MAG 2012 FIVE PERCENT PLAN FOR PM-10 FOR THE

MARICOPA COUNTY NONATTAINMENT AREA

APPENDICES

VOLUME ONE

MAY 2012
MAG 2012 FIVE PERCENT PLAN FOR PM-10 FOR THE

MARICOPA COUNTY NONATTAINMENT AREA

APPENDICES

MAY 2012
MAG 2012 FIVE PERCENT PLAN FOR PM-10 FOR THE

 MARICOPA COUNTY NONATTAINMENT AREA

APPENDICES

APPENDIX A

Exhibit 1: 2008 PM-10 Periodic Emissions Inventory for the Maricopa County,

Arizona, Nonattainment Area. Maricopa County Air Quality Department. 

Revised June 2011.

APPENDIX B

Exhibit 1: Technical Document in Support of the MAG 2012 Five Percent Plan for

PM-10 for the Maricopa County Nonattainment Area. Maricopa

Association of Governments.

Exhibit 2: Calculation of Benefits from PM-10 Certified Street Sweepers Purchased

with CMAQ Funds in 2001-2009.

APPENDIX C

Exhibit 1: Arizona Revised Statutes Listed in Table 4-1.

Exhibit 2: Maricopa County Resolution to Evaluate Measures in the MAG 2012 Five

Percent Plan for PM-10 for the Maricopa County Nonattainment Area.

Exhibit 3: Arizona Department of Environmental Quality Dust Action General Permit.

Exhibit 4: Arizona Department of Environmental Quality Commitment to Revise the

MAG 2012 Five Percent Plan for PM-10 for the Maricopa County

Nonattainment Area if Necessary for the Emerging and Voluntary

Measure.

APPENDIX D

Exhibit 1: Agricultural Best Management Practices Program.

APPENDIX E

Exhibit 1: Public Hearing Process Documentation.

Exhibit 2: Certification of Adoption.
APPENDIX A
APPENDIX A

EXHIBIT 1:

2008 PM-10 Periodic Emissions Inventory for the

Maricopa County, Arizona, Nonattainment Area. 

Maricopa County Air Quality Department. 

Revised June 2011
2008 PM10 Periodic Emissions Inventory

for the

Maricopa County, Arizona, Nonattainment Area

REVISED

June 2011

2008 Maricopa Co. PM10 Emission Inventory i June 2011 

2008 PM10 Periodic Emission Inventory

for the Maricopa County, Arizona Nonattainment Area

June 2011

REVISED 

Table of Contents

1. Introduction....................................................................................................................................1

1.1 Overview.......................................................................................................................................1

1.2 Agencies responsible for the emissions inventory........................................................................1

1.3 Temporal scope.............................................................................................................................2

1.4 Geographic scope..........................................................................................................................2

1.5 Overview of local demographic and land use data .......................................................................3

1.5.1 Demographic profile ..........................................................................................................3

1.5.2 Land use data .....................................................................................................................3

1.6 Emissions overview by source category.......................................................................................4

1.6.1 Point sources......................................................................................................................4

1.6.2 Area sources.......................................................................................................................4

1.6.3 Nonroad mobile sources ....................................................................................................5

1.6.4 Onroad mobile sources ......................................................................................................5

1.6.5 Biogenic sources................................................................................................................6

1.6.6 Summary of all source categories......................................................................................6

1.7 Public review process .................................................................................................................10

2. Point Sources................................................................................................................................11

2.1 Introduction and scope................................................................................................................11

2.2 Identification of point sources ....................................................................................................11

2.3 Procedures for estimating emissions from point sources............................................................12

2.3.1 Calculation of PM2.5 emissions........................................................................................13

2.3.2 Application of rule effectiveness.....................................................................................13

2.4 Detailed overview of point source emissions.............................................................................13

2.5 Emission reduction credits..........................................................................................................14

2.6 Summary of point source emissions...........................................................................................15

2.7 Quality assurance / quality control procedures...........................................................................15

2.7.1 Emission survey preparation and data collection.............................................................15

2.7.2 Submission processing.....................................................................................................16

2.7.3 Analysis of annual point source emissions data for this inventory..................................17

2.8 References...................................................................................................................................17

3. Area Sources.................................................................................................................................19

3.1 Scope and methodology..............................................................................................................19

3.2 Fuel combustion..........................................................................................................................20

3.2.1 Industrial natural gas........................................................................................................21

3.2.2 Industrial fuel oil..............................................................................................................22
2008 Maricopa Co. PM10 Emission Inventory ii June 2011 

3.2.3 Commercial/institutional natural gas...............................................................................24

3.2.4 Commercial/institutional fuel oil .....................................................................................25

3.2.5 Residential natural gas.....................................................................................................27

3.2.6 Residential wood combustion ..........................................................................................28

3.2.7 Residential fuel oil ...........................................................................................................29

3.2.8 Summary of all area-source fuel combustion ..................................................................30

3.3 Industrial processes.....................................................................................................................30

3.3.1 Chemical manufacturing..................................................................................................30

3.3.2 Food and kindred products...............................................................................................31

3.3.2.1 Commercial cooking ..........................................................................................31

3.3.2.2 Grain handling/processing..................................................................................34

3.3.2.3 Ammonia cold storage .......................................................................................35

3.3.3 Secondary metal production ............................................................................................35

3.3.4 Non-metallic mineral processes.......................................................................................36

3.3.5 Mining and quarrying ......................................................................................................36

3.3.6 Wood product manufacturing ..........................................................................................37

3.3.7 Rubber/plastics manufacturing ........................................................................................38

3.3.8 Fabricated metal products manufacturing........................................................................39

3.3.9 Construction.....................................................................................................................41

3.3.10 Electrical equipment manufacturing ................................................................................44

3.3.11 State-permitted portable sources......................................................................................45

3.3.12 Paved/unpaved road travel on industrial sites..................................................................46

3.3.13 Industrial processes not elsewhere classified (NEC).......................................................46

3.3.14 Summary of all area-source industrial processes.............................................................47

3.4 Waste treatment and disposal .....................................................................................................48

3.4.1 On-site incineration..........................................................................................................48

3.4.2 Open burning ...................................................................................................................49

3.4.3 Landfills...........................................................................................................................52

3.4.4 Publicly owned treatment works (POTWs).....................................................................52

3.4.5 Other industrial waste disposal ........................................................................................52

3.4.6 Summary of all area-source waste disposal .....................................................................53

3.5 Miscellaneous area sources.........................................................................................................53

3.5.1 Other combustion.............................................................................................................53

3.5.1.1 Wildfires.............................................................................................................53

3.5.1.2 Prescribed fires...................................................................................................56

3.5.1.3 Structure fires.....................................................................................................57

3.5.1.4 Vehicle fires .......................................................................................................59

3.5.1.5 Engine testing.....................................................................................................60

3.5.2 Agricultural activities.......................................................................................................60

3.5.2.1 Tilling.................................................................................................................60

3.5.2.2 Harvesting ..........................................................................................................64

3.5.2.3 Travel on unpaved agricultural roads.................................................................67

3.5.2.4 Cotton ginning....................................................................................................69

3.5.2.5 Fertilizer application ............................................................................................69

3.5.3 Livestock..........................................................................................................................70

3.5.4 Health services: crematories............................................................................................72

3.5.5 Accidental releases...........................................................................................................72

3.5.6 Humans............................................................................................................................72

3.5.7 Leaf blower fugitive dust .................................................................................................73
2008 Maricopa Co. PM10 Emission Inventory iii June 2011 

3.5.8 Offroad recreation vehicles fugitive dust.........................................................................74

3.5.9 Unpaved parking lots fugitive dust..................................................................................76

3.5.10 Windblown dust...............................................................................................................79

3.5.11 Summary of all miscellaneous area sources ....................................................................80

3.6 Summary of all area sources.......................................................................................................81

3.7 Quality assurance/quality control procedures.............................................................................83

3.8 References...................................................................................................................................85

4. Nonroad Mobile Sources.............................................................................................................89

4.1 Introduction.................................................................................................................................89

4.2 Agricultural equipment...............................................................................................................91

4.3 Airport ground support equipment and auxiliary power units....................................................92

4.4 Commercial equipment...............................................................................................................93

4.5 Construction and mining equipment...........................................................................................94

4.6 Industrial equipment ...................................................................................................................94

4.7 Lawn and garden equipment.......................................................................................................95

4.8 Pleasure craft...............................................................................................................................95

4.9 Railway maintenance equipment................................................................................................96

4.10 Recreational equipment ..............................................................................................................96

4.11 Aircraft........................................................................................................................................97

4.12 Locomotives..............................................................................................................................101

4.13 Summary of all nonroad mobile source emissions...................................................................103

4.14 Quality assurance procedures ...................................................................................................103

4.15 References.................................................................................................................................103

5. Onroad Mobile Sources.............................................................................................................105

5.1 Introduction...............................................................................................................................105

5.2 Exhaust, tire wear, and brake wear emissions..........................................................................106

5.2.1 MOVES2010a model.....................................................................................................106

5.2.2 MOVES2010a local input data ......................................................................................106

5.2.2.1 Fuel data ...........................................................................................................106

5.2.2.2 I/M programs....................................................................................................107

5.2.2.3 Meteorological data..........................................................................................107

5.2.2.4 Vehicle population ...........................................................................................107

5.2.2.5 Source type age distribution.............................................................................108

5.2.2.6 Annual VMT ....................................................................................................108

5.2.2.7 Road type distribution ......................................................................................108

5.2.2.8 VMT fraction....................................................................................................109

5.2.2.9 Average speed distribution...............................................................................109

5.2.2.10 Ramp fraction...................................................................................................109

5.2.3 MOVES2010a outputs...................................................................................................109

5.2.4 MOVES2010a emission estimates.................................................................................110

5.3 Fugitive dust emissions.............................................................................................................117

5.3.1 Paved road fugitive dust emissions................................................................................117

5.3.2 Unpaved road fugitive dust emissions...........................................................................119

5.4 Summary of particulate emissions from onroad mobile sources..............................................122

5.5 Quality assurance process.........................................................................................................122

5.5.1 VMT estimates...............................................................................................................122
2008 Maricopa Co. PM10 Emission Inventory iv June 2011 

5.5.2 Emission estimates.........................................................................................................122

5.5.3 Draft particulate matter emissions inventory.................................................................122

5.6 References.................................................................................................................................123

6. Biogenic Sources.........................................................................................................................125

6.1 Introduction...............................................................................................................................125

6.2 Modeling domain......................................................................................................................125

6.3 Input data ..................................................................................................................................125

6.3.1 Land cover data..............................................................................................................126

6.3.2 Weather data ..................................................................................................................127

6.4 Emissions estimation ................................................................................................................128

6.5 Summary of biogenic source emissions....................................................................................130

6.6 References.................................................................................................................................130

List of Tables

Table 1.2–1. Chapter authors and QA/QC contacts for this report.....................................................1

Table 1.5–1. Demographic profile of Maricopa County and the PM10 nonattainment area. ..............3

Table 1.5–2. Land use categories used to apportion emissions. .........................................................4

Table 1.6–1. Summary of annual and typical daily emissions from point sources in 

Maricopa County. ..........................................................................................................4

Table 1.6–2. Summary of annual and typical daily emissions from area sources in Maricopa 

County............................................................................................................................4

Table 1.6–3. Summary of annual and typical daily emissions from area sources in the PM10

NAA...............................................................................................................................5

Table 1.6–4. Annual and typical daily emissions from nonroad mobile sources in Maricopa

County............................................................................................................................5

Table 1.6–5. Annual and typical daily emissions from all nonroad mobile sources in the 

PM10 NAA. ....................................................................................................................5

Table 1.6–6. Annual and average daily emissions from all onroad mobile sources in 

Maricopa County. ..........................................................................................................6

Table 1.6–7. Annual and typical daily emissions from all onroad mobile sources in the 

PM10 NAA. ....................................................................................................................6

Table 1.6–8. Annual and season-day NOx emissions from biogenic sources.....................................6

Table 1.6–9. Annual and typical daily emissions from all sources in Maricopa County. ..................7

Table 1.6–10. Annual and typical daily emissions from all sources in the PM10

nonattainment area.........................................................................................................9

Table 2.2–1. Name and location of all point sources in Maricopa County.......................................12

Table 2.4–1. Annual and typical daily point source emissions, by facility. .....................................14

Table 2.5–1. Emission reduction credits...........................................................................................14

Table 2.6–1. Annual and typical daily point source emissions (including emission reduction 

credits)..........................................................................................................................15

Table 3.1–1. List of area-source categories included in this PM10 inventory...................................19

Table 3.2–1. Maricopa County natural gas sales data by supply company and end-user 

category........................................................................................................................20

Table 3.2–2. Natural gas usage, emission factors, and annual emissions from area-source 

industrial natural gas combustion, by combustion type...............................................21
2008 Maricopa Co. PM10 Emission Inventory v June 2011 

Table 3.2–3. Annual and typical daily emissions from area-source industrial natural gas 

combustion...................................................................................................................22

Table 3.2–4. Emission factors and annual emissions from area-source industrial fuel oil 

combustion, by combustion type. ................................................................................23

Table 3.2–5. Annual and typical daily emissions from area-source industrial fuel oil 

combustion...................................................................................................................24

Table 3.2–6. Emission factors and annual emissions from area-source 

commercial/institutional natural gas combustion, by combustion type.......................24

Table 3.2–7. Annual and typical daily emissions from area-source commercial/institutional 

natural gas combustion. ...............................................................................................25

Table 3.2–8. Emission factors and annual emissions from area-source 

commercial/institutional fuel oil combustion, by combustion type.............................26

Table 3.2–9. Annual and typical daily emissions from area-source commercial/institutional 

fuel oil combustion. .....................................................................................................27

Table 3.2–10. Residential natural gas combustion emission factors. .................................................27

Table 3.2–11. Annual and typical daily emissions from residential natural gas combustion.............27

Table 3.2–12. Annual wood usage, emission factors, and annual emissions from residential 

wood combustion.........................................................................................................28

Table 3.2–13. Annual and typical daily emissions from residential wood combustion. ....................29

Table 3.2–14. Annual and typical daily emissions from residential fuel oil combustion...................29

Table 3.2–15. Annual and typical daily emissions from area-source fuel combustion in 

Maricopa County. ........................................................................................................30

Table 3.2–16. Annual and typical daily emissions from all area-source fuel combustion for 

the PM10 NAA..............................................................................................................30

Table 3.3–1. NAICS codes and descriptions for chemical manufacturing.......................................30

Table 3.3–2. Annual and typical daily emissions from area-source chemical manufacturing. ........31

Table 3.3–3. Number of Maricopa County restaurants, by restaurant type......................................32

Table 3.3–4. Percentages of restaurants with each type of cooking equipment. ..............................32

Table 3.3–5. Average number of equipment pieces per restaurant, by type.....................................32

Table 3.3–6. Total pieces of cooking equipment, by restaurant type. ..............................................33

Table 3.3–7. Meat cooked weekly per restaurant (in pounds), by equipment type. .........................33

Table 3.3–8. Total meat cooked weekly (in tons), by equipment type. ............................................33

Table 3.3–9. PM10 and PM2.5 emission factors for commercial cooking equipment, by 

device type. ..................................................................................................................34

Table 3.3–10. Annual and daily emissions from commercial cooking equipment in Maricopa 

County..........................................................................................................................34

Table 3.3–11. Annual and daily PM emissions from commercial cooking equipment in the 

PM10 NAA. ..................................................................................................................34

Table 3.3–12. Annual and typical daily emissions from area-source grain handling and 

processing. ...................................................................................................................34

Table 3.3–13. Annual and typical daily ammonia emissions from ammonia cold storage. ...............35

Table 3.3–14. Annual and typical daily emissions from secondary metal production. ......................36

Table 3.3–15. Annual and typical daily emissions from area-source non-metallic mineral 

products........................................................................................................................36

Table 3.3–16. Annual and typical daily emissions from area-source mining and quarrying 

operations.....................................................................................................................37

Table 3.3–17. County-level employment estimates for wood product manufacturing, by 

NAICS code.................................................................................................................37

Table 3.3–18. Annual and typical daily emissions from area-source wood product 
2008 Maricopa Co. PM10 Emission Inventory vi June 2011 

manufacturing. .............................................................................................................38

Table 3.3–19. County-level employment estimates for rubber and plastic manufacturing, by 

NAICS code.................................................................................................................39

Table 3.3–20. Annual and typical daily emissions from area-source rubber/plastic product 

manufacturing. .............................................................................................................39

Table 3.3–21. Annual and typical daily emissions from area-source fabricated metal product 

manufacturing. .............................................................................................................40

Table 3.3–22. Maricopa County dust control permits issued in 2008, by type. .................................41

Table 3.3–23. Average project duration and emission factor, by project type. ..................................42

Table 3.3–24. Annual emissions from construction in Maricopa County, by project type. ...............43

Table 3.3–25. Annual emissions from construction within the Maricopa County portion of 

the PM10 nonattainment area, by project type..............................................................43

Table 3.3–26. Annual emissions from construction in the Pinal County portion of the PM10

NAA, by project type...................................................................................................44

Table 3.3–27. Annual and typical daily emissions from construction in Maricopa County and 

the PM10 NAA..............................................................................................................44

Table 3.3–28. Annual and typical daily emissions from area-source electric equipment 

manufacturing. .............................................................................................................44

Table 3.3–29. Annual and typical daily emissions from ADEQ-permitted portable sources.............46

Table 3.3–30. Annual and typical daily emissions from paved and unpaved road travel at 

industrial facilities........................................................................................................46

Table 3.3–31. Annual and typical daily emissions from other industrial processes not 

elsewhere classified. ....................................................................................................46

Table 3.3–32. Annual and daily emissions from all area-source industrial processes in 

Maricopa County. ........................................................................................................47

Table 3.3–33. Annual and typical daily emissions from all area-source industrial processes in 

the PM10 NAA..............................................................................................................48

Table 3.4–1. Annual and typical daily emissions from on-site incineration.....................................49

Table 3.4–2. Summary of 2008 Maricopa County burn permit activity...........................................49

Table 3.4–3. Emission and fuel loading factors for open burning....................................................50

Table 3.4–4. Annual and typical daily emissions from open burning in Maricopa County. ............51

Table 3.4–5. Surrogate land use classes and NAA:County activity ratios for burn permit 

categories. ....................................................................................................................51

Table 3.4–6. Annual and typical daily emissions from open burning in the PM10 NAA. ................51

Table 3.4–7. Annual and typical daily emissions from landfills. .....................................................52

Table 3.4–8. NH3 emissions from publicly-owned treatment works (POTWs). ..............................52

Table 3.4–9. Annual and typical daily emissions from other industrial waste disposal...................52

Table 3.4–10. Annual and typical daily emissions from all area-source waste disposal for 

Maricopa County. ........................................................................................................53

Table 3.4–11. Annual and typical daily emissions from all area-source waste disposal for the 

PM10 NAA. ..................................................................................................................53

Table 3.5–1. Sources and input data used to estimate emissions from fires in Maricopa 

County..........................................................................................................................54

Table 3.5–2. NFDRS fuel model categories and fuel loading factors for 2008 Maricopa 

County wildfires...........................................................................................................55

Table 3.5–3. Summary of data on fire occurrence, total acres burned, and total material 

burned in 2008. ............................................................................................................55

Table 3.5–4. Summary of emission factors for prescribed fire.........................................................55

Table 3.5–5. Annual emissions from wildfires in Maricopa County and the PM10 NAA................56
2008 Maricopa Co. PM10 Emission Inventory vii June 2011 

Table 3.5–6. Average daily emissions from wildfires in Maricopa County and the PM10

NAA.............................................................................................................................56

Table 3.5–7. Summary of data used to estimate emissions from prescribed fires............................56

Table 3.5–8. Emission factors for prescribed fires. ..........................................................................56

Table 3.5–9. Annual and typical daily emission from prescribed fire in Maricopa County 

and the PM10 NAA. ......................................................................................................57

Table 3.5–10. Material burned, emission and fuel loading factors for structure fires. .......................58

Table 3.5–11. Annual and typical daily emissions from structure fires in Maricopa County 

and the NAA. ...............................................................................................................58

Table 3.5–12. Estimated material burned, fuel loading factors, and emission factors for 

vehicle fires..................................................................................................................59

Table 3.5–13. Annual and typical daily emissions from vehicle fires................................................59

Table 3.5–14. Annual and typical daily emissions from engine testing. ............................................60

Table 3.5–15. 2008 crop acreage, activity, and annual uncontrolled PM10 emissions in 

Maricopa County. ........................................................................................................61

Table 3.5–16. Annual emissions from agricultural tillage in Maricopa County and Area A 

(tons/yr)........................................................................................................................63

Table 3.5–17. Annual emissions from agricultural tillage in the PM10 NAA (tons/yr)......................63

Table 3.5–18. Controlled typical daily emissions from tillage (in lbs/day)........................................64

Table 3.5–19. Maricopa County harvested acres and emission factors..............................................64

Table 3.5–20. Annual emissions from harvesting in Maricopa County and Area A (in 

tons/yr). ........................................................................................................................66

Table 3.5–21. Annual emissions from harvesting in the PM10 NAA (tons/yr)...................................66

Table 3.5–22. Typical daily emissions from harvesting, by crop (in lbs/day)....................................67

Table 3.5–23. Annual and typical daily emissions from travel on unpaved agricultural roads..........69

Table 3.5–24. Annual and typical daily emissions from area-source cotton ginning.........................69

Table 3.5–25. Annnual and typical daily NH3 emissions from fertilizer application.........................70

Table 3.5–26. Maricopa County cattle populations and PM emission factors. ..................................71

Table 3.5–27. Maricopa County cattle inventory for 2002 and 2008.................................................71

Table 3.5–28. Annual and typical daily NH3 emissions from livestock in Maricopa County............71

Table 3.5–29. Annual and typical daily emissions from livestock. ....................................................72

Table 3.5–30. Annual and typical daily emissions from crematories.................................................72

Table 3.5–31. Annual and typical daily emissions from accidental releases......................................72

Table 3.5–32. Annual and typical daily NH3 emissions from human activity....................................73

Table 3.5–33. Leaf blower equipment populations, activity levels and emission factors for 

Maricopa County. ........................................................................................................73

Table 3.5–34. Annual and typical daily emissions from leaf blower fugitive dust. ...........................74

Table 3.5–35. 2008 offroad recreational vehicle travel on unpaved surfaces in Maricopa 

County..........................................................................................................................75

Table 3.5–36. 2008 uncontrolled emissions from offroad recreational vehicles. ...............................75

Table 3.5–37. Benefits of measures that reduce offroad recreational vehicle emissions. ..................76

Table 3.5–38. 2008 controlled emissions from offroad recreational vehicles. ...................................76

Table 3.5–39. 2008 uncontrolled emissions from vehicles traveling on unpaved parking lots..........78

Table 3.5–40. Benefits of measure that reduces unpaved parking lot emissions................................78

Table 3.5–41. Annual and typical daily controlled emissions from unpaved parking lots.................78

Table 3.5–42. Annual and typical daily emissions from fugitive windblown dust for 

Maricopa County. ........................................................................................................79

Table 3.5–43. Annual and typical daily emissions from fugitive windblown dust for the 

PM10 NAA. ..................................................................................................................79
2008 Maricopa Co. PM10 Emission Inventory viii June 2011 

Table 3.5–44. Annual and typical daily emissions from all miscellaneous area sources for 

Maricopa County. ........................................................................................................80

Table 3.5–45. Annual and typical daily emissions from all miscellaneous area sources for the 

