Air Traffic 

Activity Data System (ATADS) (FAA, 2010). The ATADS is the official source for historical 

monthly or annual air traffic statistics for airports with FAA-operated or FAA-contracted traffic 

control towers. The average seasonal activity fractions were calculated by aircraft type from the 

ATADS dataset. The seasonal activity fractions (shown in Table 5-23) were then applied to the 

Treasure Valley annual emission by aircraft type to derive the ozone and PM season emissions. 
2008, 2015, 2023 Treasure Valley Emissions Inventories

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5-25

Table 5-23. Fraction of Aircraft Activity Occurring in the Ozone and PM Seasons

Type Ozone Season PM Season

Commercial aircraft 59% 32%

Ground support equipment 59% 32%

Auxiliary power units 59% 32%

Air taxi aircraft 62% 28%

General aviation aircraft 66% 26%

Military aircraft 61% 30%

5.2.3 Locomotives 

The daily emissions for locomotives are reported as the equivalent of the annual 

emissions on a daily scale. The railroads do not report temporal activity and typical of 

locomotive emission inventories, emissions are assumed to be constant year-round. The daily 

emissions were determined by dividing the annual emissions by 365 days per year.

The 2008 ozone and PM season daily emissions by source category are provided in Table 

5-24.

Table 5-24. 2008 Ozone and PM Season Daily Locomotive Emission Estimates by 

Source Category

SCC SCC Description County FIPS

NOx

(tpd)

SO2

(tpd)

VOC 

(tpd)

CO 

(tpd)

PM10

(tpd)

PM2.5

(tpd)

NH3

(tpd)

2285002006

Diesel Line Haul 

Locomotives:

Class I operations Ada 16001 0.755 0.008 0.042 0.119 0.023 0.022 0.0005

2285002006

Diesel Line Haul 

Locomotives:

Class I operations Canyon 16027 0.921 0.010 0.052 0.145 0.028 0.027 0.0006

2285002006

Diesel Line Haul 

Locomotives:

Class I operations Elmore 16039 1.600 0.018 0.090 0.252 0.048 0.047 0.0011

2285002007

Diesel Line Haul 

Locomotives:

Class II/III operations Ada 16001 0.023 0.000 0.001 0.002 0.001 0.001 0.0002

2285002007

Diesel Line Haul 

Locomotives:

Class II/III operations Canyon 16027 0.009 0.000 0.000 0.001 0.000 0.000 0.0001

2285002010

Diesel Yard 

Operations Canyon 16027 0.052 0.000 0.003 0.005 0.001 0.001 0.0004
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5-26

5.3 QA/QC procedures

In order to ensure the highest quality emissions estimates, a number of different QA/QC 

steps were implemented during the development of the nonroad mobile source emissions

inventory. These are outlined below:

 Nonroad Equipment

 NONROAD model inputs, outputs and message files were checked by the data 

generator and reviewed by QA/QC staff.

 QA/QC staff reviewed local data collected and evaluated against national 

defaults.

 Base year emission inventories were compared to U.S.EPA NEI inventories.

 Aircraft

 Aircraft compilation spreadsheets were reviewed by QA/QC staff.

 For airports in the FAA TAF database, NEI2008 LTO activity was checked 

against FAA TAF activity.

 Locomotives

 Locomotive spreadsheets were reviewed by the data generator and reviewed by 

QA/QC staff to assure that calculation inputs and equations were correct.

 Senior QA/QC staff approved emission estimation methodologies and reviewed 

the reference activity data for validity.

 Source identification and data collection were approved by the DEQ staff.

 Senior QA/QC staff confirmed thorough pollutant coverage.

 QA/QC staff reviewed and approved the emission factors and activity data used 

within the emission calculations.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

6-1

6.0 2008 BIOGENIC SOURCE EMISSIONS INVENTORY

Under Task 8 of the contract, the ERG/ENVIRON team provided review of DEQ’s 2008 

biogenic emissions inventory. This review was summarized in a technical memorandum 

submitted to DEQ (Mansell and Sakulyanonvittaya, 2009); this technical memo is provided in 

Appendix F. The technical memo examined the available biogenic emission inventory modeling 

systems, as well as the land cover and vegetation data required for implementation of these 

models. The review also focused on a comparison between DEQ’s biogenics inventory 

developed using the Biogenic Emission Inventory System (BEIS) and an alternative inventory 

developed by ENVIRON using the Model of Emissions of Gases and Aerosol from Nature 

(MEGAN).

6.1 Emissions Calculation Methodologies – Annual 

Input from DEQ modeling staff indicate that the BEIS emission estimates should be 

incorporated into the draft final report and its emission inventory (Hardy, 2010). Therefore, the 

annual biogenic emission summaries for BEIS from Table 2 of the memo were used (Mansell 

and Sakulyanonvittaya, 2009).

6.2 Emissions Calculation Methodologies – Ozone and PM Season

Monthly biogenic emission summaries for BEIS from Table 2 of the memo were used to 

develop ozone and PM season daily emissions (Mansell and Sakulyanonvittaya, 2009). The 

monthly emissions from April to October were summed and then divided by 214 (i.e., the 

number of days in the ozone season) to derive ozone season daily emissions. Likewise, the 

monthly emissions from November to February were summed and then divided by 121 (i.e., the 

number of days in the PM season) to derive PM season daily emissions.

6.3 Emission Results

The emissions presented in the biogenics technical memorandum were developed for 

nitric oxide (NO), CO, VOC, and isoprene. These emissions are shown in Table 6-1.
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Table 6-1. Annual, Ozone Season, and PM Season Biogenic Emissions

Ada Canyon Elmore Total

Annual – NO (tpy) 202.3 283.9 465.2 951.3

Annual – CO (tpy) 2,246.5 1,650.2 6,425.0 10,321.8

Annual – VOC (tpy) 12,802.5 8,902.4 30,982.3 52,687.1

Annual – Isoprene (tpy) 741.2 139.1 2,073.0 2,953.4

Ozone Season – NO (tpd) 0.7 1.0 1.7 3.4

Ozone Season – CO (tpd) 9.4 6.9 26.7 43.0

Ozone Season – VOC (tpd) 55.6 38.5 132.4 226.5

Ozone Season – Isoprene (tpd) 3.4 0.6 9.6 13.6

PM Season – NO (tpd) 0.3 0.4 0.7 1.4

PM Season – CO (tpd) 1.5 1.1 4.7 7.3

PM Season – VOC (tpd) 5.8 4.2 17.3 27.2

PM Season – Isoprene (tpd) 0.1 0.0 0.1 0.2

For purposes of the overall summary tables (Tables 7-5 through 7-16), NO was considered to be 

equivalent to NOx while isoprene was not included since it is a VOC species.
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7-1

7.0 2015 AND 2023 PROJECTED EMISSIONS INVENTORIES

The development of the 2008 base year emissions inventory was described in Sections

2.0 through 6.0. This was followed by the development of projected emissions inventories for 

the future years of 2015 and 2023. The methodologies used to develop these projections are 

described in this section. In general, the projection methodologies identified in the IPP/QAP 

were used; however, some minor adjustments were made based upon projections information 

availability and are identified herein.