PM10 NAA. ..................................................................................................................80

Table 3.6–1. Summary of annual and typical daily emissions from all area sources in 

Maricopa County. ........................................................................................................81

Table 3.6–2. Summary of annual and typical daily emissions from all area sources in the 

PM10 NAA. ..................................................................................................................82

Table 4.1–1. NONROAD model county temperature- and fuel-related inputs. ...............................90

Table 4.1–2. Default weekday and weekend day activity allocation fractions.................................91

Table 4.2–1. Annual emissions (tons/yr) from agricultural equipment in Maricopa County...........91

Table 4.2–2. Annual emissions (tons/yr) from agricultural equipment in the PM10 NAA...............91

Table 4.2–3. Typical daily emissions (lbs/day) from agricultural equipment in Maricopa 

County..........................................................................................................................91

Table 4.2–4. Typical daily emissions (lbs/day) from agricultural equipment in the PM10

nonattainment area.......................................................................................................92

Table 4.3–1. Annual emissions (tons/yr) from all airport ground support equipment (GSE) 

and auxiliary power units (APUs)................................................................................93

Table 4.3–2. Typical daily emissions (lb) from airport GSE and APU usage..................................93

Table 4.4–1. Annual emissions (tons/yr) from commercial equipment usage..................................93

Table 4.4–2. Typical daily emissions (lbs/day) from commercial equipment usage........................93

Table 4.5–1. Annual emissions (tons/yr) from construction and mining equipment usage..............94

Table 4.5–2. Typical daily emissions (lbs/day) from construction and mining equipment 

usage. ...........................................................................................................................94

Table 4.6–1. Annual emissions (tons/yr) from industrial equipment usage. ....................................94

Table 4.6–2. Typical daily emissions (lbs/day) from industrial equipment usage. ..........................94

Table 4.7–1. Annual emissions (tons/yr) from lawn and garden equipment. ...................................95

Table 4.7–2. Typical daily emissions (lbs/day) from lawn and garden equipment. .........................95

Table 4.8–1. Annual emissions (tons/yr) from pleasure craft equipment.........................................95

Table 4.8–2. Typical daily emissions (lbs/day) from pleasure craft equipment. ..............................95

Table 4.9–1. Annual emissions (tons/yr) from railway maintenance equipment. ............................96

Table 4.9–2. Typical daily emissions (lbs/day) from railway maintenance equipment. ..................96

Table 4.10–1. Annual emissions (tons/yr) from recreational equipment............................................96

Table 4.10–2. Typical daily emissions (lbs/day) from recreational equipment..................................96

Table 4.11–1. Annual airport operations (by aircraft category), and related data sources. ................98

Table 4.11–2. Example showing how most common aircraft-specific activity was grown for 

EDMS modeling. .........................................................................................................99

Table 4.11–3. EPA’s default PM10 emission factors for aircraft, by activity type. ............................99

Table 4.11–4. Annual and average daily emissions, by airport and aircraft type, from airports 

within the PM10 NAA. ...............................................................................................100

Table 4.11–5. Annual and average daily emissions, by aircraft type, from airports outside the 

PM10 NAA. ................................................................................................................101

Table 4.12–1. Emission factors for locomotives...............................................................................101

Table 4.12–2. Total diesel use and annual emissions from locomotives in Maricopa County.........101

Table 4.12–3. Annual emissions (in tons/yr) from locomotives in the PM10 NAA..........................102

Table 4.12–4. Typical daily emissions (in lbs/day) from locomotives in Maricopa County............102

Table 4.12–5. Typical daily emissions (in lbs/day) from locomotives in the PM10

nonattainment area.....................................................................................................102

Table 4.13–1. Annual and typical daily emissions from nonroad mobile sources in Maricopa 
2008 Maricopa Co. PM10 Emission Inventory ix June 2011 

County........................................................................................................................103

Table 4.13–2. Annual and typical daily emissions from nonroad mobile sources in the PM10

NAA...........................................................................................................................103

Table 5.2–1. 2008 daily VMT by facility type (annual average daily traffic)................................108

Table 5.2–2. Annual and average daily onroad mobile source emissions by facility type and 

vehicle class in the PM10 NAA. .................................................................................110

Table 5.2–3. Annual and average daily onroad mobile source emissions by facility type and 

vehicle class in Maricopa County..............................................................................114

Table 5.3–1. 2008 fugitive dust emission factors for paved roads. ................................................118

Table 5.3–2. 2008 VMT by silt loading category for paved roads. ................................................118

Table 5.3–3. 2008 uncontrolled fugitive dust emissions from paved roads. ..................................118

Table 5.3–4. 2008 benefits of measures that reduce paved road fugitive dust in the PM10 

NAA...........................................................................................................................119

Table 5.3–5. Annual controlled fugitive dust emissions from paved roads....................................119

Table 5.3–6. 2008 VMT on unpaved roads in the PM10 NAA and Maricopa County. .................120

Table 5.3–7. 2008 VMT on all roads in the PM10 NAA and Maricopa County............................121

Table 5.3–8. Daily uncontrolled unpaved road and alley fugitive dust emissions. ........................121

Table 5.3–9. 2008 benefits of measures that reduce unpaved road and alley fugitive dust in 

the PM10 NAA. .........................................................................................................121

Table 5.3–10. Annual and average daily controlled fugitive dust emissions from unpaved 

roads...........................................................................................................................121

Table 5.4–1. Annual and average daily emissions from all onroad mobile sources in 

Maricopa County. ......................................................................................................122

Table 5.4–2. Annual and average daily emissions from all onroad mobile sources in the 

PM10 NAA. ...............................................................................................................122

Table 6.2–1. Two modeling domains defined in the UTM coordinate system...............................125

Table 6.4–1. Daily mean biogenic emissions of NOx in the PM10 NAA and Maricopa 

County, by month.......................................................................................................129

Table 6.4–2. Monthly biogenic emissions of NOx in the PM10 NAA and Maricopa County.........130

Table 6.5–1. Daily mean and annual total NOx emissions from biogenic sources.........................130

List of Figures

Figure 1.4–1. Map of Maricopa County and the PM10 nonattainment area. ........................................2

Figure 2.7–1. Data flow for annual point source emission inventory reporting. ...............................16

Figure 6.3–1. Mask of the PM10 NAA in the 4-km modeling domain (top) and mask of 

Maricopa County in the 12-km modeling domain (bottom)......................................126

Figure 6.3–2. Boundaries of the PM10 NAA (red line), the 4-km eight-hour ozone modeling 

domain (pink line), Maricopa County (blue line), and the meteorological 

observation site (red star)...........................................................................................127

Figure 6.3–3. Annual mean diurnal cycles of measured temperature (top panel) and 

downward short wave radiation (bottom panel) in 2008. ..........................................128

Figure 6.4–1. Monthly emissions of NOx in Maricopa County (pink solid line, abbreviated 

as “MC”) and the PM10 NAA (blue solid line, abbreviated as “NA”).......................129
2008 Maricopa Co. PM10 Emission Inventory x June 2011 

Appendices

Appendix 1 Public Comment Period Documentation ............................................................A1–1

– MCAQD News Release re: Publication of Draft Report (April 26, 2010)

– Announcement of Public Workshop at MCAQD (May 14, 2010)

Appendix 2 Instructions for Reporting 2008 Annual Air Pollution Emissions...................A2–1

Appendix 3 Rule Effectiveness (RE) Studies...........................................................................A3–1

3.1 Introduction .....................................................................................................A3–1

3.2 Calculating Rule Effectiveness Rates for Rules 310, 310.01, and 316 ...........A3–2

3.2.1 Calculating Rule Effectiveness for Sources Subject to Rule 310 .........A3–3

3.2.2 Calculating Rule Effectiveness for Sources Subject to Rule 310.01 ....A3–4

3.2.3 Calculating Rule Effectiveness for Sources Subject to Rule 316 .........A3–4

3.3 Calculating Rule Effectiveness Rates for Agricultural Activities, Title V

Facilities, and Non-Title V Facilities..............................................................A3–4

3.3.1 Calculating Rule Effectiveness for Agricultural Activities...................A3–6

3.2.2 Calculating Rule Effectiveness for Title V and Non-Title V Processes A3–6

3.4 References.......................................................................................................A3–6

Appendix 4 Windblown Dust Emission Estimation Methodology........................................A4–1

Introduction.............................................................................................................A4–1

Supply-Limited Windblown Dust Emission Scheme .............................................A4–1

Threshold Friction Velocity....................................................................................A4–4

Vertical Emission Fluxes........................................................................................A4–6

Land Use Data.......................................................................................................A4–10

Meteorological Data..............................................................................................A4–11

Wind Speed Data ............................................................................................A4–12

Precipitation Data............................................................................................A4–15

Calculation of Windblown Dust Emissions..........................................................A4–16

Windblown Dust Emissions from Active Agricultural Areas ........................A4–17

Summary of Pre-standardized Windblown Dust Emission Calculations .......A4–18

Standardized Windblown Dust Emissions......................................................A4–19

Summary of Standardized Windblown Dust Emissions.................................A4–21

References.............................................................................................................A4–22

Attachment I: MAG 2009 GIS Existing Land Use Database Information ...........A4–25

Appendix 5 MOVES2010a Local Input Data and RunSpecs................................................A5–1

MOVES2010a RunSpec Summary (Maricopa County, July 2008) .......................A5–2

MOVES2010a RunSpec (Maricopa County, July 2008)........................................A5–3

MOVES2010a Local Input Data (Maricopa County, July 2008) ...........................A5–6
2008 Maricopa Co. PM10 Emission Inventory 1 June 2011 

1. Introduction

1.1 Overview

This 2008 periodic PM10 emissions inventory was developed to meet requirements set forth in

Title I of the Clean Air Act Amendments of 1990 (CAAA). The CAAA require development of 

a baseline emission inventory and periodic revisions for areas that fail to meet the National 

Ambient Air Quality Standards (NAAQS). A portion of Maricopa County is classified as serious 

nonattainment for PM10.

PM10 is defined as particulate matter less than or equal to ten micrometers in diameter. This 

inventory includes primary emissions of PM10 and PM2.5 as well as three particulate matter 

precursors: nitrogen oxides (NOx), sulfur dioxides (SOx) and ammonia (NH3). The inventory 

provides emission estimates from point, area, nonroad mobile, onroad mobile and biogenic 

sources. Note that totals shown in tables may not equal the sum of individual values due to 

independent rounding.

1.2 Agencies responsible for the emissions inventory

Maricopa County Air Quality Department (MCAQD) has primary responsibility for preparing 

and submitting the 2008 Periodic PM10 Emissions Inventory for Maricopa County. Point sources 

and the majority of area, and nonroad mobile source emission estimates were prepared by 

MCAQD. The Maricopa Association of Governments (MAG) prepared the emission estimates 

for onroad mobile, biogenic, and some area and nonroad mobile source categories. Table 1.2–1 

lists those responsible for inventory preparation and quality assurance/ quality control activities, 

which are described in the respective chapters.

Table 1.2–1. Chapter authors and QA/QC contacts for this report.

Chapter Author(s) QA/QC contacts

2. Point Sources Matt Poppen, MCAQD (602) 506-6790 –Eric Raisanen and Dena Konopka

MCAQD (602) 506-6790

–Cathy Arthur, MAG (602) 254-6300

3. Area Sources –Matt Poppen, Eric Raisanen and Dena 

Konopka, MCAQD (602) 506-6790

–Cathy Arthur, MAG (602) 254-6300

–Bob Downing, MCAQD (602) 506-6790

–Cathy Arthur, MAG (602) 254-6300

4. Nonroad Mobile 

Sources

Matt Poppen and Bob Downing

MCAQD (602) 506-6790

–Eric Raisanen and Dena Konopka

MCAQD (602) 506-6790

–Cathy Arthur, MAG (602) 254-6300

5. Onroad Mobile 

Sources

Ieesuck Jung and Cathy Arthur

MAG (602) 254-6300

Bob Downing and Dena Konopka

MCAQD (602) 506-6790

6. Biogenic Sources Feng Liu

MAG (602) 254-6300

Bob Downing and Dena Konopka

MCAQD (602) 506-6790
2008 Maricopa Co. PM10 Emission Inventory 2 June 2011 

1.3 Temporal scope

Annual and typical daily emissions were estimated for the year 2008, for Maricopa County and 

the Maricopa County PM10 nonattainment area (NAA).

1.4 Geographic scope

This inventory includes emission estimates for Maricopa County and for the Maricopa County 

PM10 nonattainment area. Maricopa County encompasses approximately 9,223 square miles of 

land area, while the Maricopa County PM10 nonattainment area is approximately 2,880 square 

miles or approximately 31 percent of the Maricopa County land area. A map of Maricopa 

County and the PM10 nonattainment area is provided in Figure 1.4–1.

Figure 1.4–1. Map of Maricopa County and the PM10 nonattainment area.
2008 Maricopa Co. PM10 Emission Inventory 3 June 2011 

1.5 Overview of local demographic and land use data

Many of the emissions estimates generated in this report were calculated using demographic and 

land use data provided by the Maricopa Association of Governments (MAG). These data were 

used to apportion and/or scale Maricopa County emissions estimates to the nonattainment area 

and vice versa. (For example, county-level emissions from residential natural gas usage in Maricopa County were apportioned to the nonattainment area using the ratio of total population in 

each area). Detailed explanations of how emission estimates were apportioned or scaled are 

presented in each of the following chapters, along with the data sources used.

1.5.1 Demographic profile

The demographic data provided by MAG included population, employment data, and single 

family/multi-family splits for calendar year 2008, for both Maricopa County and the PM10 nonattainment area. Table 1.5–1 provides an overview of the demographic data used in this report.

As noted throughout the text, these data are frequently used to derive estimates of activity or 

emissions within the PM10 NAA from county-level calculations. It is important to note, however, that the nonattainment area includes a portion of Pinal County, AZ (Apache Junction) as 

shown in Figure 1.4–1. Thus in some cases (e.g., those source categories calculated based on 

total population), the multiplier used to derive nonattainment area estimates from County-level 

values may be greater than 1, and thus the resulting NAA emission totals are larger than the 

County-level estimates from which they are derived. 

Table 1.5–1. Demographic profile of Maricopa County and the PM10 nonattainment area.

Demographic variable

Maricopa

County PM10 NAA

Percent within

PM10 NAA

Total resident population 4,026,000 4,024,530 99.96%

Total non-resident population 253,760 272,610 107.43%

Total population: 4,279,760 4,297,140 100.41%

Retail employment 537,430 536,100 99.75%

Office employment 444,170 444,980 100.18%

Industrial employment 412,580 411,520 99.74%

Public employment 278,610 274,500 98.52%

Other employment 191,770 189,010 98.56%

Construction 79,680 78,980 99.12%

Work at Home 65,620 64,940 98.96%

Total employment: 2,009,860 2,000,030 99.51%

Single Family/Multi-Family Household Split: 

Single-Family 75% 75%

Multi-Family 25% 25%

Source: Maricopa Association of Governments

1.5.2 Land use data

MAG provided draft 2009 land use data (as of March 2010). The draft 2009 land use data was 

assumed to be representative of 2008. Table 1.5–2 presents a summary of the land use categories 

and acreages used to develop emissions estimates for this inventory.
2008 Maricopa Co. PM10 Emission Inventory 4 June 2011 

Table 1.5–2. Land use categories used to apportion emissions.

Land Use Category

Acreage in 

Maricopa 

County

Acreage 

within PM10

NAA

Percentage

within PM10

NAA

General/active open space/golf course (e.g., parks) 228,295 223,290 97.81%

Passive/restricted open space (e.g., mountain preserves) 2,373,545 302,999 12.77%

Lakes 12,525 9,510 75.93%

Agriculture 295,509 130,445 44.14%

Vacant (e.g., developable land) 2,227,981 472,831 21.22%

1.6 Emissions overview by source category

1.6.1 Point sources

The point source category includes those stationary sources that emit a significant amount of 

pollution into the air such as power plants, industrial processes and large manufacturing 

facilities. MCAQD utilizes the US EPA’s Annual Emissions Reporting Requirements (AERR) 

Rule to define which stationary sources are listed as point sources. A detailed definition of a 

point source can be found in Section 2.1 of Chapter 2.

Table 1.6–1 summarizes annual and typical daily emissions from point sources in Maricopa 

County and the PM10 nonattainment area, respectively. A detailed breakdown of emissions 

calculations for all point sources is contained in Chapter 2.

Table 1.6–1. Summary of annual and typical daily emissions from point sources in Maricopa County.

Annual (tons/yr) Typical day (lbs/day)

Geographic Area PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Maricopa County 601.27 555.15 2,204.91 81.15 279.06 3,323.2 3,069.1 12,151.5 449.3 1,534.2

PM10 NAA 149.84 132.94 1,317.85 28.76 132.18 841.2 747.7 7,254.3 158.2 727.0

1.6.2 Area sources

Area sources are facilities or activities whose individual emissions do not qualify them as point 

sources. Area sources represent numerous facilities or activities that individually release small 

amounts of a given pollutant, but collectively they can release significant amounts of a pollutant. 

Emissions from stationary sources that were not identified as point sources in this report have 

been included in the area source inventory. Examples of area source categories include residential wood burning, commercial cooking, waste incineration and wildfires.

Tables 1.6–2 and 1.6–3 summarize annual and season-day emissions of the chief area source 

categories, for Maricopa County and the PM10 nonattainment area, respectively. A detailed 

breakdown of emissions calculations for each area source category is contained in Chapter 3.

Table 1.6–2. Summary of annual and typical daily emissions from area sources in Maricopa County.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Category PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Fuel combustion 1,303.61 1,271.30 12,289.62 898.83 51.27 9,673.4 9,370.0 78,161.3 5,773.3 328.7

Industrial processes 11,881.57 2,953.30 362.58 129.60 1,731.34 76,667.6 19,048.2 2,816.5 1,005.8 11,077.2

Waste treatmt./disposal 230.52 204.35 77.47 58.20 1,488.07 1,613.0 1,438.8 515.3 320.0 8,131.5

Misc. area sources 29,154.21 4,012.53 126.52 32.64 13,059.05 179,712.0 27,667.0 1,676.1 446.4 71,686.1

All area sources: 42,569.90 8,441.49 12,856.18 1,119.27 16,329.74 267,665.9 57,524.0 83,169.2 7,545.5 91,223.5
2008 Maricopa Co. PM10 Emission Inventory 5 June 2011 

Table 1.6–3. Summary of annual and typical daily emissions from area sources in the PM10 NAA.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Category PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Fuel combustion 1,300.65 1,268.35 12,248.07 895.83 51.11 9,653.8 9,350.6 77,895.2 5,754.1 327.6

Industrial processes 10,655.39 2,771.19 360.48 129.58 1,724.27 68,764.6 17,877.6 2,802.3 1,005.7 11,034.4

Waste treatmt./disposal 120.77 95.42 50.30 56.85 1,494.12 799.8 630.5 309.9 312.6 8,164.6

Misc. area sources 12,444.36 2,143.52 115.94 29.74 7,693.04 81,929.6 18,879.4 2,318.0 622.4 42,455.4

All area sources: 24,521.17 6,278.48 12,774.79 1,112.00 10,962.54 161,147.8 46,738.0 83,325.3 7,694.7 61,982.0

1.6.3 Nonroad mobile sources

Nonroad mobile sources include off-highway vehicles and engines that move or are moved within a 12-month period. Tables 1.6–4 and 1.6–5 summarize annual and season-day emissions from 

nonroad mobile sources, for Maricopa County and the PM10 nonattainment area, respectively. A 

detailed breakdown of emissions calculations for each source category is contained in Chapter 4.

Table 1.6–4. Annual and typical daily emissions from nonroad mobile sources in Maricopa County.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Category PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Agricultural 34.27 33.24 365.55 0.14 0.67 219.7 213.1 2,343.3 0.9 4.3

Airport GSE (+APU) 27.21 26.68 586.73 26.43 148.7 145.8 3,206.1 144.4

Commercial 117.97 112.98 1,395.23 2.40 21.12 756.2 724.2 8,943.8 15.4 135.4

Construction & mining 1,260.98 1,220.75 14,796.63 6.60 28.10 8,083.2 7,825.3 94,850.2 42.3 180.1

Industrial 101.69 98.96 2,593.13 3.22 56.23 651.8 634.4 16,622.7 20.6 360.5

Lawn and garden 182.28 168.79 798.14 3.16 19.63 1,250.1 1,156.9 5,571.5 23.1 144.6

Pleasure craft 9.25 8.54 77.74 0.85 1.73 124.5 114.9 1,046.5 11.4 23.3

Railway maintenance 1.13 1.10 9.23 0.00 0.02 7.8 7.6 63.9 0.0 0.1

Recreational equipment 45.58 41.98 63.80 0.42 2.10 389.6 358.8 545.3 3.6 18.0

Aircraft 187.91 181.42 2,625.94 317.64 1,026.8 991.3 14,349.4 1,735.8

Locomotives 70.21 65.53 1,854.62 18.72 4.45 383.6 358.1 10,134.5 102.3 24.3

All nonroad

mobile sources: 2,038.46 1,959.96 25,166.75 379.58 134.06 13,042.0 12,530.3 157,677.4 2,099.8 890.6

Table 1.6–5. Annual and typical daily emissions from all nonroad mobile sources in the PM10 NAA.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Category PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Agricultural 15.13 14.67 161.35 0.06 0.30 97.0 94.0 1,034.3 0.4 1.9

Airport GSE (+APU) 26.99 26.48 578.95 26.22 147.5 144.7 3,163.7 143.3

Commercial 117.66 112.69 1,391.61 2.39 21.06 754.2 722.4 8,920.6 15.3 135.0

Construction & mining 1,249.88 1,210.00 14,666.42 6.55 27.85 8,012.1 7,756.4 94,015.6 42.0 178.5

Industrial 101.42 98.71 2,586.39 3.21 56.09 650.1 632.7 16,579.4 20.6 359.5

Lawn and garden 183.02 169.48 801.41 3.17 19.71 1,255.3 1,161.6 5,594.4 23.2 145.2

Pleasure craft 7.02 6.48 59.03 0.64 1.32 94.5 87.3 794.6 8.6 17.7

Railway maintenance 1.13 1.10 9.26 0.00 0.02 7.8 7.6 64.1 0.0 0.1

Recreational equipment 7.68 7.08 10.76 0.07 0.35 65.7 60.5 91.9 0.6 3.0

Aircraft 183.80 177.61 2,620.31 316.00 1,004.3 970.5 14,318.6 1,726.8

Locomotives 34.16 31.88 907.76 9.11 2.16 186.7 174.2 4,960.4 49.8 11.8

All nonroad

mobile sources: 1,927.89 1,856.18 23,793.26 367.42 128.87 12,275.2 11,812.0 149,537.7 2,030.5 852.9

1.6.4 Onroad mobile sources

Emissions from onroad mobile sources were calculated for the PM10 nonattainment area located 

primarily within Maricopa County, as well as for Maricopa County as a whole. A detailed 

breakout of emissions calculations for each area source category is contained in Chapter 5.

Tables 1.6–6 and 1.6–7 summarize annual and typical daily emissions from onroad mobile 

sources in Maricopa County and the PM10 nonattainment area, respectively.
2008 Maricopa Co. PM10 Emission Inventory 6 June 2011 

Table 1.6–6. Annual and average daily emissions from all onroad mobile sources in Maricopa County.