7.1 Development of 2015 and 2023 Projection Factors

7.1.1 Point Sources

In an effort to ascertain the future plans for expansion, etc., (on which to base growth 

factors) for the point source facilities located in the Treasure Valley, a total of 18 permitted point 

source facilities were contacted by telephone in May 2010. The facility contacts were informally 

surveyed regarding overall short- and long-term growth and expansion plans. The 18 permitted 

point source facilities constituted the 10 largest VOC emitting facilities, the 3 largest NH3

emitting facilities, and the 5 largest emitting facilities for each of the other pollutants; in some 

cases, a particular facility was a significant emitter of multiple pollutants. Of the 18 facilities 

contacted, a total of 14 contacts responded to the request for information. The facilities that 

responded included the following (listed alphabetically):

 Boise Packaging and Newsprint

 C & B Quality Trailer Works

 Fiber Composites LLC

 Micron Technology

 MotivePower

 Mountain Home Air Force Base

 Northwest Pipeline

 Pacific Press Publishing Association

 Plum Creek Northwest Lumber
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 Saint Alphonsus Regional Medical Center

 Sinclair Boise Products Terminal

 Sorrento Lactalis

 TASCO – Nampa 

 Tesoro Refining and Marketing

Based on these contacts’ responses, the overall short-term outlook (i.e., out to 2015) for 

these facilities is essentially “maintenance of the current status quo”; while the long-term outlook 

(i.e., out to 2023) is basically “unforeseeable”, but some minimal growth is expected. The recent 

economic recession apparently has dampened most expectations for growth in the near-term with 

most facilities moving into a survival posture until the recession has passed. Given these 

anecdotal responses, a 2015 growth factor of 1.0000 (i.e., no growth) and a 2023 growth factor 

of 1.1000 (i.e., minimal 10 percent growth between the years 2015 and 2023) were assigned to 

all point sources. The only exception to this general growth factor assignment was that Sorrento 

Lactalis is currently expanding their facility processing capacity from 4 million gallons of milk 

per day to 5 million gallons of milk per day. This expansion commenced after the 2008 annual 

emissions submittal and so it is not reflected in the base year 2008 inventory (York, 2010). 

Thus, a growth factor of 1.2500 reflecting expanded facility capacity was assigned to both 2015 

and 2023 for the Sorrento Lactalis facility.

7.1.2 Area Sources

The 2015 and 2023 area source projections were developed using a variety of sources of 

projections data. These are described below.

7.1.2.1 Fuel Combustion

All fuel combustion area source categories (i.e., distillate, natural gas, liquefied 

petroleum gas [LPG], kerosene, and wood for the industrial, commercial/ institutional, and 

residential sectors) were estimated using projections data from the Annual Energy Outlook 

(AEO) published by the Energy Information Administration (EIA) (EIA, 2010). Regional 

consumption projections for the Mountain Census Division (i.e., Arizona, Colorado, Idaho, 
2008, 2015, 2023 Treasure Valley Emissions Inventories

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7-3

Montana, Nevada, New Mexico, Utah, and Wyoming) were used to develop growth factors for 

2015 and 2023.

7.1.2.2 Population

Population projections were used to develop projection factors for a wide range of area 

source categories where population is an appropriate surrogate for growth. These categories 

include the following:

 Commercial cooking (i.e., charbroiling and frying)

 Architectural surface coating

 Graphic arts

 Consumer solvents

 Open burning (i.e., yard waste and household waste)

 Wastewater treatment

 Structure fires

 Vehicle fires

Population projections for Ada and Canyon counties were obtained from the 

Community Planning Association of Southwest Idaho (COMPASS) (COMPASS, 2010). 

However, county-level population projections were not available for Elmore County; therefore, 

the overall state-level population projections for Idaho were used as a surrogate for Elmore 

County (U.S. Census, 2005b). The population projections for 2015 were used directly, while the 

population projection for 2023 was derived from a linear interpolation of the 2020 and 2025 

population projections.

7.1.2.3 Industrial Output Projections

Industrial output projections for 2008, 2015, and 2023 (in terms of constant 2000 year 

dollars) were used to project emissions for a number of industrial area sources, including:

 Industrial surface coating (all subcategories)

 Degreasing (all subcategories)
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 Autobody refinishing

 Dry cleaning

 Construction

 Bakeries

 Industrial refrigeration/cold storage

Appropriate output projections were selected at the 4-digit NAICS level from data 

obtained from Economy.com (Economy.com, 2010). The growth factors were developed by 

ratioing the future year output for a particular NAICS code by the 2008 year output for the same 

NAICS code. 

7.1.2.4 Long-Term Agricultural Averages

Unlike many other area source categories, agricultural sources are thought to be 

somewhat cyclical in nature. This is due to limited arable land, cyclical commodity prices, and a 

number of other factors. As a result, long-term averages of county-level agricultural acreage 

were used to develop appropriate projection factors. Specifically, the total average acreage of 

significant Idaho field crops (i.e., alfalfa, barley, corn for grain, corn for silage, potatoes, 

sugarbeets, and wheat) from 1988 to 2007 was calculated. Data were obtained from the National 

Agricultural Statistics Service (NASS) (NASS, 2010). The projection factor is the ratio of this 

total average acreage divided by the 2008 acreage for these same crops. The resultant factors are 

1.1548 for Ada County, 1.0562 for Canyon County, and 0.8255 for Elmore County. 

7.1.2.5 Vehicle Miles Travelled (VMT)

As is typically done, future year vehicle miles travelled (VMT) projections were 

developed for estimating projected on-road motor vehicle emissions (see Section 3.1.3). These 

future year VMT projections were also used to develop growth factors for the source categories 

associated with gasoline marketing (i.e., Stage I, Stage II, breathing and emptying losses, and 

tank truck transport). As described in Section 7.1.1, the effects of Idaho Rule 592 were also 

incorporated with future year area source Stage I emissions.
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7-5

7.1.2.6 No Growth

For a few area source categories, no growth (i.e., a growth factor of 1.0000) was assigned. In 

these cases, either no growth was anticipated to occur in the future or no appropriate growth surrogate 

could be reasonably determined. These categories included the following:

 Traffic markings

 Asphalt application

 Irrigation ditch burning

 Beef cattle feedlots

7.1.2.7 Ammonia Sources

With the exception of ammonia from industrial refrigeration/cold storage, ammonia 

emissions were estimated using an ammonia model as described in the previous progress reports. 

The projected ammonia emissions were also modeled using the same model. Finally, a few area 

source categories emitting ammonia were assigned no growth (i.e., a growth factor of 1.0000). 

The following assumptions were made for the various modeled ammonia emission source 

categories:

 Population projection factors described above (Section 7.1.2.2) were used for 

domestic ammonia emissions;

 Long-term agricultural average projection factors described above (Section 7.1.2.4) 

were used for fertilizer emissions; and

 No growth was assumed for livestock (i.e., due to apparent cyclical production 

trends), wild animals, and soils 

7.1.2.8 Road Dust

Future year emissions for paved road dust were estimated using the same methodology as 

used for the 2008 base year (see Section 2.3) along with estimates of 2015 and 2023 VMT. 

Elmore County 2015 and 2023 VMT estimates were based on data developed for the on-road 

vehicle emission estimates as described above. Ada and Canyon County VMT estimates were 

taken from COMPASS transportation demand model (TDM) output for 2015 and 2025. 

COMPASS 2015 VMT estimates were used directly while 2023 VMT was estimated by linearly 
2008, 2015, 2023 Treasure Valley Emissions Inventories

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7-6

interpolating between the 2015 and 2025 data provided by COMPASS. No change in the perVMT paved road dust emission rates was estimated based on the assumption of unchanged future 

maintenance practices; however, VMT estimates increase in future years based on the

COMPASS TDM, resulting in increased paved road dust.

Future year emissions for unpaved road dust were estimated using the same methodology 

as the base year. In Ada County, a reduction in VMT of 1.95 percent per year was assumed per 

the Ada County conformity documentation (COMPASS, 2005). For all other areas, unpaved 

roadway VMT was assumed unchanged from 2008 based on conversations with local highway 

districts and municipalities, which indicated that even minimal projected conversion of unpaved 

to paved roads in future years would depend on funding levels. No change in unpaved road dust 

emission rates was estimated based on the assumption of unchanged future maintenance 

practices.

7.1.3 On-Road Motor Vehicles

Ada and Canyon counties on-road emissions in future years 2015, 2023, and 2050 were 

estimated by DEQ as an update to this emissions inventory (DEQ, 2012). COMPASS provided 

DEQ with TDM output from 2015 and 2023. DEQ ran MOVES2010a using the TDM output for 

2008, 2015, and 2023 for those calendar years. To generate the 2050 VMT and emissions data 

required for establishing motor vehicle emission budgets for conformity evaluations of the

COMPASS long-range transportation plan out to 2050, COMPASS provided DEQ with 

population and VMT forecasts for 2050. DEQ used these forecasts along with the 2015 TDM 

model runs to develop 2050 motor vehicle emission estimates for the species used in the 

speciated linear rollback modeling attainment demonstration (NOx, SO2, PM10, PM2.5). 