Emission 

Category

Annual emissions (tons/year) Average daily emissions (lbs/day)

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Exhaust, tire wear, 

and brake wear 3,295.74 2,417.89 75,033.9 314.5 1,294.1 18,009.2 13,212.4 410,021.3 1,718.2 7,072.1

Paved road

fugitive dust 7,227.77 1,912.42 — — — 39,496.0 10,450.4 — — —

Unpaved road and 

alley fugitive dust 12,358.20 1,233.60 — — — 67,530.9 6,741.0 — — —

Totals: 22,881.71 5,563.91 75,033.94 314.45 1,294.12 125,036.1 30,403.8 410,021.3 1,718.2 7,072.1

Table 1.6–7. Annual and typical daily emissions from all onroad mobile sources in the PM10 NAA.

Emission 

Category

Annual emissions (tons/year) Average daily emissions (lbs/day)

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Exhaust, tire wear, 

and brake wear 3,144.17 2,300.80 71,444.20 300.66 1,235.28 17,181.3 12,572.9 390,405.5 1,643.0 6,750.5

Paved road

fugitive dust 6,694.22 1,774.76 — — — 36,580.5 9,698.1 — — —

Unpaved road and 

alley fugitive dust 11,710.70 1,169.00 — — — 63,993.1 6,387.8 — — —

Totals: 21,549.09 5,244.56 71,444.20 300.66 1,235.28 117,754.9 28,658.8 390,405.5 1,643.0 6,750.5

1.6.5 Biogenic sources

The biogenic source category includes emissions from all vegetation (e.g., crops, indigenous

vegetation, landscaping, etc.) in Maricopa County and the PM10 nonattainment area. Emissions 

were estimated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN). 

MEGAN is a state-of-the-art biogenic emissions model developed by the National Center for 

Atmospheric Research (NCAR). Some corrections and improvements were made in the latest 

version of MEGAN2.04. MEGAN2.04 was used to compute biogenic emissions in Maricopa 

County and the PM10 nonattainment area. Annual and daily NOx emissions from biogenic 

sources are shown in Table 1.6–8 for Maricopa County and the PM10 nonattainment area.

Table 1.6–8. Annual and season-day NOx emissions from biogenic sources. 

Geographic area

Annual emissions 

(tons/yr)

Typical daily emissions 

(lbs/day)

Maricopa County 896.27 4,890.0

PM10 NAA 332.77 1,815.3

1.6.6 Summary of all source categories

Tables 1.6–9 and 1.6–10 provide summary totals of annual and typical daily emissions from all 

emission sources in Maricopa County and the PM10 nonattainment area, respectively.
2008 Maricopa Co. PM10 Emission Inventory 7 June 2011 

Table 1.6–9. Annual and typical daily emissions from all sources in Maricopa County.

Section

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Point Sources 601.27 555.15 2,204.91 81.15 279.06 3,323.2 3,069.1 12,151.5 449.3 1,534.2

Area Sources:

Fuel combustion

Industrial natural gas 30.78 30.78 575.29 2.42 12.70 197.3 197.3 3,687.7 15.5 81.4

Industrial fuel oil 458.79 458.79 6,375.08 609.61 26.25 2,941.0 2,941.0 40,865.9 3,907.8 168.3

Comm./ind. natural gas 66.54 66.54 1,267.11 5.23 4.20 426.5 426.5 8,122.5 33.5 26.9

Comm./ind. fuel oil 224.14 224.14 3,273.40 271.27 8.13 1,436.8 1,436.8 20,983.3 1,738.9 52.1

Residential natural gas 61.75 61.75 763.81 4.88 337.5 337.5 4,173.8 26.6

Residential wood 461.59 429.28 34.69 5.34 4,334.2 4,030.8 325.7 50.1

Residential fuel oil 0.01 0.01 0.25 0.10 0.1 0.1 2.3 0.9

All combustion 1,303.61 1,271.30 12,289.62 898.83 51.27 9,673.4 9,370.0 78,161.3 5,773.3 328.7

Industrial Processes

Chemical manufacturing 187.43 151.42 0.00 0.34 0.03 1,445.8 1,164.5 0.0 2.6 0.9

Food products

Commercial cooking 988.99 917.18 5,434.0 5,039.5

Grain handling 20.59 6.71 149.3 49.5

Ammonia storage 1,678.43 10,759.2

Secondary metal prod. 60.56 52.16 49.73 18.65 0.04 442.7 386.2 358.8 142.7 0.0

Mineral processes 

(concrete batch, etc.) 192.82 95.47 1,337.7 659.3

Mining & quarry (sand & 

gravel) 181.01 55.20 1,239.2 362.6

Wood products 217.26 203.25 1,668.6 1,548.3

Rubber/plastics mfg. 140.94 105.96 953.3 698.8

Fabricated metal mfg. 51.48 42.62 4.50 538.1 460.6 28.9

Residential const. 1,845.79 184.58 11,832.0 1,183.2

Commercial const. 4,320.77 432.08 27,697.2 2,769.7

Road construction 2,695.73 269.57 17,280.3 1,728.0

Construction – other 194.36 19.44 1,245.9 124.6

Electric equip. mfg. 13.94 9.64 20.45 0.18 31.55 76.9 53.2 112.4 1.1 193.7

ADEQ portables 59.00 29.50 282.18 88.93 492.9 246.5 2,275.7 721.7

Unpaved road travel 566.30 271.29 3,880.4 1,847.2

Industrial proc. NEC 144.60 107.24 10.22 21.49 16.79 953.3 726.4 69.6 137.7 94.6

All Ind. Processes 11,881.57 2,953.30 362.58 129.60 1,731.34 76,667.6 19,048.2 2,816.5 1,005.8 11,077.2

Waste Treatment/Disp.

On-site incineration 0.06 0.04 5.01 0.01 0.7 0.4 38.9 0.1

Open burning 111.46 111.46 29.96 902.2 902.2 242.4

Landfills 86.21 75.92 24.11 7.57 486.1 425.4 132.9 41.7

POTWs 1,488.07 8,131.5

Other waste 32.78 16.93 18.39 50.62 224.1 110.9 101.0 278.1

All Waste Treat/Disp. 230.52 204.35 77.47 58.20 1,488.07 1,613.0 1,438.8 515.3 320.0 8,131.5

Misc. Area Sources

Wildfires 470.39 403.43 103.79 28.46 21.76 6,271.8 5,379.0 1,383.8 379.4 290.2

Prescribed fires 0.51 0.51 0.39 0.11 0.03 169.3 169.3 131.2 36.0 10.6

Structure fires 15.04 15.04 1.95 82.2 82.2 10.7

Vehicle fires 30.04 30.04 1.20 164.1 164.1 6.6

Aircraft engine testing 0.18 0.17 6.74 2.49 1.3 1.2 50.5 19.0

Tilling 2,059.00 308.85 22,932.4 3,439.9

Harvesting 136.93 20.54 3,938.9 590.8

Unpaved agric. roads 1,739.52 173.95 11,150.8 1,115.1

Cotton ginning 17.90 5.11 103.8 29.7

Fertilizer application 2,276.43 12,439.5

Livestock 455.80 50.14 9,583.89 2,490.7 274.0 52,514.5

Crematories 0.93 0.62 12.39 1.58 7.0 4.7 93.1 11.9

Accidental releases 0.01 0.01 0.06 0.1 0.1 0.3

Humans 1,176.93 6,431.3

Leaf blowers fugitive dust 891.36 336.41 4,870.8 1,838.3

Offroad rec. vehicles 

fugitive dust 12,082.12 1,200.11 66,022.5 6,558.0

Travel on unpaved 

parking lots 4,445.36 446.24 24,291.6 2,438.5

Windblown dust 6,809.13 1,021.37 37,214.6 5,582.2

All Misc. Area Sources 29,154.21 4,012.53 126.52 32.64 13,059.05 179,712.0 27,667.0 1,676.1 446.4 71,686.1

All Area Sources: 42,569.90 8,441.49 12,856.18 1,119.27 16,329.74 267,665.9 57,524.0 83,169.2 7,545.5 91,223.5
2008 Maricopa Co. PM10 Emission Inventory 8 June 2011 

Table 1.6–9 (continued). Annual and typical daily emissions from all sources in Maricopa County.

Section

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Nonroad Sources:

Agricultural equipment 34.27 33.24 365.55 0.14 0.67 219.7 213.1 2,343.3 0.9 4.3

Airport GSE (+APU) 27.21 26.68 586.73 26.43 148.7 145.8 3,206.1 144.4

Commercial equipment 117.97 112.98 1,395.23 2.40 21.12 756.2 724.2 8,943.8 15.4 135.4

Construction and mining 

equipment 1,260.98 1,220.75 14,796.63 6.60 28.10 8,083.2 7,825.3 94,850.2 42.3 180.1

Industrial equipment 101.69 98.96 2,593.13 3.22 56.23 651.8 634.4 16,622.7 20.6 360.5

Lawn and garden 

equipment 182.28 168.79 798.14 3.16 19.63 1,250.1 1,156.9 5,571.5 23.1 144.6

Pleasure craft 9.25 8.54 77.74 0.85 1.73 124.5 114.9 1,046.5 11.4 23.3

Railway maintenance 

equipment 1.13 1.10 9.23 0.00 0.02 7.8 7.6 63.9 0.0 0.1

Recreational equipment 45.58 41.98 63.80 0.42 2.10 389.6 358.8 545.3 3.6 18.0

Aircraft 187.91 181.42 2,625.94 317.64 1,026.8 991.4 14,349.4 1,735.8

Locomotives 70.21 65.53 1,854.62 18.72 4.45 383.6 358.1 10,134.5 102.3 24.3

All Nonroad Sources 2,038.46 1,959.96 25,166.75 379.58 134.06 13,042.0 12,530.4 157,677.4 2,099.8 890.6

Onroad Sources:

Exhaust, tire wear, 

and brake wear 3,295.74 2,417.89 75,033.94 314.45 1,294.12 18,009.2 13,212.4 410,021.3 1,718.2 7,072.1

Paved road

fugitive dust 7,227.77 1,912.42 39,496.0 10,450.4

Unpaved road and 

alley fugitive dust 12,358.20 1,233.60 67,530.9 6,741.0

All Mobile Sources: 22,881.71 5,563.91 75,033.94 314.45 1,294.12 125,036.1 30,403.8 410,021.3 1,718.2 7,072.1

Biogenic Sources: 896.27 4,890.0

TOTAL, All Sources: 68,091.34 16,520.51 116,158.05 1,894.45 18,036.97 409,067.3 103,527.3 667,909.3 11,812.7 100,720.4
2008 Maricopa Co. PM10 Emission Inventory 9 June 2011 

Table 1.6–10. Annual and typical daily emissions from all sources in the PM10 nonattainment area.

Section

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Point Sources 149.84 132.94 1,317.85 28.76 132.18 841.2 747.7 7,254.3 158.2 727.0

Area Sources:

Fuel combustion

Industrial natural gas 30.70 30.70 573.79 2.41 12.66 196.8 196.8 3,678.2 15.5 81.2

Industrial fuel oil 457.60 457.60 6,358.50 608.03 26.19 2,933.3 2,933.3 40,759.6 3,897.6 167.9

Comm./ind. natural gas 66.20 66.20 1,260.65 5.20 4.18 424.4 424.4 8,081.1 33.3 26.8

Comm./ind. fuel oil 223.00 223.00 3,256.70 269.88 8.09 1,429.5 1,429.5 20,876.3 1,730.0 51.8

Residential natural gas 61.73 61.73 763.51 4.87 337.3 337.3 4,172.2 26.6

Residential wood 461.41 429.11 34.67 5.33 4,332.5 4,029.2 325.6 50.1

Residential fuel oil 0.01 0.01 0.25 0.10 0.1 0.1 2.3 0.9

All combustion 1,300.65 1,268.35 12,248.07 895.83 51.11 9,653.8 9,350.6 77,895.2 5,754.1 327.6

Industrial Processes

Chemical manufacturing 186.94 151.03 0.00 0.34 0.03 1,442.0 1,161.5 0.0 2.6 0.9

Food products

Commercial cooking 993.04 920.94 5,456.3 5,060.1

Grain handling 16.73 5.68 125.3 43.0

Ammonia storage 1,674.07 10,731.2

Secondary metal prod. 60.56 52.16 49.73 18.65 0.04 442.7 386.2 358.8 142.7 0.0

Mineral processes 

(concrete batch, etc.) 187.73 91.92 1,302.8 635.6

Mining & quarry (sand & 

gravel) 156.60 46.81 1,075.7 307.2

Wood products 216.69 202.72 1,664.3 1,544.3

Rubber/plastics mfg. 140.57 105.68 950.9 697.0

Fabricated metal mfg. 51.35 42.51 4.49 536.7 459.4 28.8

Residential const. 1,692.38 169.24 10,920.3 1,092.0

Commercial const. 4,057.29 405.73 25,897.4 2,589.7

Road construction 2,051.78 205.18 13,156.8 1,315.7

Construction – other 162.41 16.24 1,043.9 104.4

Electric equip. mfg. 13.94 9.64 20.45 0.18 31.55 76.9 53.2 112.4 1.1 193.7

ADEQ portable sources 59.00 29.50 282.18 88.93 492.9 246.5 2,275.7 721.7

Unpaved road travel 472.36 217.08 3,273.9 1,500.1

Industrial proc. NEC 136.00 99.12 8.12 21.47 14.10 906.0 681.7 55.4 137.6 79.8

All Ind. Processes 10,655.39 2,771.19 360.48 129.58 1,724.27 68,764.6 17,877.6 2,802.3 1,005.7 11,034.4

Waste Treatment/Disp.

On-site incineration 0.06 0.04 5.01 0.01 0.7 0.4 38.9 0.1

Open burning 27.67 27.67 7.44 232.6 232.6 62.5

Landfills 60.25 50.78 19.47 6.22 342.4 286.6 107.4 34.3

POTWs 1,494.12 8,164.6

Other waste 32.78 16.93 18.39 50.62 224.1 110.9 101.0 278.1

All Waste Treat/Disp. 120.77 95.42 50.30 56.85 1,494.12 799.8 630.5 309.9 312.6 8,164.6

Misc. Area Sources

Wildfires 423.56 363.27 93.46 25.62 19.60 9,412.5 8,072.7 2,076.8 569.4 435.5

Prescribed fires 0.21 0.21 0.16 0.04 0.01 104.0 104.0 80.6 22.1 6.5

Structure fires 15.10 15.10 1.96 82.5 82.5 10.7

Vehicle fires 30.16 30.16 1.21 164.8 164.8 6.6

Aircraft engine testing 0.18 0.17 6.74 2.49 1.3 1.2 50.5 19.0

Tilling 834.20 125.13 9,327.3 1,399.1

Harvesting 54.14 8.12 1,560.0 234.0

Unpaved agric. roads 731.03 73.10 4,686.1 468.6

Cotton ginning 4.86 1.39 26.7 7.6

Fertilizer application 1,004.82 5,490.8

Livestock 260.95 28.70 5,486.90 1,426.0 156.9 30,065.2

Crematories 0.93 0.62 12.36 1.58 7.0 4.6 92.6 11.8

Accidental releases 0.01 0.01 0.06 0.1 0.1 0.3

Humans 1,181.71 6,457.5

Leaf blowers fugitive 

dust 894.98 337.78 4,890.6 1,845.8

Offroad rec. vehicles 

fugitive dust 2,014.17 200.09 11,006.4 1,093.4

Travel on unpaved 

parking lots 2,365.07 237.45 12,923.9 1,297.5

Windblown dust 4,814.80 722.22 26,310.4 3,946.6

All Misc. Area Sources 12,444.36 2,143.52 115.94 29.74 7,693.04 81,929.6 18,879.4 2,318.0 622.4 42,455.4

All Area Sources: 24,521.17 6,278.48 12,774.79 1,112.00 10,962.54 161,147.8 46,738.0 83,325.3 7,694.7 61,982.0
2008 Maricopa Co. PM10 Emission Inventory 10 June 2011 

Table 1.6–10 (cont’d). Annual and typical daily emissions from all sources in the PM10 nonattainment area.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Section PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Nonroad Sources:

Agricultural equipment 15.13 14.67 161.35 0.06 0.30 97.0 94.0 1,034.3 0.4 1.9

Airport GSE (+APU) 26.99 26.48 578.95 26.22 147.5 144.7 3,163.7 143.3

Commercial equipment 117.66 112.69 1,391.61 2.39 21.06 754.2 722.4 8,920.6 15.3 135.0

Construction and 

mining equipment 1,249.88 1,210.00 14,666.42 6.55 27.85 8,012.1 7,756.4 94,015.6 42.0 178.5

Industrial equipment 101.42 98.71 2,586.39 3.21 56.09 650.1 632.7 16,579.4 20.6 359.5

Lawn and garden 

equipment 183.02 169.48 801.41 3.17 19.71 1,255.3 1,161.6 5,594.4 23.2 145.2

Pleasure craft 7.02 6.48 59.03 0.64 1.32 94.5 87.3 794.6 8.6 17.7

Railway maintenance 

equipment 1.13 1.10 9.26 0.00 0.02 7.8 7.6 64.1 0.0 0.1

Recreational 

equipment 7.68 7.08 10.76 0.07 0.35 65.7 60.5 91.9 0.6 3.0

Aircraft 183.80 177.61 2,620.31 316.00 1,004.3 970.5 14,318.6 1,726.8

Locomotives 34.16 31.88 907.76 9.11 2.16 186.7 174.2 4,960.4 49.8 11.8

All Nonroad Sources: 1,927.89 1,856.18 23,793.26 367.42 128.87 12,275.2 11,812.0 149,537.7 2,030.5 852.9

Onroad Sources:

Exhaust, tire wear,

and brake wear 3,144.17 2,300.80 71,444.20 300.66 1,235.28 17,181.3 12,572.9 390,405.5 1,643.0 6,750.5

Paved road

fugitive dust 6,694.22 1,774.76 36,580.5 9,698.1

Unpaved road and 

alley fugitive dust 11,710.70 1,169.00 63,993.1 6,387.8

All Mobile Sources: 21,549.09 5,244.56 71,444.20 300.66 1,235.28 117,754.9 28,658.8 390,405.5 1,643.0 6,750.5

Biogenic Sources: 332.77 1,815.3

TOTAL, All Sources: 48,147.99 13,512.16 109,662.87 1,808.84 12,458.87 292,019.1 87,956.5 632,338.1 11,526.4 70,312.4

1.7 Public review process

Maricopa County Air Quality Department released a draft version of this document, its 2008 

PM10 emission inventory, for a 30-day public review and comment period on April 26, 2010. 

(The department’s news release announcing the availability of the draft report, and outlining the 

schedule for public review and comment, is contained in Appendix 1). The department held a 

public workshop on May 14, 2010 to discuss the draft inventory. No formal comments were 

received during the 30-day public comment period. 
2008 Maricopa Co. PM10 Emission Inventory 11 June 2011 

2. Point Sources

2.1 Introduction and scope

This inventory of PM10 and related pollutants is one of a number of emission inventories being 

prepared to meet US EPA reporting requirements.

In addition to preparing periodic emissions inventories for the PM10 nonattainment area (NAA) 

as a commitment under the current PM10 State Implementation Plan (SIP), the federal Air Emission Reporting Requirements (AERR) rule requires that state and local agencies prepare emissions estimates on a county basis, and submit data electronically to the US EPA for inclusion in 

the National Emission Inventory (NEI) for 2008. This inventory is being developed concurrently 

with similar inventories for CO and ozone precursors (VOC, NOx, and CO), as part of Maricopa 

County's requirements under the respective SIPs.

In order to provide consistency among all these inventories, it was decided to standardize the 

definition of a “point source” by adopting the designation of point sources as outlined in the 

AERR:

We are basing the requirement for point source format reporting on whether the 

source is major under 40 CFR part 70 for the pollutants for which reporting is 

required, i.e., CO, VOC, NOx, SO2, PM2.5, PM10, lead and NH3 but without regard 

to emissions of HAPs... [T]his approach will result in a more stable universe of 

reporting point sources, which in turn will facilitate elimination of overlaps and 

gaps in estimating point source emissions, as compared to nonpoint source emissions. Under this requirement, states will know well in advance of the start of the 

inventory year which sources will need to be reported. (US EPA, 2008)

Additionally, EPA guidance requires emission inventories prepared for SIP development purposes to consider point sources with 25 miles of the nonattainment area boundary. No additional 

point sources met this reporting threshold.

Several tables have been constructed to provide the point source emissions and category totals.

Table 2.2–1 provides an alphabetical listing of all point sources and their location. Table 2.4–1 

shows the 2008 annual and typical day emissions of PM10, PM2.5, NOx, SOx and NH3 for those 

point sources which reported emissions of one or more of these pollutants broken out by facility. 

Table 2.6–1 summarizes point source emissions by source category for the county and PM10 nonattainment area. Note that totals shown in the tables may not equal the sum of individual values 

due to independent rounding.

2.2 Identification of point sources

The Maricopa County Air Quality Department (MCAQD) identified point sources within Maricopa County through its electronic permit system database, EMS, and the 2008 annual emissions 

reports submitted to the department. A total of 25 stationary sources were identified as point 

sources using the definition described in Section 2.1. There are no additional point sources 

within the 25-mile boundary around the PM10 nonattainment area with permits issued by the 

Pinal County Air Quality Control District (PCAQCD). While the Arizona Department of 

Environmental Quality (ADEQ) retains permitting authority for a limited number of industrial 
2008 Maricopa Co. PM10 Emission Inventory 12 June 2011 

source categories in Maricopa County, no ADEQ-permitted facilities are considered point 

sources, and are addressed instead as area sources.

Table 2.2–1 contains an alphabetical listing of all point sources, including a unique business 

identification number, NAICS industry classification code, business name, and physical address.

Table 2.2–1. Name and location of all point sources in Maricopa County.

ID # NAICS Business name Address City ZIP

245 337122 AF Lorts Manufacturing Company 8120 W Harrison St Tolleson 85353

3313 221112 APS West Phx Power Plant 4606 W Hadley St Phoenix 85043

43063 221112 Dynegy Arlington Valley LLC 39027 W Elliot Rd Arlington 85322 *

44439 221112 Gila River Power Station 1250 E Watermelon Rd Gila Bend 85337 *

1418 326299 Goodrich Aircraft Interior Products 3414 S 5th St Phoenix 85040

355 336412 Honeywell-Engines Systems & Services 111 S 34th St Phoenix 85034

3300 92811 Luke AFB – 56th Fighter Wing 14002 W Marauder St Glendale 85309

62 33711 Mastercraft Cabinets Inc 305 S Brooks Mesa 85202

44186 221112 Mesquite Generating Station 37625 W Elliot Rd Arlington 85322 *

43530 221112 New Harquahala Generating Co 2530 N 491st Ave Tonopah 85354 *

20706 32614 New Wincup Holdings Inc 7980 W Buckeye Rd Phoenix 85043

1331 337122 Oak Canyon Manufacturing Inc 3021 N 29th Dr Phoenix 85017

52382 221112 Ocotillo Power Plant 1500 E University Dr Tempe 85281

1341 33992 Penn Racquet Sports Inc 306 S 45th Ave Phoenix 85043

42956 221112 Redhawk Generating Facility 11600 S 363rd Ave Arlington 85322 *

303 332431 Rexam Beverage Can Company 211 N 51st Ave Phoenix 85043

3315 221112 Santan Generating Station 1005 S Val Vista Rd Gilbert 85296

4175 424710 SFPP LP Phoenix Terminal 49 N 53rd Ave Phoenix 85043

3316 221112 SRP Agua Fria Generating Station 7302 W Northern Ave Glendale 85303

3317 221112 SRP Kyrene Generating Station 7005 S Kyrene Rd Tempe 85283

552 337122 Thornwood Furniture Mfg 5125 E Madison St Phoenix 85034

1210 337122 Trendwood Inc (S. 15th Ave.) 2402 S 15th Ave Phoenix 85007

1211 337122 Trendwood Inc (E. University) 261 E University Dr Phoenix 85004

174 325998 W R Meadows of Az Inc 4220 S Sarival Ave Goodyear 85338

1382 33711 Woodcase Fine Cabinetry Inc 3255 W Osborn Rd Phoenix 85017

* = Facility is outside the PM10 nonattainment area.

2.3 Procedures for estimating emissions from point sources

Annual and typical daily emission estimates were determined from annual source emission 

reports, MCAQD investigation reports, permit files and logs, or telephone contacts with sources. 

For most of the sources, material balance methods were used for determining emissions. Emissions were estimated using the emission factors from AP–42, source tests, engineering calculations, or manufacturers' specifications.

MCAQD distributes annual emissions survey forms to nearly all facilities for which MCAQD 

has issued an operating permit. Facilities are required to report detailed information on stacks, 

control devices, operating schedules, and process-level information concerning their annual 

activities. (See Appendix 2 for a copy of the instructions to complete the emissions inventory.) 

These instructions include examples and explanations on how to complete the annual emissions 

reporting forms that facilities must submit to MCAQD.

After a facility has submitted an annual emissions report to MCAQD, emissions inventory staff 

check all reports for missing and questionable data, and check the accuracy and reasonableness 

of all emissions calculations with AP–42, the Factor Information and REtrieval (webFIRE) 
2008 Maricopa Co. PM10 Emission Inventory 13 June 2011 

software, and other EPA documentation. Control efficiencies are determined by source tests 

when available, or by AP–42 factors, engineering calculations, or manufacturers' specifications. 

MCAQD has conducted annual emissions surveys for permitted facilities since 1988, and the 

department's database system, EMS, contains numerous automated quality assurance/quality 

control checks for data input and processing.

2.3.1 Calculation of PM2.5 emissions

For all county-permitted sources that submitted an annual emission inventory report, all processlevel emissions for PM10, NOx, SOx, and NH3 were calculated for each facility. Actual emissions 

for these pollutants were calculated using reported emission factors (from AP–42 or source test 

results) and reflecting any control devices installed. PM2.5 was calculated using a variety of 

methods, depending on the Source Classification Code (SCC) of the process reported:

1. For those SCCs and control device combinations included in EPA’s WebFIRE, this 

database was used to calculate PM2.5, using EPA-recommended emission factors and 

typical control efficiencies.

2. For processes with no PM10 controls, emission factors for PM2.5 published by the 

California Air Resources Board (CARB, 2004) were used where available.

3. For all other processes (where neither of the above resources provided guidance), PM2.5

was assumed equal to PM10 as a conservative estimate.

2.3.2 Application of rule effectiveness

Rule effectiveness reflects the actual ability of a regulatory program to achieve the emission 

reductions required by regulation. The concept of applying rule effectiveness in a SIP emission 

inventory has evolved from the observation that regulatory programs may be less than 100 percent effective for some source categories. Rule effectiveness (“RE”) is applied to those sources 

affected by a regulation and for which emissions are determined by means of emission factors 

and control efficiency estimates.

MCAQD has estimated RE for three distinct groups of industrial processes. (See Appendix 3 for 

details on the methods and data used in computing RE rates): 

• For manually controlled processes that are regulated under Maricopa County Rule 316 (Nonmetallic Mineral Processing), the analysis showed an overall rule effectiveness of 65.44%.

• For most other processes that claimed emissions reductions through the use of a control 

device, RE calculations were performed separately for Title V and non-Title V sources. 

Overall RE values of 90.94% (for Title V processes) and 84.27% (for non-Title V) were 

calculated.

2.4 Detailed overview of point source emissions

Table 2.4–1 provides a summary of annual and typical daily emissions from all point sources, 

within and outside the PM10 nonattainment area. Sources for which rule effectiveness has been 

applied (for PM10 emissions) are noted. Values of “0.00” and “0.0” for annual and daily emissions denote a value below the level of significance (0.005 tons/yr and 0.05 lbs/day, 

respectively).
2008 Maricopa Co. PM10 Emission Inventory 14 June 2011 

Table 2.4–1. Annual and typical daily point source emissions, by facility.

Annual emissions (tons/yr) Typical daily (lbs/day)

ID # Business name PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

245 AF Lorts Manufacturing Company * 2.69 2.68 0.01 0.00 0.00 20.7 20.6 0.1 0.0 0.0

3313 APS West Phx Power Plant 22.94 19.47 394.24 4.51 81.39 126.0 107.0 2,166.1 24.8 447.2

43063 Dynegy Arlington Valley LLC †* 6.40 3.58 35.50 2.20 5.38 36.5 20.9 214.4 15.2 29.6

44439 Gila River Power Station † 99.50 92.13 343.01 17.36 5.77 546.9 506.4 1,887.5 95.4 31.8

1418 Goodrich Aircraft Interior Products * 0.16 0.16 0.42 0.00 0.01 1.5 1.5 3.2 0.0 0.1

355 Honeywell-Engines Systems & Srvs. 3.17 3.16 51.42 9.91 0.65 17.7 17.6 282.5 54.5 4.0

3300 Luke AFB – 56th Fighter Wing * 0.60 0.59 7.15 0.15 0.02 3.7 3.7 43.1 1.0 0.1

62 Mastercraft Cabinets Inc 0.18 0.14 0.04 0.00 0.00 1.4 1.1 0.3 0.0 0.0

44186 Mesquite Generating Station † 152.65 144.01 243.09 17.12 15.56 838.8 791.3 1,336.4 94.1 85.5

43530 New Harquahala Generating Co † 116.35 116.11 86.29 6.46 93.52 639.3 638.0 474.1 35.5 513.9

20706 New Wincup Holdings Inc 0.94 0.94 12.42 0.07 0.40 5.2 5.2 68.3 0.4 2.2

1331 Oak Canyon Manufacturing Inc 0.01 0.00 0.00 0.00 0.00 0.0 0.0 0.0 0.0 0.0

52382 Ocotillo Power Plant 8.37 6.48 64.45 0.29 1.67 46.0 35.6 354.1 1.6 9.2

1341 Penn Racquet Sports Inc * 1.74 1.74 3.51 0.02 0.11 13.4 13.4 27.0 0.2 0.9

42956 Redhawk Generating Facility † 76.53 66.38 179.16 9.25 26.65 420.5 364.7 984.8 50.9 146.4

303 Rexam Beverage Can Company * 0.33 0.33 4.39 0.03 0.14 1.8 1.8 24.1 0.1 0.8

3315 Santan Generating Station 51.88 50.33 313.85 10.59 35.55 285.1 276.5 1,724.4 58.2 195.3

4175 SFPP LP Phoenix Terminal 0.63 0.61 4.96 0.24 0.00 3.5 3.3 27.2 1.3 0.0

3316 SRP Agua Fria Generating Station 25.21 18.01 392.20 0.58 3.67 138.5 98.9 2,154.9 3.2 20.1

3317 SRP Kyrene Generating Station 26.24 25.64 60.60 2.19 8.56 144.2 140.9 333.0 12.1 47.0

552 Thornwood Furniture Mfg * 2.66 2.42 0.10 0.00 0.00 20.5 18.6 0.8 0.0 0.0

1210 Trendwood Inc (S. 15th Ave.) 0.05 0.05 0.00 0.00 0.00 0.4 0.4 0.0 0.0 0.0

1211 Trendwood Inc (E. University) 0.01 0.01 0.00 0.00 0.00 0.1 0.0 0.0 0.0 0.0

174 W R Meadows of Az Inc 0.01 0.01 0.12 0.00 0.00 0.1 0.1 1.5 0.0 0.0

1382 Woodcase Fine Cabinetry Inc 0.23 0.18 0.00 0.00 0.00 1.8 1.4 0.0 0.0 0.0

† = Facility is outside the PM10 nonattainment area.

* = Facility for which rule effectiveness has been applied.

2.5 Emission reduction credits

A major source or major modification planned in a nonattainment area must obtain emissions 

reductions as a condition for approval. These emissions reductions, generally obtained from 

existing sources located in the vicinity of a proposed source must offset the emissions increase 

from the new source or modification. The obvious purpose of acquiring offsetting emissions 

decreases is to allow an area to move towards attainment of the national ambient air quality 

standards while still allowing some industrial growth.

In order for these emission reductions to be available in the future for offsetting, they must be: 1) 

explicitly included and quantified as growth in projection year inventories required in rate of 

progress plans or attainment demonstrations that were based on 1990 actual inventories, and 2) 

meet the requirements outlined in MCAQD Rule 240 (Permit Requirements for New Major 

Sources and Major Modification to Existing Major Sources).

Table 2.5–1 provides a list of emission reduction credits for PM10, NOx, and SOx. Only one 

previously operational facility maintains emission reduction credits that are still valid for 

inclusion in this report and the rate of progress plan.

Table 2.5–1. Emission reduction credits.

Facility

Emission reduction credits (tons/yr)

ID PM10 NOx SOx

1151 Freescale Semiconductor, Inc. (formerly Motorola Mesa) 1.80 8.00 0.16
2008 Maricopa Co. PM10 Emission Inventory 15 June 2011 

2.6 Summary of point source emissions

Table 2.6–1 provides an overview of source category contributions to point source emissions for 

Maricopa County and the PM10 nonattainment area.

Table 2.6–1. Annual and typical daily point source emissions (including emission reduction credits).

Annual (tons/yr) Typical day (lbs/day)

Geographic Area PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Maricopa County 601.27 555.15 2,204.91 81.15 279.06 3,323.2 3,069.1 12,151.5 449.3 1,534.2

PM10 NAA 149.84 132.94 1,317.85 28.76 132.18 841.2 747.7 7,254.3 158.2 727.0

2.7 Quality assurance / quality control procedures

2.7.1 Emission survey preparation and data collection

The MCAQD's Emissions Inventory (EI) Unit annually collects point source criteria pollutant 

emission data from sources in the county. MCAQD annually reviews EPA guidance, documents 

from the Emission Inventory Improvement Program (EIIP), and other source materials to ensure 

that the most current emission factors and emission calculation methods are used for each year's 

survey. Each January, the EI Unit prepares a pre-populated hard copy of the preceding year’s 

submissions and mails reporting forms to permitted sources, along with detailed instructions for 

completing the forms. (A copy of these instructions is included as Appendix 2). The EI Unit 

asks sources to verify and update the data. The EI Unit also holds workshops from February

through April to assist businesses in completing EI forms.

The general data flow for data collection and inventory preparation is shown in Figure 2.7–1.
2008 Maricopa Co. PM10 Emission Inventory 16 June 2011 

Figure 2.7–1. Data flow for annual point source emission inventory reporting.

Issue NOVs for 

late submitters

EI Reporting

Forms EI Reporting

Forms

Log In EI

reports/ Issue

Receipts

Data Entry

Create

Inventory files

Data

Reconciliation

EMS

Technical QA/

QC

• Code/field check

• Range checks

• Referential value checks

Using completed survey data

• Hard Copy Forms/

Instructions

• Instruction on Web

Automated QA checks

Finalized Inventory

2.7.2 Submission processing

Submitted EI reports are logged in as they are received, and receipts are issued for emissions fees 

paid. The data are input “as received” into the department's data base. During data entry, a variety of automated quality control (QC) checks are performed, including:

• pull-down menus to minimize data entry errors (e.g., city, pollutant, emission factor unit, 

etc.)

• mandatory data field requirement checks (e.g., a warning screen appears if a user tries to 

save an emission record with a missing emission factor).

• range checks (e.g., were valid SCC, Tier, SIC, and NAICS codes entered?)

• referential value checks (e.g., emission factor units, annual throughput units)

• automatic formatting of date, time, telephone number fields, etc.

Automated quality assurance (QA) checks on the report that has been entered include the 

following:

• Comparing reported emission factors to SCC reference lists

• Comparing reported emission factors to material name reference list
2008 Maricopa Co. PM10 Emission Inventory 17 June 2011 

• Checking the report for calculation errors. This includes annual throughput, emission 

factors, unit conversion factors (e.g., BTU to therms), capture efficiency, primary / 

secondary control device efficiency, and any offsite recycling credits claimed.

• Checking the report for completeness of required data.

When data entry is complete, an electronic version of the original data is preserved separately to 

document changes made during the technical review and QA/QC process.

When errors are flagged, the businesses are contacted and correct information is obtained and 

input to the EMS. Outstanding reporting issues are documented. Confidential business information (CBI) is identified by a checkbox on the form, and these data elements are flagged during 

data entry and are not transmitted to the EPA. To prepare the inventory for submittal to the 

National Emissions Inventory (NEI), the EI Unit runs Microsoft Access queries on the data in the 

EMS to pull fields for the NEI Input format (NIF) tables.

2.7.3 Analysis of annual point source emissions data for this inventory

Two air quality planners checked inventory accuracy and reasonableness, and assured that all 

point sources had been identified and that the methodology applied to calculate emissions was 

appropriate and that the calculations were correct. Other reasonableness checks were conducted 

by recalculating emissions using methods other than those used to make the initial emissions calculations and then comparing results. QA was conducted by checking all emissions reports submitted to MCAQD for the year 2008 for missing and questionable data and by checking the 

accuracy and reasonableness of all emissions calculations made for such reports. Notes concerning follow-up calls and corrections to calculations were documented on each 2008 annual 

emissions report.

The QA point source coordinator reviewed and checked calculations, identified errors, and 

performed completeness, reasonableness and accuracy checks.

2.8 References

CARB, 2004. Speciation Profiles and Size Fractions. Available at: http://www.arb.ca.gov/ei/

speciate/speciate.htm

US EPA, 2008. Air Emissions Reporting Requirements. 73 Fed. Reg. 76539. Available at: 

.

http://www.epa.gov/ttn/chief/aerr/final_published_aerr.pdf.
2008 Maricopa Co. PM10 Emission Inventory 18 June 2011 

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2008 Maricopa Co. PM10 Emission Inventory 19 June 2011 

3. Area Sources

3.1 Scope and methodology

This chapter considers all stationary sources which are too small or too numerous to be treated as 

point sources. EPA guidance documents, including “Introduction to Area Source Inventory 

Development” (US EPA, 2001a) as well as permit and emissions data in the MCAQD’s Environmental Management System (EMS) database, and previous SIP inventories, were evaluated to 

develop the list of area-source categories for inclusion. Some source categories were deemed 

“insignificant” because there are no large production facilities and/or very few small sources, and 

therefore emissions were not quantified. MCAQD prepared the area-source emission estimates 

for all area sources and provided quality assurance checks on all data. Table 3.1–1 contains a list 

of all area-source categories, with Source Classification Codes (SCCs), addressed in this chapter.

Table 3.1–1. List of area-source categories included in this PM10 inventory.

SCC Code Category Description Section

Fuel combustion:

2102006000 Industrial natural gas 3.2.1

2102004000 Industrial fuel oil 3.2.2

2103006000 Commercial/institutional natural gas 3.2.3

2103004000 Commercial/institutional fuel oil 3.2.4

2104006000 Residential natural gas 3.2.5

2104008000 Residential wood 3.2.6

2104004000 Residential fuel oil 3.2.7

Industrial processes:

2301010000 Chemical manufacturing 3.3.1

2302002000 Commercial cooking 3.3.2.1

2302040000 Grain handling/processing 3.3.2.2

2302080000 Ammonia cold storage 3.3.2.3

2304000000 Secondary metal production 3.3.3

2305000000 Non-metallic mineral processes 3.3.4

2325000000 Mining and quarrying 3.3.5

2307000000 Wood product manufacturing 3.3.6

2308000000 Rubber/plastics manufacturing 3.3.7

2309000000 Fabricated metal products manufacturing 3.3.8

2311010000 Residential construction 3.3.9

2311020000 Commercial construction 3.3.9

2311030000 Road construction 3.3.9

n/a Other construction 3.3.9

2312000000 Electrical equipment manufacturing 3.3.10

n/a State-permitted portable sources 3.3.11

n/a Paved/unpaved road travel on industrial sites 3.3.12

2399000000 Industrial processes not elsewhere classified (NEC) 3.3.13

Waste treatment and disposal:

2601000000 On-site incineration 3.4.1

2610000000 Open burning 3.4.2

2620000000 Landfills 3.4.3

2630000000 Publicly owned treatment works (POTWs) 3.4.4

2650000000 Other industrial waste disposal 3.4.5

Miscellaneous area sources:

2810001000 Wildfires 3.5.1.1

2810014000 Prescribed fires 3.5.1.2
2008 Maricopa Co. PM10 Emission Inventory 20 June 2011 

Table 3.1–1. (continued) List of area-source categories.

SCC Code Category Description Section

Miscellaneous area sources: (continued)

2810030000 Structure fires 3.5.1.3

2810050000 Vehicle fires 3.5.1.4

2810040000 Engine testing 3.5.1.5

2801000003 Tilling 3.5.2.1

2801000005 Harvesting 3.5.2.2

n/a Travel on unpaved agricultural roads 3.5.2.3

2801000000 Cotton ginning 3.5.2.4

2801700000 Fertilizer application 3.5.2.5

2810060000 Livestock 3.5.3

2810060000 Health services: crematories 3.5.4

2830000000 Accidental releases 3.5.5

2810010000 Humans 3.5.6

n/a Leaf blower fugitive dust 3.5.7

n/a Offroad recreational vehicle fugitive dust 3.5.8

n/a Unpaved parking lots fugitive dust 3.5.9

2730100000 Windblown dust 3.5.10

For nearly all categories, emissions were calculated in one of the following ways:

• Emissions estimates for some categories were developed by conducting surveys on local 

usage (e.g., natural gas consumption) or derived from state-wide data (e.g., fuel oil use).

• For some widespread or diverse categories (e.g., ammonia cold storage), emissions were 

calculated using published per-capita or per-employee emission factors.

• For source categories with some information available from annual emissions reports 

(e.g., wood product manufacturing), these data were combined with employment data to 

“scale up” reported emissions to reflect the entire source category.

• For those source categories that have detailed emissions data available from most or all of 

the significant sources in the category, emissions were calculated based on the detailed 

process-level and operational data provided by these sources.

The specific emissions estimation methodologies used for each source category (including the 

derivation and application of rule effectiveness) are described in greater detail in the respective 

sections.

3.2 Fuel combustion

Area-source emissions for the following seven categories of fuel consumption were calculated: 

Industrial natural gas, industrial fuel oil, commercial/institutional natural gas, commercial/ 

institutional fuel oil, residential natural gas, residential wood, and residential fuel oil. Data for 

emissions calculations from natural gas combustion came from a survey of the three natural gas 

suppliers in Maricopa County. Table 3.2–1 summarizes the natural gas sales data received from 

Maricopa County natural gas suppliers.

Table 3.2–1. Maricopa County natural gas sales data by supply company and end-user category.

Natural gas 

supplier

Sales by end user category (in MMCF/yr)

Electric 

Utilities Industrial 

Commercial/

Institutional Residential Transport* Other*

Southwest Gas 17.07 1,543.27 15,643.15 14,911.67 6,487.35 n/a

City of Mesa 6.52 93.02 1,609.12 1,339.62 n/a 244.97

El Paso 227,608.92 201.90 n/a n/a n/a 6.07

* For emissions calculations, sales from transport and other were grouped with industrial sales.
2008 Maricopa Co. PM10 Emission Inventory 21 June 2011 

Area-source emissions for wood and fuel oil combustion were calculated from Arizona statelevel sales and consumption data as described in the following subsections. Area-source emissions from coal and liquid petroleum gas were not calculated, as emissions from these categories 

were determined to be insignificant.

3.2.1 Industrial natural gas

All natural gas suppliers in Maricopa County were surveyed to gather information on the volume 

of natural gas distributed, by user category, within the county in 2008. Area-source industrial 

natural gas usage for the county is based on the reported total volume of natural gas sold to 

industrial sources, minus natural gas used by industrial point sources:

County area-source = Total reported industrial – Industrial point source

industrial natural gas usage natural gas sales natural gas usage

= 8,576.57 MMCF – 516.15 MMCF

= 8,060.42 MMCF

Natural gas is used for both external combustions (boilers and heaters) and internal combustion 

(generators), each of which have different emission factors. Thus the area-source natural gas 

usage derived above must be divided between these two categories. This apportionment was 

based on the percentages of external and internal natural gas combustion reported by all industrial area sources in 2008.

Annual emissions for the county and the PM10 nonattainment area were calculated by multiplying natural gas usage by the respective AP-42 emission factors for external and internal combustion, as in this example for PM10 emissions from external natural gas combustion:

PM10 emissions from = External industrial natural × PM10 emission factor for ÷ 2,000 lbs/ton

external natural gas gas usage (MMCF) external natural gas 

combustion combustion (lb/MMCF)

= 7,934.68 × 7.6 ÷ 2,000

= 30.15 tons PM10/yr

Table 3.2–2. Natural gas usage, emission factors, and annual emissions from area-source industrial natural 

gas combustion, by combustion type.

Type of 

Combustion 

% of 

total

Natural gas 

use (MMCF)

Emission factors (lb/MMCF) Annual emissions (tons/yr)

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

External 98.44 7,934.68 7.6 7.6 100 0.6 3.2 30.15 30.15 396.73 2.38 12.70

Internal 1.56 125.74 10.0 10.0 2840 0.6 n/a 0.63 0.63 178.55 0.04 n/a

Total: 100.00 8,060.43 30.78 30.78 575.29 2.42 12.70

Typical daily emissions for the county were calculated by dividing annual emissions by the 

number of days that activity occurs throughout the year:

Typical daily PM10 emissions = Annual PM10 emissions ÷ (days/week × wks/yr) × 2,000 lbs/ton

from industrial natural gas (lbs/day)

= 30.78 tons/yr ÷ (6 × 52) × 2,000

= 197.3 lbs PM10/day
2008 Maricopa Co. PM10 Emission Inventory 22 June 2011 

Annual and typical daily emissions within the PM10 nonattainment area were calculated by 

applying the ratio of industrial employment in the nonattainment area to county-level emission 

calculations. (See Section 1.5.1 for a discussion of the employment data used).

Emissions from area-source = Annual county PM10 × NAA:County industrial employment ratio

industrial natural gas combustion emissions (tons/yr) in the PM10 NAA

= 30.78 × 0.9974

= 30.70 tons PM10/yr

Table 3.2–3. Annual and typical daily emissions from area-source industrial natural gas combustion.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Maricopa County 30.78 30.78 575.29 2.42 12.70 197.3 197.3 3,687.7 15.5 81.4

PM10 NAA 30.70 30.70 573.79 2.41 12.66 196.8 196.8 3,678.2 15.5 81.2

3.2.2 Industrial fuel oil

Area-source emissions from industrial fuel oil combustion were calculated by a multi-step 

process which allocates Arizona state-level industrial fuel oil sales as reported by the U.S. 

Department of Energy, Energy Information Administration (US DOE, 2010a) to Maricopa 

County.

To derive industrial fuel oil usage in Maricopa County, reported Arizona state-level sales of 

high-sulfur diesel for 2008 are first subtracted from Arizona state-level total industrial fuel oil 

sales, as it is presumed that no high-sulfur diesel fuel is used in Maricopa County due to local air 

quality regulations and market conditions.