Anti-tampering and I/M programs were not in place for Canyon County in 2008, but 

were added for 2015 and 2023. The parameters are similar to the 2008 Ada County programs, 

except for the program change to biennial testing and testing of light-duty vehicles only. Tables 

7-1 and 7-2 show the future year updated parameters for anti-tampering and I/M, respectively. 

Alcohol blend E10 market share also changed from 68% in 2008 to 100% in future years. There 

were no other changes in inputs for the future year MOVES2010a modeling work.
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7-7

Table 7-1. 2015 and 2023 I/M Inputs by County: Anti-Tampering Program 

Parametersa

Anti-Tampering Program 

Parameters Ada County Canyon County Elmore County

Program Start Year 2010 2010 -

First Vehicle Model Year Applied Same as Ada 2008 Same as Ada 2008 -

Last Vehicle Model Year Applied Same as Ada 2008 Same as Ada 2008 -

Vehicle Types Applied Same as Ada 2008

LDGV, LDGT1, 

LDGT2 LDGT3, 

LDGT4

-

Inspection Frequency Biennial Biennial -

Compliance Rate Same as Ada 2008 Same as Ada 2008 -

Inspection Conducted Same as Ada 2008 Same as Ada 2008 -

a

See Appendix E of Northern Ada County PM10 Limited Maintenance Plan Ten-Year Update for 2008 I/M 

parameters.
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Final, August 31, 2010

7-8

Table 7-2. 2015, 2023, and 2030 MOBILE6 Inputs by County: I/M Program 

Parameters a

I/M 

Program 

Type I/M Program Parameters Ada County Canyon County

Elmore 

County

Exhaust 

Test Only 

Program –

Two speed 

test (idle 

and 2500 

RPM)

Start Year 2010 2010 -

End Year 2050 2050 -

Frequency Biennial Biennial -

First Vehicle Model Year 

Applied 1981 1981 -

Last Vehicle Model Year 

Applied 1995 1995 -

Vehicle Types Applied Same as Ada 2008

LDGV, LDGT1, 

LDGT2, LDGT3, 

LDGT4

-

Stringency (pre-1981 only) Same as Ada 2008 Same as Ada 2008 -

Compliance Rate Same as Ada 2008 Same as Ada 2008 -

Waiver Rate (expressed as 

a percentage of the vehicles 

that fail the I/M program)

Same as Ada 2008 Same as Ada 2008 -

Grace Period (the age at 

which vehicle first become 

subject to I/M testing)

4 5 -

Exhaust 

Test Only 

Program –

OBD I/M

Start Year 2010 2010 -

End Year 2050 2050 -

Frequency Biennial Biennial -

First Vehicle Model Year 

Applied Same as Ada 2008 Same as Ada 2008 -

Last Vehicle Model Year 

Applied 2050 2050 -

Vehicle Types Applied Same as Ada 2008

LDGV, LDGT1, 

LDGT2, LDGT3, 

LDGT4

-

Stringency (expected 

exhaust inspection failure 

rate for pre-1981 model 

year vehicles)

Same as Ada 2008 Same as Ada 2008 -

Compliance Rate Same as Ada 2008 Same as Ada 2008 -

Waiver Rate (expressed as 

a percentage of the vehicles 

that fail the I/M program)

Same as Ada 2008 Same as Ada 2008 -

Grace Period (the age at 

which vehicle first become 

subject to I/M testing)

4 5 -

a

See Appendix E of Northern Ada County PM10 Limited Maintenance Plan Ten-Year Update for 2008 I/M 

parameters.
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Elmore County motor vehicle emissions were not used in the Northern Ada County PM10

Limited Maintenance Plan Ten-Year Update demonstration and were not updated by DEQ in 

2010 using MOVES2010a. Thus, the original MOBILE6.2 emissions appear for Elmore County

in the remainder of this document as originally prepared by DEQ/Environ for 2008 and future 

years 2015 and 2023. For the future years, Elmore County emissions were estimated by 

multiplying emission factors specific to 2015 and 2023 with projected VMT increases from 2008 

to the future years. Elmore County emissions were not estimated for 2050. Emission factors for 

2015 and 2023 were generated by running MOBILE6.2 for those calendar years, which accounts 

for federally mandated gasoline sulfur reductions by calendar year and captures emission rate 

reductions due to increasingly stringent vehicle emission standards. The MOBILE6.2 national 

default registration distribution was used in all three years 2008, 2015 and 2023. Per DEQ, fuel 

parameters and vehicle inspection and maintenance programs do not change from 2008 in 

Elmore County. The MOBILE6.2 national default registration distribution was used in all three 

years 2008, 2015 and 2023. In addition, MOBILE6.2 accounts for federally mandated gasoline 

sulfur reductions by year and contains estimates of emission rate reductions due to increasingly 

stringent vehicle emission standards. 

2008 Elmore County VMT was projected to 2015 and 2023 using scaling factors based 

on the COMPASS TDM outputs for 2008, 2015 and 2025. The COMPASS TDM includes linklevel volumes and distances (thus VMT) by urban and rural roadway types that were readily 

classifiable into the three road types of the original 2008 Elmore County total VMT: “interstate,” 

“arterial,” and “other” for roadways that were not interstate or arterial. VMT estimates for 

2023 were calculated by linearly interpolating VMT between 2015 and 2025 datasets. The final 

projection factors for rural interstates, rural arterials and rural “other” roadways were developed 

by scaling 2015/2008 and 2023/2008. The projected VMT and future year emission factor sets 

were used to estimate future year emissions using the same approach as the base year modeling.

7.1.4 Nonroad Mobile Sources

The 2015 and 2023 nonroad mobile source projections were developed using a variety of 

sources of projections data. These are described below.
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7.1.4.1 Nonroad Equipment

The NONROAD model incorporates the effects of all “on the books” regulations. The 

model also contains growth factors for all equipment types, which have been derived by U.S. 

EPA from a proprietary database of equipment sales for several years. 

The NONROAD model was run for 2015 and 2023 analogous to what was done for 2008. 

Climate, local population, and temporal profiles used in the base year inputs were similarly used 

in the development of future year emissions. Fuel properties remained unchanged from base 

year estimates, except for the nonroad diesel sulfur level which was set to 15 ppm for 2015 and 

2023 as required by the federal Tier 4 nonroad diesel rule.

7.1.4.2 Aircraft

Aircraft emissions were projected to future years from the 2008 emissions, by airport and 

aircraft type, using LTO forecasts available from the FAA. Aircraft and APU emission factors 

were assumed to be unchanged over time. The International Civil Aviation Organization (ICAO) 

has promulgated NOx and CO emission standards for commercial aircraft (exempting general 

aviation and military engines from the rule) (ICAO, 1998); the majority of engines are already 

meeting this standard. U.S. EPA officially promulgated the ICAO standards for air carriers in a 

final rule in November 2005. 

The historic and projected LTO data by airport are available online from the Federal 

Aviation Administration (FAA) Terminal Area Forecast (TAF) database for all aircraft 

categories for which emissions were estimated (FAA, 2008). Projected LTO data for years 2015, 

2023, and historic data for 2008 were used to develop future year growth factors for all aircraft 

types by airport. Growth factors were calculated as the ratio of the sum of LTOs by airport and 

aircraft type in each future year to the sum of LTOs by airport and aircraft type in 2008. For 

airports that were included in the 2008 analysis, but are not in the FAA TAF database, growth 

factors were calculated as the ratio of the sum of LTOs by aircraft type in each future year over 

the entire Treasure Valley study region to the sum of LTOs by aircraft type in 2008 over the 

entire Treasure Valley study region. These future year growth factors were then applied to 2008 

emission estimates by airport and aircraft type to develop future year emission inventories. Base 

year LTOs and future year growth factors are shown in Table 7-3.
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Auxiliary power unit activity growth was assumed equivalent to commercial aircraft 

activity growth estimates. Airport GSE engines are subject to U.S. EPA nonroad engine 

standards. Fleet turnover to newer, engines meeting more stringent standards over time will 

decrease fleetwide airport GSE emission rates over time. Therefore, airport GSE projection 

factors must incorporate estimates of both activity growth and fleetwide emission rate decreases 

due to fleet turnover. Airport GSE fleetwide emission rate decreases were calculated based on 

the NONROAD model estimates of emission changes by fuel type in airport GSE emissions due 

to fleet turnover. To incorporate future year activity growth in airport GSE, commercial aircraft 

growth rates were applied. 

Table 7-3. Base Year Aircraft LTO Activity Data and Future Year Projection 

Factors

Airport

Commercial 

Aircraft Air Taxi Aircraft

General Aviation 

Aircraft Military Aircraft

2008 LTOs

Boise Air Terminal/Gowen 

Field 20,636 12,804 36,557 6,158

Caldwell Industrial 0 2,000 67,486 0

Nampa Municipal 0 0 54,813 50

Mountain Home Municipal 0 254 9,657 500

Other airports not in TAF 

databasea14 0 46,578 0

2015/2008 LTOs

Boise Air Terminal/Gowen 

Field 105% 67% 95% 104%

Caldwell Industrial - 100% 118% 100%

Nampa Municipal - - 123% 100%

Mountain Home Municipal - 100% 114% 100%

Other airports not in TAF 

databasea105% - 113% 104%

2023/2008 LTOs

Boise Air Terminal/Gowen 

Field 130% 88% 116% 104%

Caldwell Industrial - 100% 141% 100%

Nampa Municipal - - 157% 100%

Mountain Home Municipal - 100% 131% 100%

Other airports not in TAF 

databasea130% - 138% 104%

a Emissions projected for these airports based on estimated projections of total activity at the four airports for which data was 

available from FAA’s TAF database

7.1.4.3 Locomotives

Future year locomotive emission estimates were based on projections of activity growth 

and emission reductions. The activity growth was forecasted on the basis fuel consumption. The 

emission reduction forecasts account primarily for the fleet turnover and the lower emission 
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

7-12

standards, which were based on data available in EPA documents (U.S. EPA, 1997a; U.S. EPA, 

1997b; U.S. EPA, 2008).

A fuel consumption trend was estimated using a least squares regression analysis of 

annual fuel consumption obtained from the Association of American Railroads (AAR) for six 

years between 1999 and 2008 (AAR, 2009). Within the study domain the only Class 1 railroad 

operating was Union Pacific (UP). To accurately forecast activity, UP nationwide fuel 

consumption was analyzed (see Table 7-4). The UP data were also used to forecast the Idaho 

Northern Pacific Railroad and switching locomotive emissions; it is expected that the short-line 

and switching activity will have similar growth to the estimates for the mainline railroad (i.e., 

UP) that operates in the study domain. Based on the least squares linear regression analysis, a 

growth rate of 4,264,472 gallons of fuel per year was estimated.

Table 7-4. Union Pacific Historic Fuel Consumption

Year Fuel (gallons)

1999 1,252,111,733

2002 1,325,049,398

2005 1,362,933,944

2006 1,382,778,469

2007 1,338,300,581

2008 1,240,874,008

The growth rate was applied to the 2008 fuel consumption to generate 2015 and 2023 

estimates of 1,270,725,311 gallons and 1,304,841,085 gallons, respectively. The 2015 and 2023 

fuel consumption estimates represent a 2.40% and 5.16% increase from 2008, respectively.

The emission reduction estimates were based on the U.S. EPA line-haul and switching 

locomotive forecasted emission reductions relative to the locomotive fleets (U.S. EPA, 1997a; 

U.S. EPA, 1997b; U.S. EPA, 2008). Based on the U.S. EPA reports estimates of future year 

average emissions by the fleet type, representative emissions reductions from 2008 to 2015 and 

2008 to 2023 were extracted.

7.1.5 Biogenic Sources

Although it is expected that there will be year-to-year variability in biogenic emissions, it 

is not possible to predict this variability. Therefore, the 2008 biogenic emission estimates were 

also used for the 2015 and 2023 emission inventories.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

7-13

7.2 2015, 2023, and 2050 Inventory Summaries

Using all of the projection factors described in Section 7.1, the 2015 and 2023 projected 

emissions inventories were developed. In addition VMT projections to 2050 were used to project 

on-road and paved road dust emissions only to 2050 to support conformity evaluations of the 

COMPASS long-range transportation plans. County-level summaries of these inventories by 

source type are provided in this section. For ease of comparison, the 2008 county-level 

summaries are also presented. The annual summaries are presented in Tables 7-5 (2008), 7-6

(2015), 7-7 (2023), and 7-8 (2050). The ozone season summaries are provided in Tables 7-9 

(2008), 7-10 (2015), 7-11 (2023), and 7-12 (2050), while the PM season summaries are shown in 

Tables 7-13 (2008), 7-14 (2015), 7-15 (2023), and 7-16 (2050). Note, all values updated in these 

tables are shown in italic. The totals and subtotals are updated as well, shown in bold and italic.

The inventory summaries presented in Tables 7-5 through 7-16 reflect four categories of 

revisions that DEQ made to the emissions inventories in 2012 during preparation of the 

Northern Ada County PM10 Maintenance Plan Ten-Year Update:

1. On-road emissions of all pollutants were revised using the MOVES model;

2. Area source emissions were updated to include revisions to the paved road dust 

emissions included in the area source category;

3. Area source SO2 emissions included in the ozone season summary tables contained 

calculation errors in the ozone season distillate combustion worksheets prepared by 

ERG/Environ. These errors have been corrected.

4. DEQ projected 2015 on-road and paved road dust emissions to 2050 using 

COMPASS VMT projections and 2015 emission estimates.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

7-14

Table 7-5. 2008 County-Level Annual Emissions Summarized by Source Type

County Source 

Type

NOx

(tpy)

SO2 

(tpy)

VOC 

(tpy)

CO PM10 PM2.5 NH3

(tpy) (tpy) (tpy) (tpy)

Ada Point 355.6 65.70 268.1 198.5 169.1 142.6 46.0

Areaa920.7 26.90 12,962.8 7,715.1 19,555.0 3,552.0 3,995.3

On-Roada9,775.4 67.40 4,182.3 47,168.3 412.7 330.4 152.9

Nonroad 2,894.6 90.40 2,031.2 24,870.5 257.8 244.8 2.8

Biogenic 202.3 0.00 12,802.5 2,246.5 0.0 0.0 0.0

Total 14,148.6 250.40 32,246.9 82,198.9 20,394.6 4,269.8 4,197.0

Canyon Point 1,356.5 2,007.30 303.4 1,044.7 495.9 277.8 420.6

Areaa545.8 19.10 7,507.9 7,221.7 41,974.4 9,372.2 7,726.9

On-Roada5,847.8 35.00 3,202.1 36,404.4 258.2 212.1 81.8

Nonroad 1,878.3 47.90 754.1 8,251.3 174.7 164.0 1.8

Biogenic 283.9 0.00 8,902.4 1,650.2 0.0 0.0 0.0

Total 9,912.3 2,109.30 20,669.9 54,572.3 42,903.2 10,026.1 8,231.1

Elmore Point 360.3 2.50 26.6 105.3 135.9 58.7 0.0

Area 80.5 5.80 1,730.0 1,595.8 22,491.9 2,806.1 4,812.3

On-Roada576.6 3.10 529.8 5,460.8 14.7 9.3 30.7

Nonroad 914.8 16.10 368.6 1,873.0 56.8 53.6 0.7

Biogenic 465.2 0.00 30,982.3 6,425.0 0.0 0.0 0.0

Total 2,397.4 27.50 33,637.3 15,459.9 22,699.3 2,927.7 4,843.7

Total Point 2,072.4 2,075.40 598.1 1,348.5 800.9 479.0 466.6

Areaa1,547.1 51.80 22,200.7 16,532.7 84,021.3 15,730.3 16,534.5

On-Roada16,199.8 105.50 7,914.2 89,033.5 685.6 551.8 265.4

Nonroad 5,687.6 154.50 3,153.8 34,994.8 489.3 462.4 5.4

Biogenic 951.4 0.00 52,687.2 10,321.7 0.0 0.0 0.0

Total 26,458.3 2,387.20 86,554.0 152,231.2 85,997.1 17,223.5 17,271.9

a On-road emission estimates were revised in 2012 for the Northern Ada County PM10 Limited Maintenance Plan 