State industrial fuel oil sales = Reported state total – Reported state high-sulfur diesel sales

other than high-sulfur diesel industrial fuel oil sales

(in thousand gallons, or Mgal)

= 137,044 Mgal – 224 Mgal

= 136,820 Mgal/yr

Arizona state industrial fuel oil sales (less high-sulfur diesel fuel) are then multiplied by the ratio 

of industrial employment in Maricopa County to Arizona State (0.70), as determined by data 

from the US Census Bureau (2010a) to estimate annual Maricopa County-level industrial fuel oil 

sales, as follows:

Maricopa County = Arizona state industrial fuel × Maricopa County:State

industrial fuel oil sales oil sales less high-sulfur diesel industrial employment ratio

= 136,820 Mgal × 0.7007

= 95,869.77 Mgal/yr

To avoid double-counting, industrial fuel oil use attributable to stationary point sources 

(addressed in Chapter 2) and nonroad mobile sources (addressed in Chapter 4) are subtracted 

from County industrial fuel oil sales to estimate county fuel oil usage by area sources:
2008 Maricopa Co. PM10 Emission Inventory 23 June 2011 

Maricopa County area = Maricopa County – Fuel oil used by industrial – Fuel oil used by industrial

source fuel oil sales industrial fuel oil sales nonroad mobile equipment stationary point sources

= 95,869.77 Mgal – 11,596.87 Mgal – 136.82 Mgal

= 84,136.09 Mgal/yr

Industrial fuel oil is used for both external combustions (boilers, heaters) and internal combustion (generators), each of which have different emission factors. Thus the area-source industrial 

fuel oil sales derived above must be apportioned between these two categories. This apportionment was based on the percentages of external and internal fuel oil combustion reported by all 

industrial area sources surveyed in 2008 (shown in Table 3.2–4 below).

Annual emissions for the county and the PM10 nonattainment area were calculated by multiplying industrial fuel oil sales by the respective AP-42 emission factors for external and internal 

combustion, as in this example for PM10 emissions from external fuel oil combustion:

Annual PM10 emissions = External industrial fuel × PM10 emission factor for external ÷ 2,000 lbs/ton

from external industrial oil sales (Mgal) fuel oil combustion (lb/Mgal)

fuel oil combustion

= 65,634.56 × 2 ÷ 2,000

= 65.63 tons PM10/yr

Table 3.2–4. Emission factors and annual emissions from area-source industrial fuel oil combustion, by 

combustion type.

Combustion 

type

% of 

total

Annual 

sales 

(Mgal)

Emission factors (lb/Mgal) Annual emissions (tons/yr)

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

External 78.01 65,634.56 2.0 2.0 24 7.39 0.8 65.63 65.63 787.61 242.36 26.25

Internal 21.99 18,501.53 42.5 42.5 604 39.70 – 393.16 393.16 5,587.46 367.26 n/a

Totals: 100.00 84,136.09 458.79 458.79 6,375.08 609.61 26.25

Typical daily emissions for the county were calculated by dividing annual emissions by the 

number of days during which activity occurs throughout the year, as recommended by EIIP 

guidance (US EPA, 2001a):

Typical daily PM10 emissions = Annual PM10 emissions ÷ (days/week × wks/yr) × 2,000 lbs/ton

from industrial fuel oil (tons/yr)

= 458.79 ÷ (6 × 52) × 2,000

= 2,941.0 lbs PM10/day

Annual and typical daily emissions in the PM10 nonattainment area were calculated by applying 

the ratio of industrial employment in the nonattainment area to county-level emission 

calculations. (See Section 1.5.1 for a discussion of the employment data used).

PM10 NAA emissions from area = Annual county × NAA:County industrial employment ratio

source industrial fuel oil combustion PM10 emissions

= 458.79 tons/yr × 0.9974

= 457.60 tons PM10/yr
2008 Maricopa Co. PM10 Emission Inventory 24 June 2011 

Table 3.2–5. Annual and typical daily emissions from area-source industrial fuel oil combustion.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Maricopa County 458.79 458.79 6,375.08 609.61 26.25 2,941.0 2,941.0 40,865.9 3,907.8 168.3

PM10 NAA 457.60 457.60 6,358.50 608.03 26.19 2,933.3 2,933.3 40,759.6 3,897.6 167.9

3.2.3 Commercial/institutional natural gas

All natural gas suppliers in Maricopa County were surveyed to gather information on the volume 

of natural gas distributed, by user category, within the county in 2008. Area-source commercial 

and institutional (C&I) natural gas usage for the county is based on the reported total volume of 

natural gas sold to C&I sources, minus natural gas used by C&I point sources:

County area-source C&I = Reported C&I natural gas sales – C&I point source natural gas usage

natural gas usage

= 17,503.31 MMCF – 84.08 MMCF

= 17,419.23 MMCF

Natural gas is used for both external combustion (boilers, heaters) and internal combustion 

(generators), each of which have different emission factors. Thus the area-source natural gas 

usage derived above must be apportioned between these two categories. This apportionment was 

based on the percentages of external and internal natural gas combustion reported by all C&I 

area sources in 2008.

Annual emissions for the county were calculated by multiplying natural gas usage by the 

respective AP-42 emission factors for external and internal combustion, as in this example for 

PM10 emissions from external natural gas combustion:

Annual PM10 emissions = External C&I natural × PM10 emission factor for ÷ 2,000 lbs/ton

from external natural gas gas usage (MMCF) external natural gas 

combustion combustion (lb/MMCF)

= 17,130.07 × 7.6 ÷ 2,000

= 65.09 tons PM10/yr

Table 3.2–6. Emission factors and annual emissions from area-source commercial/institutional natural gas 

combustion, by combustion type.

Combustion 

type

% of 

total

C&I natural 

gas usage 

(MMCF)

Emission factors (lb/MMCF) Annual emissions (tons/yr)

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

External 98.34 17,130.07 7.6 7.6 100 0.6 0.49 65.09 65.09 856.50 5.14 4.20

Internal 1.66 289.16 10.0 10.0 2840 0.6 n/a 1.45 1.45 410.61 0.09 n/a

Total: 100.00 17,419.23 66.54 66.54 1,267.11 5.23 4.20

Typical daily emissions for the county were calculated by dividing annual emissions by the 

number of days that activity occurs throughout the year:

Typical daily PM10 emissions = Annual PM10 emissions ÷ (days/week × wks/yr) × 2,000 lbs/ton

from comm./inst. natural gas (tons/yr)

= 66.54 ÷ (6 × 52) × 2,000

= 426.54 lbs/day
2008 Maricopa Co. PM10 Emission Inventory 25 June 2011 

Annual and typical daily emissions within the PM10 nonattainment area were calculated by 

applying the combined ratio of retail, office, public and other employment in the nonattainment 

area to county-level emission calculations. (See Section 1.5.1 for a discussion of the employment data used).

PM10 NAA emissions from area-source = Annual county PM10 emissions × NAA:County C&I employment ratio

comm./inst. natural gas combustion (tons/yr)

= 66.54 × 0.9949

= 66.20 tons PM10/yr

Table 3.2–7. Annual and typical daily emissions from area-source commercial/institutional natural gas 

combustion.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Maricopa County 66.54 66.54 1,267.11 5.23 4.20 426.5 426.5 8,122.5 33.5 26.9

PM10 NAA 66.20 66.20 1,260.65 5.20 4.18 424.4 424.4 8,081.1 33.3 26.8

3.2.4 Commercial/institutional fuel oil

Area-source emissions from commercial and institutional (C&I) fuel oil combustion were 

calculated by a multi-step process of allocating Arizona state-level C&I fuel oil sales as reported 

by the U.S. Department of Energy, Energy Information Administration (US DOE, 2010b) to 

Maricopa County.

To derive commercial/institutional fuel oil usage in Maricopa County, reported Arizona statelevel sales of high-sulfur diesel for 2008 are first subtracted from Arizona state-level total C&I 

fuel oil sales, as it is presumed that no high-sulfur diesel fuel is used in Maricopa County due to 

local clean air act requirements and market conditions.

State C&I fuel oil sales = Reported state total – Reported state high-sulfur diesel sales

other than high-sulfur diesel C&I fuel oil sales

(in thousand gallons, or Mgal)

= 47,586 Mgal – 367 Mgal

= 47,219 Mgal/yr

Arizona state commercial/institutional fuel oil sales (less high-sulfur diesel fuel) are then 

multiplied by the ratio of C&I employment in Maricopa County to Arizona state (0.80), as 

determined by data from the US Census Bureau (2010a) to estimate annual Maricopa Countylevel commercial/institutional fuel oil sales, as follows:

Maricopa County = Arizona state C&I fuel oil × Maricopa County:state commercial/

C&I fuel oil sales sales (less high-sulfur diesel) institutional employment ratio

= 47,219 Mgal × 0.7973

= 37,647.71 Mgal/yr

To avoid double-counting, C&I fuel oil use attributable to stationary point sources (addressed in 

Chapter 2) and nonroad mobile sources (addressed in Chapter 4) are subtracted from County 

C&I fuel oil sales to estimate county fuel oil usage used by area sources:
2008 Maricopa Co. PM10 Emission Inventory 26 June 2011 

Annual Maricopa County = Maricopa County – Fuel oil used by C&I – Fuel oil used by C&I

commercial/institutional C&I fuel oil sales nonroad mobile equipment stationary point sources

area-source fuel oil sales

= 37,647.71 Mgal – 7,291.00 Mgal – 3.94 Mgal

= 30,352.77 Mgal/yr

Fuel oil is used for both external combustions (boilers, heaters) and internal combustion 

(generators), each of which have different emission factors. Thus the area-source C&I fuel oil 

sales derived above must be apportioned between these two categories. This apportionment was 

based on the percentages of external and internal fuel oil combustion reported by all commercial 

and institutional area sources surveyed in 2008 (shown in Table 3.2–8 below).

Annual emissions for the county were calculated by multiplying comm./inst. fuel oil sales by the 

respective AP-42 emission factors for external and internal combustion, as in this example for 

PM10 emissions from external fuel oil combustion:

Annual PM10 emissions from = External C&I fuel oil × PM10 emission factor for external ÷ 2,000 lbs/ton

external fuel oil combustion sales (Mgal) fuel oil combustion (lb/Mgal)

= 20,321.18 × 1.08 ÷ 2,000

= 10.97 tons PM10/yr

Table 3.2–8. Emission factors and annual emissions from area-source commercial/institutional fuel oil 

combustion, by combustion type.

Combustion 

type

% of 

total

C&I fuel oil 

sales (Mgal)

Emission factors (lb/Mgal) Annual emissions (tons/yr)

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

External 66.95 20,321.18 1.08 1.08 24 7.1 0.8 10.97 10.97 243.85 72.14 8.13

Internal 33.05 10,031.59 42.5 42.5 604 39.7 n/a 213.17 213.17 3,029.54 199.13 n/a

Total: 100.00 30,352.78 224.14 224.14 3,273.40 271.27 8.13

Typical daily emissions for the county were calculated by dividing annual emissions by the 

number of days activity occurs throughout the year, as recommended by EIIP guidance (US 

EPA, 2001a):

Typical daily PM10 emissions = Annual PM10 emissions ÷ (days/week × wks/yr) × 2,000 lbs/ton

from C&I fuel oil combustion (tons/yr)

= 224.14 ÷ (6 × 52) × 2,000

= 1,436.8 lbs/day

Annual and typical daily emissions within the PM10 nonattainment area were calculated by 

applying the combined ratio of retail, public, office and other employment in the nonattainment 

area to county-level emission calculations. (See Section 1.5.1 for a discussion of the 

employment data used).

PM10 NAA emissions from area = Annual county PM10 × NAA:County C&I employment ratio

source C&I fuel oil combustion emissions (tons/yr)

= 224.14 × 0.9949

= 223.00 tons PM10/yr
2008 Maricopa Co. PM10 Emission Inventory 27 June 2011 

Table 3.2–9. Annual and typical daily emissions from area-source commercial/institutional fuel oil 

combustion.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Maricopa County 224.14 224.14 3,273.40 271.27 8.13 1,436.8 1,436.8 20,983.3 1,738.9 52.1

PM10 NAA 223.00 223.00 3,256.70 269.88 8.09 1,429.5 1,429.5 20,876.3 1,730.0 51.8

3.2.5 Residential natural gas

All natural gas suppliers in Maricopa County were surveyed to gather information on the volume 

of natural gas sold, by user category, within the county. Annual emissions from residential 

natural gas combustion emissions were calculated by multiplying residential natural gas sales by 

emission factors for residential natural gas combustion summarized in the table below (US EPA, 

1998a), as follows:

Table 3.2–10. Residential natural gas combustion emission factors.

Emission Factors (lb/MMCF)

PM10 PM2.5 NOx SOx

7.6 7.6 94 0.6

Annual PM10 emissions = Annual sales of residential × PM10 emission factor for ÷ 2,000 lbs/ton

from residential natural natural gas (MMCF) residential natural gas (lbs/MMCF)

gas combustion

= 16,251.29 × 7.6 ÷ 2,000

= 61.75 tons PM10/yr

Typical daily emissions were calculated by dividing annual emissions by the number of days 

(366) that activity occurs for residential natural gas combustion, as follows:

Typical daily PM10 emissions from = Annual PM10 emissions × 2,000 lbs/ton ÷ days/yr 

residential natural gas combustion

= 61.75 tons/yr × 2, 000 ÷ 366

= 337.4 lbs PM10/day

Annual and typical daily residential natural gas emissions in the PM10 nonattainment area were 

calculated by multiplying county-level emissions by the percentage of total residential population in the PM10 nonattainment area as follows:

Annual PM10 emissions = Annual PM10 emissions × % of County residential population in the NAA

from residential natural gas in Maricopa County

combustion in the NAA

= 61.75 × 99.96%

= 61.73 tons PM10/yr

Table 3.2–11. Annual and typical daily emissions from residential natural gas combustion.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NOx SOx PM10 PM2.5 NOx SOx

Maricopa County 61.75 61.75 763.81 4.88 337.5 337.5 4,173.8 26.6

PM10 NAA 61.73 61.73 763.51 4.87 337.3 337.3 4,172.2 26.6
2008 Maricopa Co. PM10 Emission Inventory 28 June 2011 

3.2.6 Residential wood combustion

Area-source emissions from residential wood combustion were calculated based on the amount 

of wood burned in fireplaces and woodstoves in Maricopa County, as recommended by EIIP 

guidance (US EPA, 2001b). Residential wood combustion in the county is estimated by multiplying data on statewide residential wood combustion usage from the US Department of Energy 

(US DOE, 2010c) by the ratio of county to state households that report use of wood for heating

from the US Census Bureau (2010b). The latest available data on residential wood use for 

household heating from the US Department of Energy is for the calendar year 2007. Since all 

fireplaces in homes constructed since 1999 are required by Arizona statute to be clean-burning, it 

is assumed that these new homes have negligible emissions. Thus, year 2007 data is assumed to 

be representative of 2008 emissions.

Maricopa County residential = Arizona residential × Ratio of county:state households

wood usage (cords/yr) wood usage (cords/yr) using wood for heat

= 651,000 × 1,457 / 44,330

= 21,397 cords/yr

To calculate emissions, the amount of wood used is converted to tons by multiplying cords by 

the number of cubic feet of wood in a cord and by the density of the wood used (US EPA, 

2001b). Wood density is determined by weighted average of types of wood used for residential 

combustion in Maricopa County, provided by the US Forest Service (USFS, 1993).

County residential = County wood × avg. ft3 wood/cord × Wood density (lbs/ ft3) ÷ 2,000 lbs/ton

wood usage (tons/yr) usage (cords)

= 21,397 × 79 × 31.57 ÷ 2,000

= 26,682 tons

Annual emissions from residential wood combustion were calculated by multiplying the tons of 

wood used by the PM10 emission factor for residential woodstoves and fireplaces from Table 

2.4 –1 of US EPA (2001b).

Annual PM10 emissions from residential = Residential wood usage × PM10 emission factor ÷ 2,000 lbs/ton

wood combustion (tons/yr) (tons) (lbs/ton)

= 26,682 × 34.6 ÷ 2,000

= 461.59 tons PM10/yr

Table 3.2–12. Annual wood usage, emission factors, and annual emissions from residential wood combustion.

Residential wood 

usage (tons/yr)

Emission factors (lbs/ton) Annual emissions (tons/yr)

PM10 PM2.5* NOx SOx PM10 PM2.5* NOx SOx

26,681.76 34.6 32.2 2.6 0.4 461.59 429.28 34.69 5.34

*PM2.5 is assumed to be 93% of PM10 (Houck and Tiegs, 1998).

Typical daily emissions were calculated by apportioning wood burning activity based on heating 

degree days (i.e., the number of degrees per day that the daily average temperature is below 

65°F). Data provided by Arizona Department of Commerce (ADOC, 2010) indicated that there 

were five months (April, plus June–September, totaling 152 days) in 2008 where no heating 

degree days were recorded. Assuming that no wood burning activity took place during those 

months, it is assumed that all residential wood burning occurred during the remaining 213 days 
2008 Maricopa Co. PM10 Emission Inventory 29 June 2011 

of the year. Thus, typical daily emissions were calculated by dividing annual emissions by the 

number of days residential wood burning occurred, as follows:

Typical daily PM10 emissions = Annual PM10 emissions × 2,000 lbs/ton ÷ no. days wood burning occurred

from residential wood combustion (tons/yr)

(lbs/day)

= 461.59 × 2,000 ÷ 213

= 4,334.2 lbs PM10/day

Annual and typical daily emissions within the PM10 nonattainment area (presented in Table 3.2–

13) were calculated by multiplying county totals by the ratio of residential population in the 

nonattainment area to the residential population in the county. See Section 1.5.1 for a further 

discussion of the population used.

Annual emissions from residential wood = County annual emissions × NAA:county residential population ratio

combustion in the PM10 NAA (tons/yr)

= 461.59 × 0.9996

= 461.41 tons PM10/yr

Table 3.2–13. Annual and typical daily emissions from residential wood combustion.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NOx SOx PM10 PM2.5 NOx SOx

Maricopa County 461.59 429.28 34.69 5.34 4,334.2 4,030.8 325.7 50.1

PM10 NAA 461.41 429.11 34.67 5.33 4,332.5 4,029.2 325.6 50.1

3.2.7 Residential fuel oil

Emissions from residential fuel oil use were calculated using an approach similar to that used for 

residential wood combustion described in Section 3.2.6. County-level residential fuel oil use 

was derived from statewide totals (US EIA, 2010) using the ratio of county to state households 

that report fuel oil use from the US Census Bureau (2010c):

Maricopa County residential = Arizona residential × Ratio of county:state households

fuel oil usage (Mgal/yr) fuel oil use (Mgal/yr) reporting fuel oil use

= 91 × 573 / 1,881

= 27.72 Mgal/yr

Annual and daily emissions were calculated using AP-42 emission factors (shown below in 

Table 3.2–14) and data on heating degree days and residential housing units described in Section 

3.2.6. Annual and daily emissions are shown below in Table 3–2.14.

Table 3.2–14. Annual and typical daily emissions from residential fuel oil combustion.

Geographic area

Emission factors

(lb/Mgal)

Annual emissions

(tons/yr)

Typical daily emissions 

(lbs/day)

PM10 PM2.5 NOx SOx PM10 PM2.5 NOx SOx PM10 PM2.5 NOx SOx

Maricopa County 0.4 0.4 18 7.1 0.01 0.01 0.25 0.10 0.1 0.1 2.3 0.9

PM10 NAA 0.4 0.4 18 7.1 0.01 0.01 0.25 0.10 0.1 0.1 2.3 0.9
2008 Maricopa Co. PM10 Emission Inventory 30 June 2011 

3.2.8 Summary of all area-source fuel combustion

Tables 3.2–15 and 3.2–16 provide a summary of annual and typical daily emissions from all fuel 

combustion, for Maricopa County and the PM10 nonattainment area, respectively.

Table 3.2–15. Annual and typical daily emissions from area-source fuel combustion in Maricopa County.

Fuel combustion type

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Industrial natural gas 30.78 30.78 575.29 2.42 12.70 197.3 197.3 3,687.7 15.5 81.4

Industrial fuel oil 458.79 458.79 6,375.08 609.61 26.25 2,941.0 2,941.0 40,865.9 3,907.8 168.3

Comm./inst. natural gas 66.54 66.54 1,267.11 5.23 4.20 426.5 426.5 8,122.5 33.5 26.9

Comm./inst. fuel oil 224.14 224.14 3,273.40 271.27 8.13 1,436.8 1,436.8 20,983.3 1,738.9 52.1

Residential natural gas 61.75 61.75 763.81 4.88 337.5 337.5 4,173.8 26.6

Residential wood 461.59 429.28 34.69 5.34 4,334.2 4,030.8 325.7 50.1

Residential fuel oil 0.01 0.01 0.25 0.10 0.1 0.1 2.3 0.9

Total: 1,303.61 1,271.30 12,289.62 898.83 51.27 9,673.4 9,370.0 78,161.3 5,773.3 328.7

Table 3.2–16. Annual and typical daily emissions from all area-source fuel combustion for the PM10 NAA.

Fuel combustion type

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Industrial natural gas 30.70 30.70 573.79 2.41 12.66 196.8 196.8 3,678.2 15.5 81.2

Industrial fuel oil 457.60 457.60 6,358.50 608.03 26.19 2,933.3 2,933.3 40,759.6 3,897.6 167.9

Comm./inst. natural gas 66.20 66.20 1,260.65 5.20 4.18 424.4 424.4 8,081.1 33.3 26.8

Comm./inst. fuel oil 223.00 223.00 3,256.70 269.88 8.09 1,429.5 1,429.5 20,876.3 1,730.0 51.8

Residential natural gas 61.73 61.73 763.51 4.87 337.3 337.3 4,172.2 26.6

Residential wood 461.41 429.11 34.67 5.33 4,332.5 4,029.2 325.6 50.1

Residential fuel oil 0.01 0.01 0.25 0.10 0.1 0.1 2.3 0.9

Total: 1,300.65 1,268.35 12,248.07 895.83 51.11 9,653.8 9,350.6 77,895.2 5,754.1 327.6

3.3 Industrial processes

3.3.1 Chemical manufacturing

Emissions from area-source chemical manufacturing were calculated by the “scaling up” method 

as described in EPA emission inventory guidance (US EPA, 2001a). This method combines 

detailed emissions data from a subset of sources, and county-level employment data from the US 

Census Bureau (2010a) to develop a per-employee emission factor that is then used to estimate 

emissions from all sources in an industry category.

The most recent data from the US Census Bureau’s County Business Patterns (CBP) for 2007 

employment were used. Table 3.3–1 shows the NAICS codes and employment data used to 

calculate emissions from chemical manufacturing.

Table 3.3–1. NAICS codes and descriptions for chemical manufacturing.

NAICS 

Code Description

US Census 

employment data 

325 Chemical Manufacturing 3,930

42469 Other Chemical and Allied Products Merchant Wholesalers 1,093

424910 Farm Supplies Merchant Wholesalers 229

33312 Construction Machinery Manufacturing 212

Total: 5,464
2008 Maricopa Co. PM10 Emission Inventory 31 June 2011 

There were no point sources in this category. Area-source employment estimate were used to 

“scale up” emissions reported from those facilities surveyed in 2008 as follows:

Area-source PM10 = Emissions from surveyed area sources

emissions from Employment at surveyed area sources

× Total area-source employment

chemical mfg.