Ten-Year Update. Ada and Canyon counties on-road emissions values and paved road dust emissions (PM10 and 

PM2.5 in Area category) are from Appendix E of the Ten-Year Update, entitled “Development of the Base- and 

Future-Year Mobile Source Emission Inventories for the Treasure Valley, Idaho." Elmore County emissions were 

not revised. Table values revised in 2012 are shown in italic.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

7-15

Table 7-6. 2015 County-Level Annual Emissions Summarized by Source Type

County Source 

Type

NOx

(tpy)

SO2 

(tpy)

VOC 

(tpy)

CO PM10 PM2.5 NH3

(tpy) (tpy) (tpy) (tpy)

Ada Point 355.6 65.70 268.1 198.5 169.1 142.6 46.0

Areaa900.0 23.60 14,551.2 6,885.8 21,107.4 3,651.0 4,143.2

On-Roada5,856.6 33.40 2,939.7 39,263.4 283.0 193.0 126.4

Nonroad 1,979.8 28.20 1,480.7 21,192.5 196.9 185.8 3.2

Biogenic 202.3 0.00 12,802.5 2,246.5 0.0 0.0 0.0

Total 9,294.3 150.90 32,042.2 69,786.7 21,756.4 4,172.4 4,318.8

Canyon Point 1,365.9 2,007.30 303.9 1,054.8 500.3 282.1 420.6

Areaa509.7 16.70 7,690.9 6,310.3 8,494.0 2,025.6 7,907.8

On-Roada3,870.5 17.70 2,177.2 27,974.3 178.4 127.6 74.4

Nonroad 1,351.8 6.60 546.1 7,047.7 126.9 116.8 2.0

Biogenic 283.9 0.00 8,902.4 1,650.2 0.0 0.0 0.0

Total 7,381.8 2,048.30 19,620.5 44,037.3 9,299.6 2,552.1 8,404.8

Elmore Point 360.3 2.50 26.6 105.3 135.9 58.7 0.0

Area 74.0 5.30 1,781.0 1,412.5 22,923.7 2,876.3 4,636.3

On-Road 425.7 4.60 458.9 6,040.8 15.8 8.3 46.9

Nonroad 701.7 7.30 260.1 1,723.9 39.7 37.0 0.8

Biogenic 465.2 0.00 30,982.3 6,425.0 0.0 0.0 0.0

Total 2,026.9 19.70 33,508.9 15,707.5 23,115.1 2,980.3 4,684.0

Total Point 2,081.8 2,075.50 598.6 1,358.6 805.3 483.3 466.6

Areaa1,483.7 45.60 24,023.1 14,608.6 52,525.1 8,552.8 16,687.3

On-Roada10,152.8 55.70 5,575.8 7,3278.5 477.2 328.9 247.7

Nonroad 4,033.2 42.10 2,286.8 2,9964.1 363.6 339.6 6.0

Biogenic 951.4 0.00 52,687.2 10,321.7 0.0 0.0 0.0

Total 18,702.9 2,218.90 85,171.5 129,531.5 54,171.2 9,704.6 1,7407.6

a On-road emission estimates were revised in 2012 for the Northern Ada County PM10 Limited Maintenance Plan 

Ten-Year Update. Ada and Canyon counties on-road emissions values and paved road dust emissions (PM10 and 

PM2.5 in Area category) are from Appendix E of the Ten-Year Update, entitled “Development of the Base- and 

Future-Year Mobile Source Emission Inventories for the Treasure Valley, Idaho.” Elmore County emissions were 

not revised. Table values revised in 2012 are shown in italic.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

7-16

Table 7-7. 2023 County-Level Annual Emissions Summarized by Source Type

County Source 

Type

NOx SO2 

(tpy)

VOC 

(tpy)

CO PM10 PM2.5 NH3

(tpy) (tpy) (tpy) (tpy) (tpy)

Ada Point 391.2 72.30 294.9 218.4 186.0 156.8 50.6

Areaa951.9 23.80 18,062.8 7,146.3 25,267.1 4,072.7 4,207.4

On-Roada4,306.4 42.00 2,396.8 38,771.8 285.2 157.1 146.6

Nonroad 1,355.0 33.80 1,407.9 22,622.6 135.8 125.9 3.6

Biogenic 202.3 0.00 12,802.5 2,246.5 0.0 0.0 0.0

Total 7,206.8 171.90 34,964.9 71,005.6 25,874.1 4,512.5 4,408.2

Canyon Point 1,497.7 2,208.00 334.0 1,155.2 548.1 308.1 462.7

Areaa519.3 16.90 8,820.6 6,469.1 11,753.2 2,260.0 7,930.7

On-Roada3,273.6 25.10 1,935.0 27,684.6 191.5 112.3 95.0

Nonroad 860.7 6.90 504.2 7,402.5 83.6 73.5 2.3

Biogenic 283.9 0.00 8,902.4 1,650.2 0.0 0.0 0.0

Total 6,435.2 2,256.90 2,0496.2 4,4361.6 12,576.4 2,753.9 8,490.7

Elmore Point 396.3 2.70 29.3 115.8 149.5 64.5 0.0

Area 75.2 5.40 1,900.3 1,459.2 23,710.4 30,66.6 4,639.0

On-Road 340.6 6.50 422.6 7,416.2 19.8 9.4 66.0

Nonroad 457.5 7.60 191.7 1,714.4 25.0 22.5 0.8

Biogenic 465.2 0.00 30,982.3 6,425.0 0.0 0.0 0.0

Total 1,734.8 22.20 33,526.2 17,130.6 23,904.7 3,163.0 4,705.8

Total Point 2,285.3 2,283.00 6,58.2 1,489.4 883.6 529.5 513.2

Areaa1,546.4 46.10 28,783.7 15,074.6 60,730.6 9,399.3 16,777.1

On-Roada7,920.6 73.60 4,754.4 73,872.6 496.5 278.8 307.6

Nonroad 2,673.1 48.30 2,103.8 31,739.4 244.5 222.0 6.8

Biogenic 951.4 0.00 52,687.2 10,321.7 0.0 0.0 0.0

Total 15,376.8 2,451.00 88,987.3 132,497.7 62,355.2 10,429.6 17,604.7

a On-road emission estimates were revised in 2012 for the Northern Ada County PM10 Limited Maintenance Plan 

Ten-Year Update. Ada and Canyon counties on-road emissions values and paved road dust emissions (PM10 and 

PM2.5 in Area category) are from Appendix E of the Ten-Year Update, entitled” Development of the Base- and 

Future-Year Mobile Source Emission Inventories for the Treasure Valley, Idaho.” Elmore County emissions were 

not revised. Table values revised in 2012 are shown in italic.

Table 7-8. 2050 County-Level Annual On-Road Emissions for Ada County

County Source Type

NOx

(tpy)

SO2

(tpy)

VOC 

(tpy)

CO

(tpy)

PM10

(tpy)

PM2.5

(tpy)

NH3

(tpy)

Ada On-Road (MOVES)a 12,494 71.3 6,271 83,763 603.7 411.8 269.7

Ada Paved Road Dusta N/A N/A N/A N/A 19,550 N/A N/A

Ada Unpaved Road Dusta N/A N/A N/A N/A 1,795 N/A N/A

a For conformity demonstration in the Northern Ada County PM10 Limited Maintenance Plan Ten-Year Update. 

Projected by scaling 2015 emissions using 2050/2015 ratio VMT projected by COMPASS.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

7-17

Table 7-9. 2008 County-Level Ozone Season Emissions Summarized by Source 

Type

County Source 

Type

NOx

(tpd) 

SO2

VOC (tpd)

CO PM10 PM2.5 NH3

(tpd) (tpd) (tpd) (tpd) (tpd)

Ada Point 1.0 0.20 0.7 0.6 0.5 0.4 0.1

Areaa1.4 0.04 33.7 4.8 43.6 6.6 12.7

On-Roadb28.5 0.20 10.9 110.9 1.1 0.9 0.5

Nonroad 10.1 0.30 7.2 85.6 0.9 0.9 0.0

Biogenic 0.7 0.00 55.6 9.4 0.0 0.0 0.0

Total 41.7 0.74 108.1 211.3 46.1 8.7 13.3

Canyon Point 3.5 5.20 0.8 2.1 1.3 0.7 1.1

Areaa0.9 0.02 18.4 3.8 13.0 2.8 23.8

On-Roadb16.7 0.1 8.4 87.9 0.65 0.52 0.24

Nonroad 6.8 0.20 2.8 29.2 0.7 0.6 0.0

Biogenic 1.0 0.00 38.5 6.9 0.0 0.0 0.0

Total 28.9 5.52 68.9 129.9 15.6 4.6 25.1

Elmore Point 1.0 0.00 0.1 0.3 0.4 0.2 0.0

Areaa0.1 0.01 4.5 1.4 73.5 8.3 15.2

On-Road 1.5 0.00 1.5 11.0 0.0 0.0 0.1

Nonroad 3.0 0.10 1.7 8.1 0.2 0.2 0.0

Biogenic 1.7 0.00 132.4 26.7 0.0 0.0 0.0

Total 7.3 0.11 140.2 47.5 74.1 8.7 15.3

Total Point 5.5 5.40 1.6 3.0 2.2 1.3 1.2

Areaa2.4 0.06 56.6 10.1 130.0 17.6 51.8

On-Roadb46.7 0.3 20.8 209.8 1.7 1.4 0.8

Nonroad 19.8 0.60 11.7 122.8 1.8 1.7 0.0

Biogenic 3.4 0.00 226.5 43.0 0.0 0.0 0.0

Total 77.8 6.36 317.2 388.7 135.8 22.0 53.8

a Small errors in ozone season distillate combustion sulfur dioxide (SO2) emissions were corrected.

b On-road emission estimates were revised in 2012 for the Northern Ada County PM10 Limited Maintenance Plan 

Ten-Year Update. Ada and Canyon counties on-road emissions values and paved road dust emissions (PM10 and 

PM2.5 in Area category) are from Appendix E of the Ten-Year Update, entitled “Development of the Base- and 

Future-Year Mobile Source Emission Inventories for the Treasure Valley, Idaho.” Elmore County on-road and 

paved road emissions were not revised. Table values revised in 2012 are shown in italic.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

7-18

Table 7-10. 2015 County-Level Ozone Season Emissions Summarized by Source 

Type

County Source 

Type

NOx

(tpd) 

SO2

(tpd)

VOC 

(tpd) CO (tpd)

PM10 PM2.5 NH3

(tpd) (tpd) (tpd)

Ada Point 1.0 0.20 0.7 0.6 0.5 0.4 0.1

Areaa1.3 0.03 38.4 4.7 45.6 7.1 13.1

On-Roadb16.9 0.10 7.7 83.8 0.7 0.5 0.37

Nonroad 6.8 0.10 5.2 72.6 0.7 0.7 0

Biogenic 0.7 0.00 55.6 9.4 0.0 0.0 0

Total 26.7 0.43 107.6 171.1 47.5 8.6 13.57

Canyon Point 3.5 5.20 0.8 2.1 1.3 0.7 1.1

Areaa0.9 0.01 19.3 3.5 14.5 2.9 24.3

On-Roadb11.0 0.05 5.7 61.1 0.5 0.3 0.22

Nonroad 4.9 0.00 2.0 24.6 0.5 0.4 0

Biogenic 1.0 0.00 38.5 6.9 0.0 0.0 0

Total 21.3 5.26 66.3 98.2 16.8 4.3 25.62

Elmore Point 1.0 0.00 0.1 0.3 0.4 0.2 0

Areaa0.1 0.01 4.7 1.3 74.1 8.4 14.8

On-Road 1.1 0.00 1.3 11.8 0.1 0 0.1

Nonroad 2.3 0.00 1.1 7.4 0.1 0.1 0

Biogenic 1.7 0.00 132.4 26.7 0 0 0

Total 6.20 0.01 139.60 47.50 74.70 8.70 14.90

Total Point 5.5 5.40 1.6 3 2.2 1.3 1.2

Areaa2.3 0.1 62.4 9.5 134.2 18.4 52.2

On-Roadb29.0 0.15 14.7 156.7 1.3 0.8 0.7

Nonroad 14 0.10 8.3 104.6 1.3 1.2 0

Biogenic 3.4 0.00 226.5 43 0 0 0

Total 54 5.70 314 317 139 22 54

a Small errors in ozone season distillate combustion sulfur dioxide (SO2) emissions were corrected.

b On-road emission estimates were revised in 2012 for the Northern Ada County PM10 Limited Maintenance Plan 

Ten-Year Update. Ada and Canyon counties on-road emissions values and paved road dust emissions (PM10 and 

PM2.5 in Area category) are from Appendix E of theTen-Year Update, entitled “Development of the Base- and 

Future-Year Mobile Source Emission Inventories for the Treasure Valley, Idaho.” Elmore County on-road and 

paved road emissions were not revised. Table values revised in 2012 are shown in italic.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

7-19

Table 7-11. 2023 County-Level Ozone Season Emissions Summarized by Source 

Type

County Source 

Type

NOx

(tpd) 

SO2

(tpd) VOC (tpd) CO (tpd)

PM10 PM2.5 NH3

(tpd) (tpd) (tpd)

Ada Point 1.1 0.20 0.8 0.6 0.5 0.4 0.1

Areaa1.4 0.03 48.0 5.1 51.2 7.8 13.3

On-Roadb12.4 0.12 6.6 78.5 0.8 0.4 0.4

Nonroad 4.5 0.10 4.8 77.0 0.5 0.4 0.0

Biogenic 0.7 0.00 55.6 9.4 0.0 0.0 0.0

Total 20.1 0.45 115.8 170.6 52.9 9.0 13.8

Canyon Point 3.9 5.70 0.9 2.3 1.5 0.8 1.2

Areaa0.9 0.01 22.3 3.6 18.5 3.2 24.4

On-Roadb9.2 0.07 5.2 57.2 0.5 0.3 0.3

Nonroad 3.1 0.00 1.7 25.4 0.3 0.3 0.0

Biogenic 1.0 0.00 38.5 6.9 0.0 0.0 0.0

Total 18.1 5.78 68.6 95.4 20.8 4.5 25.9

Elmore Point 1.1 0.00 0.1 0.4 0.4 0.2 0.0

Areaa0.1 0.01 5.0 1.4 74.5 8.6 14.8

On-Road 0.9 0.00 1.2 14.5 0.1 0.0 0.2

Nonroad 1.5 0.00 0.8 7.2 0.1 0.1 0.0

Biogenic 1.7 0.00 132.4 26.7 0.0 0.0 0.0

Total 5.3 0.01 139.5 50.2 75.1 8.9 15.0

Total Point 6.0 5.90 1.8 3.3 2.4 1.4 1.3

Areaa2.4 0.1 75.3 10.1 144.2 19.6 52.4

On-Roadb22.5 0.19 13.0 150.2 1.3 0.6 0.9

Nonroad 9.1 0.10 7.3 109.6 0.9 0.8 0.0

Biogenic 3.4 0.00 226.5 43.0 0.0 0.0 0.0

Total 43.4 6.24 323.9 316.2 148.9 22.4 54.6

a Small errors in ozone season distillate combustion sulfur dioxide (SO2) emissions were corrected.

b On-road emission estimates were revised in 2012 for the Northern Ada County PM10 Limited Maintenance Plan 

Ten-Year Update. Ada and Canyon counties on-road emissions values and paved road dust emissions (PM10 and 

PM2.5 in Area category) are from Appendix E of theTen-Year Update, entitled “Development of the Base- and 

Future-Year Mobile Source Emission Inventories for the Treasure Valley, Idaho.” Elmore County on-road and 

paved road emissions were not revised. Table values revised in 2012 are shown in italic.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

7-20

Table 7-12. 2050 Ozone Season On-Road Emissions for Ada County

County Source Type

NOx

(tpd) 

SO2

(tpd)

VOC 

(tpd) CO (tpd)

PM10

(tpd)

PM2.5

(tpd)

NH3

(tpd)

Ada On-Road (MOVES)a36.1 0.21 16.4 178.9 1.6 1.02 0.79

Ada Paved Road Dusta N/A N/A N/A N/A 26.5 N/A N/A

Ada Unpaved Road Dusta N/A N/A N/A N/A 5.6 N/A N/A

a For conformity demonstration in the Northern Ada County PM10 Limited Maintenance Plan Ten-Year Update. 