= 35.71 tons of PM10/yr

1,041 employees

× 5,464 employees

= 187.43 tons PM10/yr

Typical daily emissions were calculated in the same method as annual emissions, only using 

surveyed daily emissions instead of annual totals. Annual and typical daily emissions for the 

PM10 nonattainment area were calculated by multiplying the Maricopa County emission totals by 

the percentage industrial employment within the nonattainment area. (See Section 1.5.1 for a 

discussion of the employment data used.)

PM10 emissions from area-source = Annual Maricopa County emissions × NAA:county ratio of

chemical mfg. in the PM10 NAA (tons/yr) (tons/yr) industrial employment

= 187.43 × 0.9974

= 186.94 tons PM10/yr

Table 3.3–2 summarizes annual and typical daily emissions from chemical manufacturing in 

both Maricopa County and the PM10 nonattainment area.

Table 3.3–2. Annual and typical daily emissions from area-source chemical manufacturing.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NOx SOx NHx PM10 PM2.5 NOx SOx NHx

Maricopa County 187.43 151.42 0.00 0.34 0.03 1,445.8 1,164.5 0.0 2.6 0.9

PM10 NAA 186.94 151.03 0.00 0.34 0.03 1,442.0 1,161.5 0.0 2.6 0.9

3.3.2 Food and kindred products

3.3.2.1 Commercial cooking

Emissions from commercial cooking were estimated for five types of commercial cooking equipment using EPA methodology (US EPA, 2006a). The equipment types include: chain-driven 

charbroilers, under-fired charbroilers, deep-fat fryers, flat griddles, and clamshell griddles. 

EPA’s methodology estimates commercial cooking activity rates for restaurants with each type 

of cooking equipment (ethnic, family, fast food, seafood, and steak & barbeque) based on an 

average number of equipment pieces in each restaurant type, and also the and average quantity of 

meat cooked on each type of equipment per week (steak, hamburger, poultry, pork, and seafood). 

The estimates number of restaurants in Maricopa County for the five restaurant types was 

obtained from a commercial database (www.selectoryonline.com) and is shown in Table 3.3–3.
2008 Maricopa Co. PM10 Emission Inventory 32 June 2011 

Table 3.3–3. Number of Maricopa County restaurants, by restaurant type.

Restaurant Type No. of restaurants

Ethnic food 907

Fast food 1,068

Family 253

Seafood 37

Steak and barbecue 75

All restaurants: 2,340

Using EPA’s emissions estimation methodology (US EPA, 2006a), commercial cooking activity 

data were estimated by first multiplying the county number of restaurants that use commercial 

cooking equipment in each category (ethnic, fast food, family, seafood, and steak and barbeque) 

by the percentage of restaurants with each type of cooking equipment (Table 3.3–4).

Number of ethnic food = Number of ethnic food × % ethnic food restaurants

restaurants with under- restaurants in Maricopa County with underfired charbroilers

fired charbroilers

= 907 × 47.5%

= 431

Table 3.3–4. Percentages of restaurants with each type of cooking equipment.

Restaurant Type

Chain-driven 

Charbroilers

Underfired 

Charbroilers

Deep Fat 

Fryers Flat Griddles

Clamshell 

Griddles

Ethnic 3.5% 47.5% 81.9% 62.7% 4.0%

Family 10.1% 60.9% 91.4% 82.9% 1.4%

Fast Food 18.6% 30.8% 96.8% 51.9% 14.7%

Seafood 0.0% 52.6% 100.0% 36.8% 10.5%

Steak and Barbeque 6.9% 55.2% 82.8% 89.7% 0.0%

The resulting product was then multiplied by the average number of equipment pieces by 

restaurant type (shown in Table 3.3–5) to derive an estimate of the total number of each cooking 

equipment type in Maricopa County restaurants (Table 3.3–6).

Table 3.3–5. Average number of equipment pieces per restaurant, by type.

Restaurant Type

Chain-driven 

Charbroilers

Underfired 

Charbroilers

Deep Fat 

Fryers Flat Griddles

Clamshell 

Griddles

Ethnic 1.62 1.54 1.63 1.88 1.80

Family 1.71 1.29 2.34 2.03 —

Fast Food 1.07 1.58 3.10 1.43 2.09

Seafood — 1.10 2.47 1.11 1.50

Steak and Barbeque — 1.63 2.42 1.35 —

Number of underfired charbroilers = number of ethnic food restaurants × average number of underfired charat ethnic food restaurants with underfired charbroilers broilers per ethnic food restaurant

= 431 × 1.54

= 664
2008 Maricopa Co. PM10 Emission Inventory 33 June 2011 

Table 3.3–6. Total pieces of cooking equipment, by restaurant type.

Restaurant Type

Chain-driven 

Charbroilers

Underfired 

Charbroilers

Deep Fat 

Fryers Flat Griddles

Clamshell 

Griddles

Ethnic 51.43 663.47 1,210.82 1,069.14 65.30

Family 43.70 198.76 541.11 425.77 —

Fast Food 212.55 519.73 3204.85 792.64 328.12

Seafood — 21.41 91.39 15.11 5.83

Steak and Barbeque — 67.48 150.28 90.82 —

Totals: 307.68 1,470.85 5,198.45 2,393.47 399.25

The total number of each type of cooking equipment is then multiplied by average pounds of 

meat cooked on each type of equipment per week (Table 3.3–7) to derive the total estimate of the 

amount of meat cooked in Maricopa County each week (Table 3.3–8).

Table 3.3–7. Meat cooked weekly per restaurant (in pounds), by equipment type.

Type of Meat

Chain-driven 

Charbroilers

Underfired 

Charbroilers

Deep Fat 

Fryers Flat Griddles

Clamshell

Griddles

Steak 236 180 181 166 94

Hamburger 798 270 274 362 1314

Poultry, with Skin 147 144 365 88 113

Poultry, Skinless 266 179 208 111 108

Pork 57.6 148 58.6 112 118

Seafood 119 143 159 92.1 632

Other 0 41.5 274 57.5 0

Total steak cooked on all under- = Steak cooked on each under- × Total number of under-fired ÷ 2,000 lbs/ton

fired charbroilers (tons/wk) fired charbroiler (lbs/wk) charbroilers at all restaurants

= 180 lbs/ week × 1,470.85 ÷ 2,000 

= 132.38 tons/week

Table 3.3–8. Total meat cooked weekly (in tons), by equipment type.

Type of Meat

Chain-driven 

Charbroilers

Underfired 

Charbroilers

Deep Fat 

Fryers Flat Griddles

Clamshell 

Griddles

Steak 36.31 132.38 470.46 198.66 18.76

Hamburger 122.76 198.56 712.19 433.22 262.31

Poultry, with Skin 22.61 105.90 948.72 105.31 22.56

Poultry, Skinless 40.92 131.64 540.64 132.84 21.56

Pork 8.86 108.84 152.31 134.03 23.56

Seafood 18.31 105.17 413.28 110.22 126.16

Other 0.00 30.52 712.19 68.81 0.00 

Totals: 249.77 813.01 3,949.78 1,183.09 474.91

The total amount of meat cooked in Maricopa County restaurants weekly (Table 3.3–8) was then 

multiplied by the appropriate emission factor from Table 3.3–9 (US EPA, 2006a). The results 

were then summed to estimate annual emissions for each type of cooking equipment, shown in 

Table 3.3–10. Commercial cooking is assumed to occur uniformly throughout both the week 

(i.e., 7 days/week) and year.
2008 Maricopa Co. PM10 Emission Inventory 34 June 2011 

Table 3.3–9. PM10 and PM2.5 emission factors for commercial cooking equipment, by device type.

Emission Factor (lb/ton)

Equipment type PM10 PM2.5

Chain-driven charbroilers 15.996058 15.506208

Underfired charbroilers 32.666124 31.577929

Deep fat fryers 0.00 0.00

Flat griddle fryers 5.922517 4.501113

Clamshell griddles 1.006137 0.852257

Table 3.3–10. Annual and daily emissions from commercial cooking equipment in Maricopa County.

Equipment type

Annual Emissions (tons/yr) Typical Daily Emissions (lbs/day)

PM10 PM2.5 PM10 PM2.5

Chain-driven charbroilers 103.88 100.70 570.8 553.3

Underfired charbroilers 690.51 667.51 3,794.0 3,667.6

Deep fat fryers 0.00 0.00 0.0 0.0

Flat griddles 182.18 138.46 1,001.0 760.7

Clamshell griddles 12.42 10.52 68.3 57.8

Totals: 988.99 917.18 5,434.0 5,039.5

Annual and typical daily emissions for the PM10 nonattainment area were calculated by 

multiplying the county totals by the ratio of total population in the nonattainment area to the total 

population in the county (100.41%) (See Section 1.5.1 for a discussion of the population data 

used.) Table 3.3–11 summarizes the annual and typical daily emissions from commercial 

cooking for the PM10 NAA.

Table 3.3–11. Annual and daily PM emissions from commercial cooking equipment in the PM10 NAA.

Equipment type

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

PM10 PM2.5 PM10 PM2.5

Chain-driven charbroilers 104.31 101.11 573.1 555.6 

Underfired charbroilers 693.34 670.24 3,809.6 3,682.6 

Deep fat fryers 0.00 0.00 - - 

Flat griddles 182.93 139.02 1,005.1 763.9 

Clamshell griddles 12.47 10.57 68.5 58.1 

Totals: 993.04 920.94 5,456.3 5,060.1 

3.3.2.2 Grain handling/processing

Annual emissions from area-source grain handling and processing operations were derived from 

annual emission reports submitted by permitted sources. It was assumed that there were no 

significant unpermitted sources within Maricopa County.

Typical daily emissions were calculated based on reported activity data (days per week) for each 

individual process, and then summed. Nearly all processes reported operating on either a 5- or 6-

day week. Annual and typical daily emissions for the PM10 nonattainment area were derived 

based on the location data of the individual facilities. Annual and typical daily emissions for 

both the County and the PM10 NAA are shown in Table 3.3–12.

Table 3.3–12. Annual and typical daily emissions from area-source grain handling and processing.

Geographic Area

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

PM10 PM2.5 PM10 PM2.5

Maricopa County 20.59 6.71 149.3 49.5

PM10 NAA 16.73 5.68 125.3 43.0
2008 Maricopa Co. PM10 Emission Inventory 35 June 2011 

3.3.2.3 Ammonia cold storage

Area-source emissions from ammonia cold storage are estimates of ammonia emissions from 

food and kindred products industrial sources that use ammonia for refrigeration of food products. 

Emission calculations are based on the number of employees in the food and kindred products 

industry classification (NAICS codes 311, 312) as reported by the 2007 County Business 

Patterns (US Census Bureau, 2010a). Annual emissions were calculated by multiplying 

employment numbers by the emission factor for ammonia cold storage as listed in Table 6-5 of 

“Development and Selection of Ammonia Emission Factors” (Battye et al., 1994) as follows:

Annual NH3 emissions = Number of employees × NH3 emission ÷ 2,000 lbs/ton

from ammonia cold in relevant industries factor (lb/employee-yr)

storage (tons/yr) (from CBP)

= 8,128 × 413 ÷ 2,000

= 1,678.43 tons NH3/yr

Typical daily emissions were calculated by dividing annual emissions by the number of days per 

year that activity occurred, as follows:

Typical daily = Annual emissions (tons/yr) × 2,000 lbs/ton ÷ (weeks/year × days/week)

NH3 emissions

(lbs/day)

= 1,678.43 × 2,000 ÷ (52 × 6)

= 10,759.2 lbs NH3/day

Annual and typical daily emissions for the PM10 nonattainment area (shown in Table 3.3–13 

below) were calculated by multiplying Maricopa County emissions by the ratio of County 

industrial employment that occurs in the PM10 nonattainment area. (See Section 1.5.1 for a more 

detailed discussion of the employment data used).

Annual NH3 emissions from = Annual county emissions (tons/yr) × NAA:County industrial employment ratio

ammonia cold storage in the

PM10 NAA (tons/yr)

= 1,678.43 × 0.9974

= 1,674.07 tons NH3/yr

Table 3.3–13. Annual and typical daily ammonia emissions from ammonia cold storage.

Geographic area Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Maricopa County 1,678.43 10,759.2

PM10 NAA 1,674.07 10,731.2

3.3.3 Secondary metal production

Annual emissions from secondary metal production facilities were derived from annual emission 

reports from permitted sources. As this category consists primarily of foundries, it was assumed 

that there were no significant unpermitted sources within Maricopa County. Since all facilities 

considered in this section are located within the PM10 nonattainment area, total emission values 

for the county and the PM10 NAA from area-source secondary metal production are equal. 

Annual and daily emissions are shown in Table 3.3–14.
2008 Maricopa Co. PM10 Emission Inventory 36 June 2011 

Table 3.3–14. Annual and typical daily emissions from secondary metal production.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Maricopa County 60.56 52.16 49.73 18.65 0.04 442.7 386.2 358.8 142.7 0.0

PM10 NAA 60.56 52.16 49.73 18.65 0.04 442.7 386.2 358.8 142.7 0.0

3.3.4 Non-metallic mineral processes

The primary contributors to this source category include concrete batch plants, ceramic clay and 

tile manufacturing, brick manufacturing, and gypsum mining. Emissions from this source were 

derived from annual emission reports from permitted facilities. Since all permitted facilities in 

this category were surveyed in 2008, it was assumed that there were no significant unpermitted 

sources within Maricopa County. Some portable concrete batch operations which operate within 

Maricopa County for only part of the year are issued air quality permits by the Arizona 

Department of Environmental Quality (ADEQ). All state-permitted portable sources are 

addressed in Section 3.3.11.

Typical daily emissions were calculated based on the operating schedule data reported by 

surveyed facilities. Annual and typical daily emissions for the PM10 nonattainment area were 

derived based on the location data of the individual facilities. County-permitted portable sources 

with no location data were assumed to operate within the PM10 nonattainment area as a 

conservative estimate.

Table 3.3–15 summarizes annual and typical daily emissions from non-metallic mineral 

processing activities in both Maricopa County and the PM10 nonattainment area.

Table 3.3–15. Annual and typical daily emissions from area-source non-metallic mineral products.

Geographic area

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

PM10 PM2.5 PM10 PM2.5

Maricopa County 192.82 95.47 1,337.7 659.3

PM10 NAA 187.73 91.92 1,302.8 635.6

3.3.5 Mining and quarrying

Annual emissions from area-source mining and quarrying (sand and gravel) operations were 

derived from annual emission reports submitted by permitted sources. It was assumed that there 

were no significant unpermitted sources within Maricopa County. Some portable mining and 

quarrying operations which operate within Maricopa County for only part of the year are issued 

air quality permits by the Arizona Department of Environmental Quality (ADEQ). All statepermitted portable sources are addressed in Section 3.3.11.

Typical daily emissions were calculated based on reported activity data (days per week) for each 

individual process, and then summed. Nearly all processes reported operating on either a 5- or 6-

day week. Emissions within the PM10 nonattainment area were identified using information on 

the location of each permitted facility. County-permitted portable sources with no location data 

were assumed to operate within the PM10 nonattainment area as a conservative estimate. Annual 

and daily emissions are shown in Table 3.3–16.
2008 Maricopa Co. PM10 Emission Inventory 37 June 2011 

Table 3.3–16. Annual and typical daily emissions from area-source mining and quarrying operations.

Geographic Area

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

PM10 PM2.5 PM10 PM2.5

Maricopa County 181.01 55.20 1,239.2 362.6

PM10 NAA 156.60 46.81 1,075.7 307.2

3.3.6 Wood product manufacturing

Emissions from wood product manufacturing were calculated by the “scaling up” method as 

described in EPA emission inventory guidance (US EPA, 2001a). This method combines 

detailed emissions data from a subset of sources, and county-level employment data from the US 

Census Bureau (2010a) to estimate an annual per-employee emission factor that is then used to 

estimate emissions from all sources in an industry category.

The most recent employment estimates (for the year 2007) from the US Census Bureau’s County 

Business Patterns (CBP) were used. Table 3.3–17 shows the NAICS codes and employment 

estimates used to calculate emissions from wood product manufacturing.

Table 3.3–17. County-level employment estimates for wood product manufacturing, by NAICS code.

NAICS Code NAICS Code Description 2007 employment estimate 

321--- Wood products manufacturing 6,917

337--- Furniture and related products manufacturing 7,153

Total: 14,070

Since some larger facilities in this category are considered point sources, they have been 

included in the point source calculations presented earlier in Chapter 2. To avoid doublecounting, employment at point sources was subtracted from total employment as follows:

Total area-source = Total County employment – Employment reported from facilities

employment in for the sector reported as point sources

wood products

= 14,070 – 930

= 13,140 employees

Annual emissions for the entire wood product manufacturing sector were calculated by “scaling 

up” detailed area-source emissions reported from those facilities surveyed in 2008 as follows:

Total area-source = Emissions from surveyed area sources

emissions Employment at surveyed area sources

× Total area-source employment

Area-source PM10 = 102.99 tons PM10/yr

emissions from 6,229 employees

× 13,140 employees

wood products

= 217.26 tons PM10/yr

Typical daily emissions were calculated in the same method, using surveyed daily emissions 

estimates from the subset of surveyed area sources. From these County totals, emissions 

estimates for the PM10 nonattainment area were calculated by multiplying the County totals by 

the percentage of industrial employment within the nonattainment area. (See Section 1.5.1 for a

discussion of the employment data used.)
2008 Maricopa Co. PM10 Emission Inventory 38 June 2011 

PM10 emissions from area-source = Total County emissions × NAA:county ratio for

wood product manufacturing industrial employment

in the PM10 NAA (tons/yr)

= 217.26 tons/yr × 0.9974

= 216.69 tons PM10/yr

Table 3.3–18 summarizes annual and typical daily emissions from wood products manufacturing 

in both Maricopa County and the PM10 nonattainment area.

Table 3.3–18. Annual and typical daily emissions from area-source wood product manufacturing.

Geographic Area

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

PM10 PM2.5 PM10 PM2.5

Maricopa County 217.26 203.25 1,668.6 1,548.3

PM10 NAA 216.69 202.72 1,664.3 1,544.3

3.3.7 Rubber/plastics manufacturing

Emissions from area-source rubber and plastic manufacturing facilities were calculated by the 

“scaling up” method as described in EPA emission inventory guidance (US EPA, 2001a). This 

method combines detailed emissions data from a subset of sources, and county-level employment data from the US Census Bureau (2010a) to develop a per-employee emission factor that is 

then used to estimate emissions from all sources in an industry category. The most recent data 

from the US Census Bureau’s County Business Patterns (CBP) for 2007 employment were used. 

Where CBP employment estimates were presented as a range, the midpoint values were chosen 

for these calculations. Table 3.3–19 lists the NAICS codes and employment data used to 

calculate emissions from rubber and plastic manufacturing facilities.

Some facilities in this category are considered point sources, and have been addressed in Chapter 

2. To avoid double-counting, employment at point sources is subtracted from total employment 

as follows:

Total area-source employment = Total employment (from US – Employment at point sources

in rubber & plastic product Census’ County Business Patterns) (from annual emission reports)

manufacturing

= 11,380 – 896

= 10,484 employees

This area-source employment estimate is used to “scale up” emissions reported from those 

facilities surveyed in 2008 as follows:

Total area-source PM10 emissions = Emissions from surveyed area sources

from rubber/plastic product mfg. Employment at surveyed area sources

× Area-source employment

= 30.37 tons PM10/yr

2,256 employees

× 10,484 employees

= 140.94 tons PM10/yr
2008 Maricopa Co. PM10 Emission Inventory 39 June 2011 

Table 3.3–19. County-level employment estimates for rubber and plastic manufacturing, by NAICS code.

NAICS Code NAICS Code Description 2007 employment estimate 

32614 Polystyrene Foam Product Manufacturing 351

32619 Other Plastics Product Manufacturing 4,178

32622 Rubber & Plastics Hoses & Belting Manufacturing 60

33992 Sporting & Athletic Goods Manufacturing 1,750

42461 Plastics Materials & Basic Forms & Shapes Merchant 

Wholesalers

368

325211 Plastics Material & Resin Manufacturing 10

325520 Adhesive Manufacturing 123

325991 Custom Compounding of Purchased Resins 194

326113 Unlaminated Plastics Film & Sheet (except Packaging) Mfg. 60

326122 Plastics Pipe & Pipe Fitting Manufacturing 144

326140 Polystyrene Foam Product Manufacturing 351

326160 Plastics Bottle Manufacturing 175

326199 All Other Plastics Product Manufacturing 175

326212 Tire Retreading 42

326299 All Other Rubber Product Manufacturing 71

327991 Cut Stone & Stone Product Manufacturing 583

332913 Plumbing Fixture Fitting & Trim Manufacturing 10

336612 Boat Building 53

337920 Blind & Shade Manufacturing 286

339113 Surgical Appliance & Supplies Manufacturing 88

339115 Ophthalmic Goods Manufacturing 60

441320 Tire Dealers 2,248

Typical daily emissions were calculated in the same method as annual emissions, only using 

surveyed daily emissions instead of annual totals. Annual and typical daily emissions for the 

PM10 nonattainment area were calculated by multiplying the Maricopa County emission totals by 

the percentage industrial employment within the nonattainment area. (See Section 1.5.1 for a 

discussion of the employment data used.)

PM10 emissions from = Annual Maricopa County × NAA:county ratio of

area-source plastic/rubber emissions industrial employment

in the PM10 NAA (tons/yr)

= 140.94 tons PM10/yr × 0.9974

= 140.57 tons PM10/yr

Table 3.3–20 summarizes annual and typical daily emissions from rubber/plastic products 

manufacturing in both Maricopa County and the PM10 nonattainment area.

Table 3.3–20. Annual and typical daily emissions from area-source rubber/plastic product manufacturing.

Geographic Area

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

PM10 PM2.5 PM10 PM2.5

Maricopa County 140.94 105.96 953.3 698.8

PM10 NAA 140.57 105.68 950.9 697.0

3.3.8 Fabricated metal products manufacturing

Emissions from fabricated metal products manufacturing were calculated by the “scaling up” 

method as described in EPA emission inventory guidance (US EPA, 2001a). This method combines detailed emissions data from a subset of sources, and county-level employment data from 
2008 Maricopa Co. PM10 Emission Inventory 40 June 2011 

the US Census Bureau (2010a) to develop a per-employee emission factor that is then used to 

estimate emissions from all sources in an industry category.

The most recent data from the US Census Bureau’s County Business Patterns (CBP) for 2007 

employment were used. CBP employment data for NAICS code 332* (fabricated metal products 

manufacturing) indicated that there were 16,138 employees in this industry in Maricopa County. 

Some facilities in this category are considered point sources, and have been addressed in Chapter 

2. To avoid double-counting, employment at point sources is subtracted from total employment 

as follows:

Total area-source = Total employment (from US – Employment at point sources

employment in Census’ County Business Patterns) (from annual emission reports)

fab. metal products

= 16,138 – 4,000

= 12,138 employees

Annual emissions were calculated by “scaling up” area-source emissions reported from those 

facilities surveyed in 2007 as follows:

Total area-source = Emissions from surveyed area sources

emissions Employment at surveyed area sources

× Total area-source employment

Area-source PM10 = 18.07 tons of PM10/yr

emissions from 4,261 employees

× 12,138 employees

fab. metal products

= 51.48 tons PM10/yr

Typical daily emissions were calculated in the same method as annual emissions, only using 

surveyed daily emissions instead of annual totals. Annual and typical daily emissions for the 

PM10 nonattainment area were calculated by multiplying the Maricopa County emission totals by 

the percentage of industrial employment within the nonattainment area. (See Section 1.5.1 for a 

discussion of the employment data used.)