Projected by scaling 2015 emissions using 2050/2015 ratio VMT projected by COMPASS.

Table 7-13. 2008 County-Level PM Season Emissions Summarized by Source 

Type

County Source 

Type

NOx

(tpd) 

SO2

(tpd)

VOC 

(tpd) CO (tpd)

PM10 PM2.5 NH3

(tpd) (tpd) (tpd)

Ada Point 1.0 0.20 0.7 0.5 0.5 0.4 0.1

Areaa4.4 0.10 39.1 49.7 67.6 15.1 8.5

On-Roada24.0 0.16 12.3 156.4 1.2 1.0 0.4

Nonroad 5.6 0.20 4.4 62.5 0.4 0.4 0.0

Biogenic 0.3 0.00 5.8 1.5 0.0 0.0 0.0

Total 35.3 0.66 62.3 270.6 69.7 16.9 9.0

Canyon Point 4.4 6.50 0.9 4.8 1.5 0.8 1.3

Areaa2.4 0.10 24.4 46.2 32.0 10.6 17.7

On-Roada14.8 0.09 9.3 117.1 0.8 0.7 0.2

Nonroad 2.9 0.10 1.4 18.9 0.2 0.2 0.0

Biogenic 0.4 0.00 4.2 1.1 0.0 0.0 0.0

Total 24.9 6.79 40.2 188.1 34.5 12.2 19.2

Elmore Point 1.0 0.00 0.1 0.2 0.4 0.2 0.0

Area 0.4 0.00 5.1 9.0 47.2 7.1 10.5

On-Road 1.6 0.00 1.1 17.2 0.0 0.0 0.1

Nonroad 1.9 0.00 0.5 3.1 0.1 0.1 0.0

Biogenic 0.7 0.00 17.3 4.7 0.0 0.0 0.0

Total 5.6 0.00 24.1 34.2 47.7 7.4 10.6

Total Point 6.4 6.70 1.6 5.5 2.3 1.4 1.5

Areaa7.1 0.30 68.6 104.9 146.8 32.7 36.7

On-Roada40.4 0.25 22.7 290.7 2.0 1.7 0.7

Nonroad 10.4 0.30 6.3 84.5 0.7 0.7 0.0

Biogenic 1.4 0.00 27.3 7.3 0.0 0.0 0.0

Total 65.7 7.55 126.5 492.9 151.7 36.5 38.9

a On-road emission estimates were revised in 2012 for the Northern Ada County PM10 Limited Maintenance Plan 

Ten-Year Update. Ada and Canyon counties on-road emissions values and paved road dust emissions (PM10 and 

PM2.5 in Area category) are from Appendix E of the Ten-Year Update, entitled “Development of the Base- and 

Future-Year Mobile Source Emission Inventories for the Treasure Valley, Idaho.” Elmore County emissions 

were not revised. Table values revised in 2012 are shown in italic.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

7-21

Table 7-14. 2015 County-Level PM Season Emissions Summarized by Source 

Type

County Source 

Type

NOx

(tpd) 

SO2

(tpd)

VOC 

(tpd) CO (tpd)

PM10 PM2.5 NH3

(tpd) (tpd) (tpd)

Ada Point 1.0 0.20 0.7 0.5 0.5 0.4 0.1

Areaa4.3 0.10 42.8 43.5 75.0 14.9 8.9

On-Roada14.7 0.08 8.7 144.3 0.8 0.6 0.3

Nonroad 3.8 0.10 3.3 54.5 0.3 0.3 0.0

Biogenic 0.3 0.00 5.8 1.5 0.0 0.0 0.0

Total 24.1 0.48 61.3 244.3 76.6 16.2 9.3

Canyon Point 4.4 6.50 0.9 4.8 1.5 0.8 1.3

Areaa2.3 0.10 24.2 40.0 36.2 9.7 18.2

On-Roada9.9 0.05 6.5 100.6 0.6 0.4 0.2

Nonroad 2.0 0.00 1.1 16.6 0.2 0.2 0.0

Biogenic 0.4 0.00 4.2 1.1 0.0 0.0 0.0

Total 19.0 6.65 36.9 163.1 38.5 11.2 19.7

Elmore Point 1.0 0.00 0.1 0.2 0.4 0.2 0.0

Area 0.3 0.00 5.2 7.9 48.5 7.2 10.0

On-Road 1.2 0.00 0.9 18.8 0.0 0.0 0.1

Nonroad 1.5 0.00 0.4 2.9 0.1 0.1 0.0

Biogenic 0.7 0.00 17.3 4.7 0.0 0.0 0.0

Total 4.7 0.00 23.9 34.5 49.0 7.5 10.1

Total Point 6.4 6.70 1.6 5.5 2.3 1.4 1.5

Areaa6.8 0.20 72.2 91.4 159.7 31.8 37.1

On-Road

a

25.8 0.13 16.0 263.7 1.4 1.0 0.6

Nonroad 7.3 0.10 4.8 74.0 0.6 0.5 0.0

Biogenic 1.4 0.00 27.3 7.3 0.0 0.0 0.0

Total 47.7 7.13 121.9 441.9 164.0 34.7 39.2

a On-road emission estimates were revised in 2012 for the Northern Ada County PM10 Limited Maintenance Plan 

Ten-Year Update. Ada and Canyon counties on-road emissions values and paved road dust emissions (PM10 and 

PM2.5 in Area category) are from Appendix E of theTen-Year Update, entitled “Development of the Base- and 

Future-Year Mobile Source Emission Inventories for the Treasure Valley, Idaho." Elmore County emissions 

were not revised. Table values revised in 2012 are shown in italic.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

7-22

Table 7-15. 2023 County-Level PM Season Emissions Summarized by Source 

Type

County Source 

Type

NOx

(tpd) 

SO2

(tpd)

VOC 

(tpd) CO (tpd)

PM10 PM2.5 NH3

(tpd) (tpd) (tpd)

Ada Point 1.1 0.20 0.8 0.5 0.5 0.4 0.1

Areaa4.5 0.10 52.6 44.8 94.7 16.6 9.1

On-Roada10.9 0.10 6.6 149.7 0.8 0.5 0.4

Nonroad 2.8 0.10 3.3 59.2 0.2 0.2 0.0

Biogenic 0.3 0.00 5.8 1.5 0.0 0.0 0.0

Total 19.6 0.50 69.1 255.7 96.3 17.7 9.6

Canyon Point 4.9 7.20 0.9 5.3 1.6 0.9 1.5

Areaa2.3 0.10 27.4 41.0 52.0 10.9 18.3

On-Roada8.5 0.06 5.5 105.3 0.6 0.4 0.2

Nonroad 1.3 0.00 1.1 18.0 0.1 0.1 0.0

Biogenic 0.4 0.00 4.2 1.1 0.0 0.0 0.0

Total 17.4 7.36 39.1 170.7 54.3 12.3 20.0

Elmore Point 1.1 0.00 0.1 0.3 0.4 0.2 0.0

Area 0.3 0.00 5.5 8.1 51.4 7.9 10.0

On-Road 0.9 0.00 0.9 23.0 0.1 0.0 0.2

Nonroad 1.0 0.00 0.3 3.1 0.0 0.0 0.0

Biogenic 0.7 0.00 17.3 4.7 0.0 0.0 0.0

Total 4.0 0.00 24.1 39.2 51.9 8.1 10.2

Total Point 7.0 7.40 1.8 6.0 2.5 1.5 1.6

Areaa7.2 0.30 85.5 93.9 198.1 35.4 37.4

On-Roada20.3 0.16 12.9 278.0 1.5 0.9 0.8

Nonroad 5.1 0.10 4.7 80.3 0.4 0.4 0.0

Biogenic 1.4 0.00 27.3 7.3 0.0 0.0 0.0

Total 41.0 7.96 132.2 465.5 202.5 38.2 39.8

a On-road emission estimates were revised in 2012 for the Northern Ada County PM10 Limited Maintenance Plan 

Ten-Year Update. Ada and Canyon counties on-road emissions values and paved road dust emissions (PM10 and 

PM2.5 in Area category) are from Appendix E of the Ten-Year Update, entitled “Development of the Base- and 

Future-Year Mobile Source Emission Inventories for the Treasure Valley, Idaho.” Elmore County emissions 

were not revised. Table values revised in 2012 are shown in italic.