PM10 emissions from area-source fabricated = Annual Maricopa County× NAA:County ratio of

metal production in the PM10 NAA (tons/yr) emissions (tons/yr) industrial employment

= 51.48 tons/yr × 0.9974

= 51.35 tons PM10/yr

Table 3.3–21 summarizes annual and typical daily emissions from fabricated metal products 

manufacturing in both Maricopa County and the PM10 nonattainment area.

Table 3.3–21. Annual and typical daily emissions from area-source fabricated metal product manufacturing.

Geographic Area

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

PM10 PM2.5 NHx PM10 PM2.5 NHx

Maricopa County 51.48 42.62 4.50 538.1 460.6 28.9

PM10 NAA 51.35 42.51 4.49 536.7 459.4 28.8
2008 Maricopa Co. PM10 Emission Inventory 41 June 2011 

3.3.9 Construction

Maricopa County’s air quality permits database was used to identify all dust control permits 

issued during 2008. A total of 4,622 permits were issued, comprising a total of 42,130 acres 

(Table 3.3–22). Data requested on each dust control permit application includes the project type 

and acreage. It was assumed there is no unpermitted earthmoving activity.

Table 3.3–22. Maricopa County dust control permits issued in 2008, by type.

Total Acreage, by Project Type Reported Acres

Residential (single- and multi-family) 20,437.0

Commercial 10,850.0

Road construction 4,449.0

Trenching 3,396.1

Demolition 1,970.6

Weed control 687.0

Site prep / land development 218.9

Temp. storage yard 122.4

Totals: 42,130.9

The Western Regional Air Partnership (WRAP) Fugitive Dust Handbook (WRAP, 2006a) 

provides different emission factors for residential (single-family houses and apartment 

buildings), nonresidential, road, and general construction. MCAQD used the WRAP-suggested 

emission factors except for the following activities:

• The WRAP Fugitive Dust Handbook recommended using 0.42 ton PM10/acre-month for road 

construction to account for the large amount of dirt moved during the construction of roadways. However, both the South Coast Air Quality Management District (SCAQMD) and the 

Clark County Department of Air Quality and Environmental Management have estimated 

that a certain percentage of their road construction projects do not involve large-scale earthmoving activities, and thus have developed average emission factors for road construction 

projects (0.1895 ton PM10/acre-month and 0.265 ton PM10/acre-month, respectively). Since

Maricopa County and Clark County have similar population growth rates, climatic conditions, and PM10 sources, MCAQD used the Clark County road construction emission factor 

of 0.265 tons/acre-month to estimate emissions from road construction projects (Clark 

County, 2001).

• Specific emission factors were not available in the WRAP Fugitive Dust Handbook for 

trenching, demolition, weed control, and temporary storage yard activities; thus, the general 

construction emission factor of 0.11 tons PM10/acre-month was used to estimate emissions 

from these activities.

Information was not readily available regarding the breakout of residential construction activity 

between single-family and multi-family residential construction; thus, acreage for residential 

construction was allocated based on single-family and multi-family household percentages (See 

Section 1.5.1 for single-family and multi-family household percentages used).

Estimates for the duration of house and apartment construction were obtained from EIIP 

guidance (US EPA, 2002). Estimates for the duration of nonresidential construction and road 

construction were obtained from the WRAP Fugitive Dust Handbook (WRAP, 2006a). No 

estimates for the duration of trenching, demolition, weed control, site prep/land development, 

and temporary storage yard activities were available; thus, MCAQD assumed the following:
2008 Maricopa Co. PM10 Emission Inventory 42 June 2011 

• 1-month duration for trenching, demolition, and weed control.

• 8-month duration for site prep/land development activities (weighted average of residential 

and commercial duration) because the duration depends on the project type and size.

• 12-month duration for temporary storage yard activities because these activities are 

frequently associated with road construction.

The average duration of construction activity and emission factors for each project type are 

shown below in Table 3.3–23.

Table 3.3–23. Average project duration and emission factor, by project type.

Project Type

Average Duration 

(months)

Emission factor

(tons PM10/acre-month)

Residential: single-family 6 0.032

Residential: multi-family 12 0.11

Commercial 11 0.19

Road construction 12 0.265

Trenching 1 0.11

Demolition 1 0.11

Weed control 1 0.11

Site prep / land development 8 0.11

Temp. storage yard 12 0.11

County-wide annual uncontrolled PM10 emissions for each construction category were then 

calculated as follows:

Annual uncontrolled = total acres/yr × no. months × emission factor

PM10 emissions

Example:

Annual uncontrolled PM10 = 15,327.8 acres/yr × 6 months × 0.032 tons PM10/acre-month

emissions from single-family

residential construction = 2,942.93 tons PM10/yr

As in prior years, a control efficiency of 90% was applied to the uncontrolled emissions calculations. This factor is in line with values applied in a number of earlier SIP documents for Maricopa and Clark Counties, including:

• Revised MAG 1999 Serious Area Particulate Plan for PM10 (Appendices volume two, page 

V-9, and vol. four), Feb. 2000.

• Revised MAG 1999 Serious Area Particulate Plan for PM10, (Appendix C, Exhibit 3: 

Evaluation for Compliance with 24-Hour PM10 Standard for West Chandler and Gilbert 

Microscale Sites, Arizona Department of Environmental Quality, June 1999, pp. 3-5 and 3-

9), Feb. 2000.

• “Evaluation of Fugitive Dust Control in the Maricopa Co. PM10 Nonattainment Area”, report 

by ENSR in: Final Plan for Attainment of the 24-hour PM10 Standard, ADEQ, May 1997, 

Appendix B.

• Clark Co. PM10 State Implementation Plan, June 2001, pg. L-5. (An 87% emission reduction 

percentage is assumed for watering at construction activities.)

A recent rule effectiveness study by Maricopa County (contained in Appendix 3) indicated an 

89.94% compliance rate with Maricopa County Rule 310 on dust control at construction sites. 
2008 Maricopa Co. PM10 Emission Inventory 43 June 2011 

Thus, an overall control effectiveness of 80.9% (= 90% × 89.94%) was applied. Controlled 

PM10 emissions were calculated as follows:

Annual controlled = Uncontrolled PM10 emissions (tons/yr) × [1 – (control efficiency × rule effectiveness)]

PM10 emissions

Example:

Annual controlled PM10 emissions from = 2,942.93 tons/yr × [1 – (90% control × 89.94% rule effectiveness)]

single-family residential construction

= 560.75 tons PM10/yr

PM2.5 emissions were estimated to comprise 10% of PM10 emissions (WRAP, 2006a). Table 

3.3–24 summarizes the calculations for each dust control permit category.

Table 3.3–24. Annual emissions from construction in Maricopa County, by project type.

Project Type

Total acremonthsEmission factor 

(tons/acre-month)

Uncontrolled 

PM10

Controlled

PM10

Controlled 

PM2.5

Residential: single-family 91,966.5 0.032 2,942.93 560.75 56.07

Residential: multi-unit 61,311.0 0.11 6,744.21 1,285.04 128.50

Commercial 119,349.7 0.19 22,676.44 4,320.77 432.08

Road construction 53,388.0 0.265 14,147.82 2,695.73 269.57

Trenching 3,396.1 0.11 373.57 71.18 7.12

Demolition 1,970.6 0.11 216.76 41.30 4.13

Weed control 687.0 0.11 75.56 14.40 1.44

Site prep/land development 1,750.9 0.11 192.60 36.70 3.67

Temporary storage yard 1,468.7 0.11 161.55 30.78 3.08

Totals: 47,531.45 9,056.64 905.66

Dust control permit site location data were used to determine construction activity that occurred 

in the Maricopa County PM10 nonattainment area. The same average duration of construction 

activity and emission factors used to estimate Maricopa County emissions (see Table 3.3–18) 

were applied to construction activity in the Maricopa County PM10 nonattainment area. Table 

3.3–25 summarizes Maricopa County PM10 nonattainment area construction activity and 

calculations for each project type.

Table 3.3–25. Annual emissions from construction within the Maricopa County portion of the PM10

nonattainment area, by project type.

Project Type

Total 

Acres

Total acremonthsEF (tons/

acre-month)

Uncontrolled 

PM10

Controlled

PM10

Controlled

PM2.5

Residential: single-family 13,989.0 83,934.0 0.032 2,685.89 511.77 51.18

Residential: multi-unit 4,663.0 55,956.0 0.11 6,155.16 1,172.80 117.28

Commercial 10,125.2 111,376.9 0.19 21,161.61 4,032.13 403.21

Road construction 3,383.9 40,606.8 0.265 10,760.80 2,050.36 205.04

Trenching 1,938.2 1,938.2 0.11 213.20 40.62 4.06

Demolition 1,949.0 1,949.0 0.11 214.39 40.85 4.08

Weed control 638.5 638.5 0.11 70.23 13.38 1.34

Site prep/land development 218.9 1,750.9 0.11 192.60 36.70 3.67

Temporary storage yard 122.4 1,468.7 0.11 161.55 30.78 3.08

Totals: 37,027.9 41,615.42 7,929.40 792.94

In addition, the Pinal County Air Quality Department (PCAQD) provided construction emission 

estimates for the Pinal County portion of the PM10 nonattainment. PCAQD estimated that 

approximately 0.8 percent of the Pinal County construction activity occurred in the Pinal County 

portion of the PM10 nonattainment area, thus, annual and typical daily emission for the Pinal 
2008 Maricopa Co. PM10 Emission Inventory 44 June 2011 

County portion of the PM10 nonattainment area was calculated by multiplying the Pinal County 

emission totals by 0.8 percent. The PCAQD estimates (presented in Table 3.3–26 below) incorporated the same assumptions concerning relevant input variables such as the average duration of 

construction activity, emission factors, control efficiency, and rule effectiveness as Maricopa 

County's estimates.

Table 3.3–26. Annual emissions from construction in the Pinal County portion of the PM10 NAA, by project 

type.

Project Type PM10 PM2.5

Residential: single-family 7.65 0.77

Residential: multi-family 0.16 0.02

Commercial 25.16 2.52

Road construction 1.42 0.14

Trenching 0.08 0.00

Totals: 34.47 3.45

To calculate average daily emissions from construction activity, It was assumed that construction 

activity typically occurs 6 days per week and remains relatively even throughout the year. Thus, 

typical daily emissions were calculated by dividing annual emissions for each category were 

divided by 312 (= 6 days/wk × 52 wks/yr) to derive the daily emissions estimates shown in Table 

3.3–27.

Table 3.3–27. Annual and typical daily emissions from construction in Maricopa County and the PM10 NAA.

Construction Type

Maricopa County PM10 NAA 

Annual emissions 

(tons/yr)

Typical daily emissions 

(lbs/day)

Annual emissions 

(tons/yr)

Typical daily emissions 

(lbs/day)

PM10 PM2.5 PM10 PM2.5 PM10 PM2.5 PM10 PM2.5

Residential 1,845.79 184.58 11,832.0 1,183.2 1,692.38 169.24 10,920.3 1,092.0

Commercial 4,320.77 432.08 27,697.2 2,769.7 4,057.29 405.73 25,897.4 2,589.7

Road construction 2,695.73 269.57 17,280.3 1,728.0 2,051.78 205.18 13,156.8 1,315.7

All other* 194.36 19.44 1,245.9 124.6 162.41 16.24 1,043.9 104.4

Total: 9,056.64 905.66 58,055.4 5,805.5 7,963.87 796.39 51,018.4 5,101.8

*Includes: trenching, demolition, weed control, site prep/land development, and temporary storage yard.

3.3.10 Electrical equipment manufacturing

Annual and typical daily emissions from electric equipment manufacturing were derived from 

annual emission reports submitted by permitted sources. It was assumed that there were no 

significant unpermitted sources within Maricopa County and all electrical equipment manufacturing permitted sources are reported here as area-sources.

As all facilities addressed in this source category are located within the PM10 nonattainment area, 

emission totals for both areas are equal. Annual and typical daily emissions are shown in Table 

3.3–28.

Table 3.3–28. Annual and typical daily emissions from area-source electric equipment manufacturing.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Maricopa County 13.94 9.64 20.45 0.18 31.55 76.9 53.2 112.4 1.1 193.7

PM10 NAA 13.94 9.64 20.45 0.18 31.55 76.9 53.2 112.4 1.1 193.7
2008 Maricopa Co. PM10 Emission Inventory 45 June 2011 

3.3.11 State-permitted portable sources

The Arizona Department of Environmental Quality (ADEQ) retains the authority to permit 

certain categories of sources within Maricopa County, including portable sources. MCAQD 

requested information from ADEQ for all ADEQ-permitted sources that reported any activity in 

Maricopa County during 2008. Annual total emissions for most pollutants were provided, along 

with information on the facility type, and information on the location of the site(s) during the 

year. Permits were classified into four major types: asphalt batch, concrete batch, crushing/ 

screening, and other (including soil remediation, generators, etc.). From this information, 

emissions that occurred within Maricopa County were estimated as in the following example.

Data provided

Source information: McNeil Brothers - Erie Strayer Portable Plant

:

Permit type: Concrete batch plant

Operating schedule: Operated from 1/1-5/15 in Mesa at SR202 and McKellips (SE Corner);

operated from 10/16-12/31 in Goodyear at Northside I-10 east of Estrella.

Total annual emissions:

(tons/yr)

PM10 PM2.5 * NOx SOx

0.923 0.461 8.429 2.306

* PM2.5 was assumed to be 50% of reported PM10 for crushing/screening operations.

Using this information, calculations were made to determine:

Total operating days in 2008: 136 = 31 (Jan.) + 29 (Feb.) + ...16 (Oct.) + 30 (Nov.) + 31 (Dec.)

Total operating days in Maricopa County: 136 = 31 (Jan.) + 29 (Feb.) + ...16 (Oct.) + 30 (Nov.) + 31 (Dec.)

All emissions were assumed to be equally distributed among all reported days of operation. 

First, emissions attributable to activity within Maricopa County were calculated as follows:

Annual PM10 emissions = Total annual emissions ×

in Maricopa County (tons/yr) total operating days in 2008

operating days in Maricopa County

= 0.923 ×

136

136

= 0.923 tons PM10/yr

Typical daily emissions were then calculated as follows:

Typical daily =total emissions attributable to activity in Maricopa County × 2,000 lbs

emissions number of operating days in Maricopa County ton

(lbs/day)

= 0.923 tons × 2,000 lbs

136 days ton

= 13.6 lbs PM10/day

Table 3.3–29 summarizes the annual and typical daily emissions for all ADEQ-permitted 

portable sources that operated within Maricopa County at some point during 2008. Since precise 

location data was not available for all permits, all emissions are conservatively assumed to have 

originated within the PM10 nonattainment area; thus emission estimates for Maricopa County and 

the PM10 nonattainment area are equal.
2008 Maricopa Co. PM10 Emission Inventory 46 June 2011 

Table 3.3–29. Annual and typical daily emissions from ADEQ-permitted portable sources.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

PM10 PM2.5 NOx SOx PM10 PM2.5 NOx SOx

Total: 59.00 29.50 282.18 88.93 492.9 246.5 2,275.7 721.7

3.3.12 Paved/unpaved road travel on industrial sites

This section addresses emissions from travel on paved and unpaved roads within the boundaries 

of a permitted facility. Emissions from motor vehicle travel on public and private roads is 

addressed in Chapter 5, Mobile Sources, and road travel emissions from facilities considered 

point sources are addressed in Chapter 2, Point Sources. PM10 emissions from this source 

category were derived from annual emission reports from permitted sources, using AP-42 

equations based on vehicle size and average speed (US EPA, 1997; 1998b). It is assumed that 

there are no unpermitted sources with significant emissions from on-site road travel.

PM2.5 emissions were calculated from PM10 using a ratio derived from California Air Resources 

Board’s (CARB) PM2.5 Fraction Table (CARB, 2006).

Typical daily emissions were calculated using operating schedule information for each reported 

process (normally a 5 or 6-day week), which were then summed to provide total daily emissions 

for the county. Emissions totals for the PM10 nonattainment area were determined from the site 

locations of each facility. Results for each geographic area are shown in Table 3.3–30.

Table 3.3–30. Annual and typical daily emissions from paved and unpaved road travel at industrial facilities.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 PM10 PM2.5

Maricopa County 566.30 271.29 3,880.4 1,847.2

PM10 NAA 472.36 217.08 3,273.9 1,500.1

3.3.13 Industrial processes not elsewhere classified (NEC)

Annual area-source emissions from other industrial processes NEC were derived from annual 

emissions reports from permitted facilities. Other industrial processes include a wide array of 

industrial activities that are often specific to the permitted facility that reported the process. For 

this reason, it is assumed there are no significant emissions from other industrial processes, other 

than those reported by permitted facilities on their annual emissions reports. Typical daily 

emissions were calculated based on operating schedule information provided by individual 

facilities through MCAQD’s annual emissions reporting program. Emissions estimates for the 

PM10 nonattainment area were derived using data on the location of the facilities that report other 

industrial processes. Emissions totals are presented in Table 3.3–31.

Table 3.3–31. Annual and typical daily emissions from other industrial processes not elsewhere classified.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Maricopa County 144.60 107.24 10.22 21.49 16.79 953.3 726.4 69.6 137.7 94.6

PM10 NAA 136.00 99.12 8.12 21.47 14.10 906.0 681.7 55.4 137.6 79.8
2008 Maricopa Co. PM10 Emission Inventory 47 June 2011 

3.3.14 Summary of all area-source industrial processes

Tables 3.3–32 and 3.3–33 provide a summary of annual and typical daily emissions from all 

industrial sources, for Maricopa County and the PM10 nonattainment area, respectively.

Table 3.3–32. Annual and daily emissions from all area-source industrial processes in Maricopa County.

Annual emissions (tons/yr)

Source category PM10 PM2.5 NOx SOx NH3

Chemical manufacturing 187.43 151.42 0.00 0.34 0.03

Commercial cooking 988.99 917.18

Grain handling/processing 20.59 6.71

Ammonia cold storage 1,678.43

Secondary metal production 60.56 52.16 49.73 18.65 .004

Non-metallic mineral processes 195.81 97.28

Mining and quarrying 210.39 59.56

Wood product manufacturing. 217.26 203.25

Rubber/plastic product manufacturing 140.94 105.96

Fabricated metal product manufacturing 51.48 42.62

Residential construction 2,451.72 245.17

Commercial construction 5,739.18 573.92

Road construction 3,580.67 358.07

Other construction 258.18 25,82

Electrical equipment manufacturing 13.94 9.64 20.45 0.18 31.55

ADEQ-permitted portable sources 59.00 29.50 282.18 88.93

Road travel at industrial sites 566.30 271.29

Industrial processes NEC 144.60 107.24 10.22 21.49 16.79

All industrial processes: 11,881.57 2,953.30 362.58 129.60 1,731.34

Typical daily emissions (lbs/day)

Source category PM10 PM2.5 NOx SOx NH3

Chemical manufacturing 1,445.8 1,164.5 0.0 2.6 0.6

Commercial cooking 5,434.0 5,039.5

Grain handling/processing 149.3 49.5

Ammonia cold storage 10,759.2

Secondary metal production 442.7 386.2 358.8 142.7 0.0

Non-metallic mineral processes 1,357.4 671.7

Mining and quarrying 1,442.1 390.8

Wood product manufacturing. 1,668.6 1,548.3

Rubber/plastic product manufacturing 953.3 698.8

Fabricated metal product manufacturing 538.1 460.6 28.9

Residential construction 15,716.1 1,571.6

Commercial construction 36,789.6 3,679.0

Road construction 22,953.0 2,295.3

Other construction 1,654.9 165.5

Electrical equipment manufacturing 76.9 53.2 112.4 1.1 193.7

ADEQ-permitted portable sources 492.9 246.5 2,275.7 721.7

Road travel at industrial sites 3,880.4 1,847.2

Industrial processes NEC 953.3 726.4 69.6 137.7 94.6

All industrial processes: 76,667.6 19,048.2 2,816.5 1,005.8 11,077.2
2008 Maricopa Co. PM10 Emission Inventory 48 June 2011 

Table 3.3–33. Annual and typical daily emissions from all area-source industrial processes in the PM10 NAA.

Annual emissions (tons/yr)

Source category PM10 PM2.5 NOx SOx NH3

Chemical manufacturing 186.94 151.03 0.00 0.34 0.03

Commercial cooking 993.04 920.94

Grain handling/processing 16.73 5.68

Ammonia cold storage 1,674.1

Secondary metal production 60.56 52.16 49.73 18.65 0.04

Non-metallic mineral processes 187.73 91.92

Mining and quarrying 156.60 46.81

Wood product manufacturing. 216.69 202.72

Rubber/plastic product manufacturing 140.57 105.68

Fabricated metal product manufacturing 51.35 42.51 4.49

Residential construction 1,692.38 169.24

Commercial construction 4,057.29 405.73

Road construction 2,051.78 205.18

Other construction 162.41 16.24

Electrical equipment manufacturing 13.94 9.64 20.45 0.18 31.55

ADEQ-permitted portable sources 59.00 29.50 282.18 88.93

Road travel at industrial sites 472.36 217.08

Industrial processes NEC 136.00 99.12 8.12 21.47 14.10

All industrial processes: 10,655.39 2,771.19 360.48 129.58 1,724.27

Typical daily emissions (lbs/day)

Source category PM10 PM2.5 NOx SOx NH3

Chemical manufacturing 1,442.0 1,161.5 0.0 2.6 0.9

Commercial cooking 5,456.3 5,060.1

Grain handling/processing 125.3 43.0

Ammonia cold storage 10,731.2

Secondary metal production 442.7 386.2 358.8 142.7 0.0

Non-metallic mineral processes 1,302.8 635.6

Mining and quarrying 1,075.7 307.2

Wood product manufacturing. 1,664.3 1,544.3

Rubber/plastic product manufacturing 950.9 697.0

Fabricated metal product manufacturing 536.7 459.4 28.8

Residential construction 10,920.3 1,092.0

Commercial construction 25,897.4 2,589.7

Road construction 13,156.8 1,315.7

Other construction 1,043.9 104.4

Electrical equipment manufacturing 76.9 53.2 112.4 1.1 193.7

ADEQ-permitted portable sources 492.9 246.5 2,275.7 721.7

Road travel at industrial sites 3,273.9 1,500.1

Industrial processes NEC 906.0 681.7 55.4 137.6 79.8

All industrial processes: 68,764.6 17,877.6 2,802.3 1,005.7 11,034.4

3.4 Waste treatment and disposal

3.4.1 On-site incineration

This section includes emissions from on-site industrial incinerators, primarily burn-off ovens 

used to reclaim electric wire or other materials. Emissions from human and animal crematories 

are addressed in Section 3.5.4. There were no incinerators at residential (e.g., apartment 

complexes) or commercial/institutional facilities (e.g., hospitals, service establishments) in 

operation during 2008.
2008 Maricopa Co. PM10 Emission Inventory 49 June 2011 

Emissions from on-site incineration were determined from annual emission inventory reports. It 

is assumed that all incinerator emissions are accounted for, since all permitted incinerators 

received surveys in 2008. All surveyed facilities are located within the PM10 nonattainment area, 

thus total emissions for the county and NAA are equal.