Table 7-16. 2050 County-Level PM Season On-Road Emissions for Ada County 

County Source Type

NOx

(tpd) 

SO2

(tpd)

VOC 

(tpd)

CO 

(tpd)

PM10

(tpd)

PM2.5

(tpd)

NH3

(tpd)

Ada On-Road (MOVES)a31.3 0.18 18.5 307.8 1.8 1.3 0.66

Ada Paved Road Dusta N/A N/A N/A N/A 91.9 N/A N/A

Ada Unpaved Road Dusta N/A N/A N/A N/A 3.1 N/A N/A

a For conformity demonstration in the Northern Ada County PM10 Limited Maintenance Plan Ten-Year Upate.

Projected by scaling 2015 emissions using 2050/2015 ratio VMT projected by COMPASS.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

8-1

8.0 EMISSIONS INVENTORY DATA FORMATTING

As indicated in the discussion of contract scope in Section 1.2, all contract tasks have 

been completed. The emissions results presented in this final report have been generated using 

either calculation spreadsheets or computer models.

In order to facilitate their use in air quality models, the relevant emissions data were

exported to ASCII comma-delimited (.csv) files for re-formatting as input files to the Sparse 

Matrix Operator Kernel Emissions (SMOKE) model. Relevant parameters included pollutant 

emissions (i.e., annual, ozone season daily, and PM season daily), pollutant codes, SCCs, and 

county FIPS codes. For stationary point sources, information related to stack parameters and 

operating schedules were also needed. Where applicable, local temporal and speciation profiles 

were also provided in spreadsheet format. Computer scripts developed with Perl were then used 

to re-format emissions data for SMOKE. These script procedures were implemented by 

ENVIRON, who routinely performs these procedures and has developed a robust set of scripts, 

including limited internal data consistency checks, to accomplish this task.

Besides the final emissions inventory report, all inventory data (i.e., supporting data, 

spreadsheets, SMOKE-ready files, and all other ancillary information needed to duplicate the 

emissions inventory) have also been submitted to DEQ. The level of detail provided by the 

ERG/ENVIRON team ensures a transparent and defensible inventory that DEQ will be able to

understand and replicate. 
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

8-2
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

9-1

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9-2

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9-4

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9-5

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2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

9-6

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2008, 2015, 2023 Treasure Valley Emissions Inventories

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9-7

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2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

9-8

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9-9

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2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

9-10

USDA, 1997. Usual Planting and Harvesting Dates for U.S. Field Crops, Agricultural 

Handbook Number 628. U.S. Department of Agriculture.

USDA, 2009. 2007 Census of Agriculture, Idaho State and County Data (Volume 1 Geographic 

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EPA420-R-92-009. December.

U.S. EPA, 1997a. Locomotive Emission Standards, Regulatory Support Document (RSD), U.S. 

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U.S. EPA, 1997b. Emission Factors (EF) for Locomotives. EPA420-F-97-051. U.S. 

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U.S. EPA, 2002a. Review of Emission Factors and Methodologies to Estimate Ammonia 

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Agency, National Risk Management Research Laboratory, Research Triangle Park, NC. April.

U.S. EPA, 2002b. Emissions Modeling Clearinghouse Temporal Allocation Files. U.S. 

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emch/temporal/index.html

U.S. EPA, 2006. Documentation for the Final 2002 Nonpoint Sector (FEB 06 version) National 

Emission Inventory for Criteria and Hazardous Air Pollutants. U.S. Environmental Protection 

Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC. July.

U.S. EPA, 2007. Development Work for Improved Heavy-Duty Vehicle Modeling Capability 

Data Mining – FHWA Datasets. EPA/600/R-07/096. U.S. Environmental Protection Agency. 

July.

U.S. EPA, 2008. Regulatory Impact Analysis (RIA): Control of Emissions of Air Pollution from 

Locomotive Engines and Marine Compression Ignition Engines Less than 30 Liters Per 

Cylinder. EPA420-R-08-001. U.S. Environmental Protection Agency. March.

U.S. EPA, 2009a. Municipal Solid Waste Generation, Recycling, and Disposal in the United 

States – Detailed Tables and Figures for 2008. U.S. Environmental Protection Agency, Office 

of Resource Conservation and Recovery. November.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

9-11

U.S. EPA, 2009b. NONROAD2008 model. U.S. Environmental Protection Agency, Office of 

Transportation and Air Quality. Internet address: http://www.epa.gov/otaq/ 

nonrdmdl.htm#model

U.S. EPA, 2009c. Emission Factors for Locomotives. EPA-420-F-09-025. Office of 

Transportation and Air Quality. April.

U.S. EPA, 2010a. Compilation of Air Pollution Emission Factors – Volume 1: Stationary Point 

and Area Sources (AP-42), Fifth Edition (and subsequent updates). U.S. Environmental 

Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, North 

Carolina.

U.S. EPA, 2010b. U.S. EPA’s NEI2008. Internet address: http://www.epa.gov/ttn/chief/net/ 

2008inventory.html). 

U.S. EPA, 2010c. Motor Vehicle Emission Simulator 2010 (MOVES2010) model. U.S. 

Environmental Protection Agency, Office of Transportation and Air Quality. Internet address: 

http://www.epa.gov/otaq/models/moves/index.htm

USGS, 2010. National Hydrography Dataset. U.S. Geological Service. Internet address: 

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Waldinger, 2009. Personal communication between Mary Ann Walldinger (COMPASS) and 

Alison Pollack (ENVIRON). August.

Waldinger 2010. Personal communication between Mary Ann Walldinger (COMPASS) and 

John Grant (ENVIRON). January.

Walter, 2010. Personal communication between Craig Walter (City of Boise, Public Works 

Department) and Lan Ma (ENVIRON). January.

Walters, 2010. State-level gasoline statistics provided by Dar Walters, Idaho Tax Commission.

Webb, 2009. Personal communication between Steve Webb (City of Boise, Buildings 

Department) and Gopi Manne (ERG). November.

Winterfield, 2009. Personal communication between Steve Webb (Elmore County, Growth and 

Development Department) and Gopi Manne (ERG). November.

Winterfeld, 2010. Personal communication between Bob Winterfeld (Elmore County, Growth 

and Development Department) and Lan Ma (ENVIRON). January.

Woodward, 2010. Personal communication between Mike Woodward (City of Boise Parks and 

Recreation Department) and Lan Ma (ENVIRON). January.
2008, 2015, 2023 Treasure Valley Emissions Inventories

Final, August 31, 2010

9-12

WRCC. 2009. Idaho Climate Summaries: Period of Record General Climate Summaries. 

Western Regional Climate Center, Desert Research Institute. December. 

Wright, 2010. Personal communication between Raquel Wright (Federal Railroad 

Administration) and Tim Sturtz (ENVIRON). January.

York, 2010. Personal communication between Wendy York (Sorrento Lactalis) and Marty Wolf 

(ERG). May 5.

Zhang, 2009. Personal communication regarding MM5 modeling from Wei Zhang (Idaho 

Department of Environmental Quality). August 8.