Table 3.4–1. Annual and typical daily emissions from on-site incineration.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NOx SOx PM10 PM2.5 NOx SOx

Maricopa County 0.06 0.04 5.01 0.01 0.7 0.4 38.9 0.1

PM10 NAA 0.06 0.04 5.01 0.01 0.7 0.4 38.9 0.1

3.4.2 Open burning

Emissions from controlled open burning are regulated by Maricopa County Air Pollution Control 

Regulations Rule 314 (Open Outdoor Fires), which requires a burn permit for open burning in 

Maricopa County. Burn permits are issued primarily for purposes of agricultural ditch bank and 

fence row burning, tumbleweed burning, land clearance, air curtain destructor burning of trees, 

and fire fighting training. Maricopa County’s burn permit data base was used to identify all burn 

permits issued during 2008. A total of 55 permits were issued during the year; however, not all 

permit applications contained the requested information that is needed to calculate emissions. 

Where data were missing, activity data for each permit category was grown from those permits 

that contained the necessary information, as follows:

=∑ ×

number of permits with activity data

total number of permitsissued Total activity activity reported

Example:

787,398 linear ft

22 permits with data

32 burn permitsissued 541,336 linear ft (reported) bank/fencerows

Total ditch -

= × =

Reported and estimated activity data for each open burning category are summarized in Table 

3.4–2. Permits issued for firefighting training are addressed Section 3.5.1.2.

Table 3.4–2. Summary of 2008 Maricopa County burn permit activity.

Category Unit of measure

Total reported 

activity

Number of 

permits with 

activity data

Total 

permits 

issued

Estimated total 

annual activity 

level

Ditchbank/fencerow Linear ft 541,336 22 32 787,398

Land clearance Acres 564 5 12 1,354

Air curtain Tons of Material Burned 70* 0 7 70

Tumbleweeds Piles 14 2 4 28

* Assumed that air curtain destructors burn 10 tons/day of brush/trees/vegetation.

The above activity data were converted to tons material burned using fuel loading factors from 

AP-42, Table 2.5–5 (US EPA, 1992). The emission and loading factors used are shown in Table 

3.4–3. As a conservative estimate, all particulate matter is presumed to be PM10 (and PM2.5).
2008 Maricopa Co. PM10 Emission Inventory 50 June 2011 

Table 3.4–3. Emission and fuel loading factors for open burning.

Emission factors (lbs/ton burned) Fuel loading factor

Category PM (tons/acre) 10 PM2.5 NOx SOx NH3

Weeds, unspecified 15 15 4 N/A N/A 3.2 

Russian Thistle (tumbleweeds) 22 22 4 N/A N/A 0.1 

Orchard crops: Citrus 6 6 4 N/A N/A 1.0 

The following assumptions were made based on previous Maricopa County emission inventory 

and information from MCAQD's open burn program staff:

• Ditch banks and fence rows in Maricopa County average 7 feet in width and are burned twice 

per year (MCESD, 1999).

• A pile of tumbleweeds 15 feet in diameter and 5 feet high weighs 200 lbs (MCESD, 1993). 

This is equivalent to the AP-42 fuel loading factor for tumbleweeds (0.1 tons/acre).

• Air curtain destructors burn between 7–10 tons of material per day (MCAQD, 2006).

To calculate the annual amount of material burned on ditch banks and fence rows in Maricopa 

County, MCAQD estimated the area burned and then applied AP-42 fuel loading factor. The 

tons of material burned in ditch banks and fence rows in Maricopa County were estimated as 

follows:

Material burned from = 787,398 ft length × 7 ft width × 3.2 tons/acre × 2 times/yr

ditchbanks and fence rows 43,560 ft2/acre

= 809.81 tons/yr

Activity data for the other categories were similarly converted to derive the total mass of 

material burned using AP-42 fuel loading factors.

Annual emissions were then calculated by multiplying the amount of material burned by AP-42 

emission factors (listed in Table 3.4–3) for each open burning category. To account for unpermitted illegal outdoor burning, all calculated emissions estimates were multiplied by a factor of 

2.87, based on complaints received in 2008 reporting suspected open or illegal outside burning in 

the County (158 complaints were received in 2008; thus 158 complaints/55 open burn permits = 

2.87).

Annual PM10 emissions from = Total material burned × emission factor × unit conversion factor

ditchbank and fence row burning

= 809.81 tons × 15 lbs/ton × 1 ton / 2,000 lbs

= 6.07 tons/yr

Total annual PM10 emissions = Calculated emissions from permit data × unpermitted burning adjustment factor

including unpermitted burning

= 6.07 tons/yr × 2.87

= 17.43 tons PM10/yr
2008 Maricopa Co. PM10 Emission Inventory 51 June 2011 

Table 3.4–4 summarizes the 2008 emissions in Maricopa County from each category of open 

burning activity.

Table 3.4–4. Annual and typical daily emissions from open burning in Maricopa County.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Category Ton-equivalents PM10 PM2.5 NOx PM10 PM2.5 NOx

Ditchbank/fencerow 809.8 17.45 17.45 4.65 179.0 179.0 47.7

Land clearance 4,331.5 93.32 93.32 24.89 717.9 717.9 191.4

Air curtain 70.0 0.60 0.60 0.40 4.6 4.6 3.1

Tumbleweeds 2.8 0.09 0.09 0.02 0.7 0.7 0.1

Totals: 111.46 111.46 29.96 902.2 902.2 242.4

It was assumed that open burning occurs 5 days per week (most burn permits are issued for 

weekdays but permits may be issued on weekends depending on circumstances). Open burning 

occurs year-round with the exception of ditch bank and fence row burning, which is not allowed 

during the CO season (November through January).

PM10 typical daily emissions for Maricopa County were derived as follows:

Typical daily PM10 emissions =annual PM10 emissions (tons/yr) × 2000 lbs/ton

(burn days/week) × (burn weeks/year)

Typical daily PM10 emissions from =17.45 tons/yr × 2000 lbs/ton

ditchbank/ fence row burning 5 days/wk × 39 wks/yr

= 179.0 lbs PM10/day

Table 3.4–4 above summarizes the typical daily emissions for Maricopa County from each open 

burning category.

Annual and daily emissions for the nonattainment area were calculated by multiplying the percentage of agricultural and/or vacant land use within the PM10 nonattainment area by the County 

wide emissions estimates, results are shown in Table 3.4–5. (See Section 1.5.1 for a discussion 

of the land use data used.) Table 3.4–6 summarizes the annual emissions for the PM10 nonattainment area.

Table 3.4–5. Surrogate land use classes and NAA:County activity ratios for burn permit categories.

Category

Surrogate land

use categories

2008 NAA:county 

land use ratio

Ditchbank/fencerow Agriculture 44.14 %

Land clearance Vacant 21.22 %

Air curtain Agriculture and vacant 23.91 %

Tumbleweeds Agriculture and vacant 23.91 %

Table 3.4–6. Annual and typical daily emissions from open burning in the PM10 NAA.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Category PM10 PM2.5 NOx PM10 PM2.5 NOx

Ditchbank/fencerow 7.70 7.70 2.05 79.0 79.0 21.1

Land clearance 19.81 19.81 5.28 152.4 152.4 40.6

Air curtain 0.14 0.14 0.10 1.1 1.1 0.7

Tumbleweeds 0.02 0.02 0.00 0.2 0.2 0.0

Totals: 27.67 27.67 7.44 232.6 232.6 62.5
2008 Maricopa Co. PM10 Emission Inventory 52 June 2011 

3.4.3 Landfills

Emissions from municipal solid waste (MSW) landfills come from uncontrolled landfill gas 

emissions as well as from cover operations and combustion from control measures, such as a 

flare. Total emissions were calculated from annual emissions inventory reports from all landfills 

located within the county; results are shown in Table 3.4–7 below. No landfills were considered 

point sources; thus all MSW landfills are reported here as an area-source activity.

Table 3.4–7. Annual and typical daily emissions from landfills.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NOx SOx PM10 PM2.5 NOx SOx

Maricopa County 86.21 75.92 24.11 7.57 486.1 425.4 132.9 41.7

PM10 NAA 60.25 50.78 19.47 6.22 342.4 286.6 107.4 34.3

3.4.4 Publicly owned treatment works (POTWs)

Emissions from publicly owned treatment works (POTWs) were calculated by multiplying percapita emission factors (Battye et al., 1994) by population estimates and per-capita wastewater 

usage estimates of 100 gallons per day per person (Tchobanoglous, 1979), as shown in Table 

3.4–8. Typical daily emissions were calculated by dividing annual emissions by 366 days, as 

activity is assumed to occur uniformly throughout the year.

Table 3.4–8. NH3 emissions from publicly-owned treatment works (POTWs).

Geographic area

2008

Population

NH3 emission factor

(lbs/106 gals treated)

Annual NH3

emissions 

(tons/yr)

Typical daily NH3

emissions 

(lbs/day)

Maricopa County 4,279,760 19.0 1,488.07 8,131.5

PM10 NAA 4,297,140 19.0 1,494.12 8,164.6

3.4.5 Other industrial waste disposal

Annual area-source emissions from other industrial waste disposal were derived from annual 

emissions reports from permitted facilities. Other industrial waste disposal processes include a 

wide array of industrial activities that are often specific to the permitted facility that reported the 

process. For this reason, it is assumed there are no significant emissions from this category, 

other than those reported by permitted facilities on their annual emissions reports. Typical daily 

emissions were calculated based on operating schedule information provided by the facilities in 

their annual emissions report. Emission estimates are shown in Table 3.4–9 below.

All facilities that reported area-source emissions from other industrial waste disposal are located 

inside the PM10 nonattainment area, therefore emissions for Maricopa County and the PM10

NAA are equal.

Table 3.4–9. Annual and typical daily emissions from other industrial waste disposal.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NOx SOx PM10 PM2.5 NOx SOx

Maricopa County 32.78 16.93 18.39 50.62 224.1 110.9 101.0 278.1

PM10 NAA 32.78 16.93 18.39 50.62 224.1 110.9 101.0 278.1
2008 Maricopa Co. PM10 Emission Inventory 53 June 2011 

3.4.6 Summary of all area-source waste disposal

Tables 3.4–10 and 3.4–11 provide a summary of annual and typical daily emissions from all 

waste disposal activity, for Maricopa County and the PM10 nonattainment area, respectively.

Table 3.4–10. Annual and typical daily emissions from all area-source waste disposal for Maricopa County.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Category PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

On-site incineration 0.06 0.04 5.01 0.01 0.7 0.4 38.9 0.1

Open burning 111.46 111.46 29.96 902.2 902.2 242.4

Landfills 86.21 75.92 24.11 7.57 486.1 425.4 132.9 41.7

POTWs 1,488.07 8,131.5

Other 32.78 16.93 18.39 50.62 224.1 110.9 101.0 278.1

Total: 230.52 204.35 77.47 58.20 1,488.07 1,613.0 1,438.8 515.3 320.0 8,131.5

Table 3.4–11. Annual and typical daily emissions from all area-source waste disposal for the PM10 NAA.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Category PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

On-site incineration 0.06 0.04 5.01 0.01 0.7 0.4 38.9 0.1

Open burning 27.67 27.67 7.44 232.62 232.62 62.46

Landfills 60.25 50.78 19.47 6.22 342.4 286.6 107.4 34.3

POTWs 1,494.12 8,164.6

Other 32.78 16.93 18.39 50.62 224.1 110.9 101.0 278.1

Total: 120.77 95.42 50.30 56.85 1,494.12 799.8 630.5 309.9 312.6 8,164.6

3.5 Miscellaneous area sources

3.5.1 Other combustion

3.5.1.1 Wildfires

Data on wildfires in 2008 within Maricopa County were obtained from the Arizona State Land 

Department (ASLD) Forestry Division (ASLD, 2009); the Arizona Department of Fire, Building, 

and Life Safety (DFBLS, 2009); and the Federal Fire Occurrence website (FFOW, 2009).

The ASLD Forestry Division provides for the prevention and suppression of wildfires on state 

and private lands located outside of incorporated municipalities. The wildfire data provided by 

ASLD includes wildfires that occur outside of local fire districts and municipalities on State, 

private, and U.S. Bureau of Land Management (BLM) land in 2008. The ASLD reported 25 

wildfires in 2008 in Maricopa County, encompassing a total of nearly 750 acres. Wildfire data 

provided by ASLD were compared to that data reported in the Geospatial Multi-Agency Coordination Group (GeoMAC) Wildland Fire Support database1

 1 The GeoMAC, is an internet-based mapping application designed for fire managers to access online maps of 

current fire locations and perimeters in the conterminous 48 States and Alaska. Historical fire data is also housed in 

the GeoMac database 

and 2008 Incident Status Summary 

reports (ICS-209) to identify wildfires that may have occurred outside of ASLD jurisdiction. 

GeoMAC and ICS-209 reports only include large wildfires, generally fires greater than 100 

acres. Three Maricopa County wildfires were reported in GeoMAC and on ICS-209 reports in 

2008 (USDA, 2008a; USGS, 2008). Two of these fires were included in the ASLD data, one 

http://www.geomac.gov/.
2008 Maricopa Co. PM10 Emission Inventory 54 June 2011 

fire, the Ethan fire, was not captured in the ASLD data because it occurred on tribal lands. The 

Ethan fire encompassed 6,660 acres.

The DFBLS coordinates reporting to the National Fire Incident Reporting System (NFIRS) for 

Arizona fire departments. NFIRS is a national reporting system used by fire departments to 

report fires and other incidents to which they respond and to maintain records of these incidents 

in a uniform manner. Twenty-one of thirty-six fire departments in Maricopa County reported 

over 10,000 fires to NFIRS in 2008. This included ten “forest, woods or wildland fires”. The 

ten “forest, woods or wildland fires” were analyzed for inclusion in the wildfire emission 

estimates. First, the DFBLS fires were culled for duplicates by comparing the incident dates and 

locations with wildfires reported by ASLD. One DFBLS fire was excluded from combined dataset because it may have been a duplicate already captured in the ASLD data. Because only four 

of the ten DFBLS fires included acreage, an average number of acres burned per fire (= 1.05 

acres) were determined from the fires with reported acreage. This average number of acres 

burned was then applied to the fires with no reported acreage.

The Federal Fire Occurrence Website is an official government website that provides users with 

the ability to query, research and download wildland fire occurrence data. The data available 

through this website contains over 548,000 fire records collected by Federal land management 

agencies for fires that occurred from 1980 through 2008 in the United States. The 2008 data for 

Maricopa County included eighty-one fires. The federal wildland fire occurrence data were 

culled for duplicates by comparing the incident names, dates and locations with wildfires 

reported by ASLD and DFBLS. Thirteen fires were excluded from the combined dataset as they 

appeared to be duplicates already captured in either the ASLD or DFBLS data and seven fires 

contained no acreage data. The final 2008 dataset listed 96 fires encompassing over 7,400 acres. 

Table 3.5–1 summarizes fire data obtained from each data source.

Table 3.5–1. Sources and input data used to estimate emissions from fires in Maricopa County.

Data Source

Number of 

Fires in 2008

Total 

Acreage

Arizona State Land Department (ASLD) 25 747.25

Arizona Department of Fire, Building, and Life Safety (DFBLS) 9 9.45

Federal Fire Occurrence website (FFOW) 61 16.79

ICS-209 1 6,660.00

Total: 96 7,433.49

Estimates for fuel loading rates were assigned using fuel model codes from the National Fire 

Danger Rating System (NFDRS) and a table of fuel loading values for NFDRS fuel model 

categories (WGA/WRAP, 2005). The department used the NFDRS Fuel Model map in ArcGIS 

to identify NFDRS fuel types for fires with latitude and longitude data.
2008 Maricopa Co. PM10 Emission Inventory 55 June 2011 

Table 3.5–2. NFDRS fuel model categories and fuel loading factors for 2008 Maricopa County wildfires.

NFDRS Model Category 2008 Fires Total Acreage

Fuel Loading Factor 

(tons/acre)

Agriculture* 33 744.05 4.5

California chaparral 1 0.01 19.5

Barren* 2 0.40 0.5

Pine-grass savanna 1 0.01 4.7

Intermediate brush 17 2.87 15.0

Sagebrush grass 42 6,686.15 4.5

Total 96 7,433.49 — * “Agriculture” and “barren” NFDRS model descriptions were not included in WGA/WRAP 2002 fuel loading values for NFDRS fuel model 

categories. Therefore, it was assumed that “Agriculture” is similar to "sagebrush grass" and “Barren” is similar to “western grasses (annual) and 

fuel loadings were assigned accordingly.

Estimates of the material burned were derived by multiplying the number of acres burned for 

each category by the applicable fuel loading factor. Table 3.5–3 shows the number of wildfires 

and acres burned within both Maricopa County and the PM10 nonattainment area during 2008, as 

well as estimates of total material burned.

Table 3.5–3. Summary of data on fire occurrence, total acres burned, and total material burned in 2008.

Geographic Area No. of Fires

Total Acres 

Burned

Material Burned 

(tons)

Maricopa County 96 7,433 33,479

PM10 NAA 55 6,699 30,147

The prescribed-fire emission factors listed in Table 3.5–4 were obtained from the Western 

Regional Air Partnership's (WRAP) 2002 Fire Emission Inventory (WGA/WRAP, 2005).

Table 3.5–4. Summary of emission factors for prescribed fire.

PM10 PM2.5 NOx SOx NH3

WRAP Emission Factors for Wildfires and

Prescribed Broadcast Burning (lbs/ton) 28.1 24.1 6.2 1.7 1.3

Source: WGA/WRAP, 2005

Annual emissions from wildfires for each geographic area were calculated as follows:

Annual PM10 emissions from = material burned × emission factor (lbs/ton)

wildfires in Maricopa County 2,000 lbs/ton

= 33,479 tons of material burned × 28.1 lbs PM10/ton

2,000 lbs/ton

= 470.38 tons PM10/yr

The majority of fire data included fire locations in latitude and longitude. For those fires without 

longitude and latitude, the fire location address was used to determine latitude and longitude. 

This latitude and longitude data was used to determine the number of acres burned inside of the 

nonattainment areas. Fifty-five wildfires occurred within the PM10 nonattainment area, resulting 

in nearly 6,700 acres burned. The largest fire within the PM10 nonattainment area was the Ethan 

fire which occurred in July 2008 and resulted in more than 6,600 acres burned.

Annual emissions from wildfires within the nonattainment area were calculated in the same 

method as Maricopa County annual emissions.
2008 Maricopa Co. PM10 Emission Inventory 56 June 2011 

Table 3.5–5. Annual emissions from wildfires in Maricopa County and the PM10 NAA.

Average daily emissions were estimated by dividing annual emissions by the number of burn 

days in 2008. There were 150 burn days in Maricopa County and 90 burn days in the PM10

nonattainment area in 2008; thus:

Average daily PM10 emissions from = 470.39 tons PM10/yr × 2,000 lbs/ton

wildfires in Maricopa County 150 days/yr

= 6,271.8 lbs PM10/day

Table 3.5–6. Average daily emissions from wildfires in Maricopa County and the PM10 NAA.

Number of 

Burn Days

Average daily emissions (lbs/day)

Geographic Area PM10 PM2.5 NOx SOx NH3

Maricopa County 150 6,271.8 5,379.0 1,383.8 379.4 290.2

PM10 NAA 90 9,412.5 8,072.7 2,076.8 569.4 435.5

3.5.1.2 Prescribed fires

Prescribed fires data were obtained from the U. S. Forest Service (USFS, 2009). The USFS 

reported that six prescribed fires occurred in Maricopa County in 2008. Twenty-nine acres of 

piled fuels were burned. Four of six prescribed fires occurred inside the PM10 nonattainment 

area. Because all 2008 prescribed fires were piled fuels, material burned was derived by 

multiplying the number of acres burned by tons of piles per acre for each fire. The data provided 

by the USFS, the resulting material burned for each fire, and whether the fire occurred within the 

nonattainment area are shown below in Table 3.5–7.

Table 3.5–7. Summary of data used to estimate emissions from prescribed fires.

Burn Date

Burn 

Number

Burn 

Location

Acres 

Treated

Tons of 

Piles/ Acre

Material 

Burned (tons) Within NAA?

01/13/2008 TNF0106 T6N,R7E,S28 3 1 3 Yes

03/13/2008 TNF0106P T6N,R7E,S28 3 3 9 Yes

04/04/2008 TNF0302 T3N,R7E,S34 2 5 10 Yes

04/09/2008 TNF0302 T3N,R8E,S28 5 5 25 No

09/25/2008 TNF0302 T3N,R8E,S31 10 5 50 No

11/06/2008 TNF0302 T2N,R7E,S18 6 5 30 Yes

29 24 127

Prescribed fire emission factors for “piled fuels” were obtained from the Western Regional Air 

Partnership’s (WRAP) 2002 Fire Emission Inventory (WGA/WRAP, 2005). The emission 

factors are listed below in Table 3.5–8.

Table 3.5–8. Emission factors for prescribed fires.

Type of fire

Emission factors (lbs/ton burned)

PM10 PM2.5 NOx SOx NH3

Prescribed fire (piled fuels) 8.0 8.0 6.2 1.7 0.5

Annual emissions (tons/yr)

Geographic Area PM10 PM2.5 NOx SOx NH3

Maricopa County 470.39 403.43 103.79 28.46 21.76

PM10 NAA 423.56 363.27 93.46 25.62 19.60
2008 Maricopa Co. PM10 Emission Inventory 57 June 2011 

Annual emissions from prescribed fires in Maricopa County were calculated as follows.

Annual PM10 emissions = material burned (tons/acre) × emission factor (lbs/ton)

from prescribed fires 2,000 lbs/ton

in Maricopa County

= 127 tons/acres× 8.0 lbs/ton

2,000 lbs/ton

= 0.508 tons PM10/yr

It was assumed that each prescribed fire lasted one day. Thus, daily emissions from prescribed 

fires were determined by dividing the annual emissions (converted to lbs/yr) by the number of 

burn days. Because six prescribed fires occurred in Maricopa County in 2008, it was assumed 

that there were 6 burn days in 2008.

Typical daily PM10 emissions = annual PM10 emissions (lbs) from prescribed fires

Number of burn days

= 1,016 lbs PM10

6 burn days

= 169.3 lbs PM10/day

Since the prescribed fire data provided by USFS (2009) included burn location, GIS was used to 

determine the fires that burned inside the nonattainment area. Fifty-two of the one-hundred 

twenty-seven acres burned were within the nonattainment area. Thus, annual emissions from 

prescribed fires for the nonattainment area were determined using the formula shown above with 

the material burned within the nonattainment area. Results are shown in Table 3.5–9 below.

Table 3.5–9. Annual and typical daily emission from prescribed fire in Maricopa County and the PM10 NAA.

Annual emissions (tons/yr) Typical daily emission (lbs/day)

Geographic Area PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Maricopa County 0.51 0.51 0.39 0.11 0.03 169.3 169.3 131.2 36.0 10.6

PM10 NAA 0.21 0.21 0.16 0.04 0.01 104.0 104.0 80.6 22.1 6.5

3.5.1.3 Structure fires

2008 structure fire data were from the Arizona Department of Fire, Building, and Life Safety 

(DFBLS; DFBLS, 2009). The DFBLS coordinates reporting to the National Fire Incident 

Reporting System (NFIRS) for Arizona fire departments. The NFIRS is a national reporting 

system used by fire departments to report fires and other incidents to which they respond and to 

maintain records of these incidents in a uniform manner. Twenty-one of thirty-six fire departments in Maricopa County reported over 10,000 fires to NFIRS in 2008. This included nearly 

2,150 reported structure fires. Because the DFBLS data only included data reported by twentyone of thirty-six fire departments in Maricopa County, the number of structure fires reported 

were scaled up to the entire inventory area based on population. The most recent population 

estimates for Maricopa County were used to scale up the number of structure fires (ADC, 2008). 

Seven open burn permits were issued in 2008 for fire training; these were included in the total 

number of estimated structure fires for 2008. It was estimated that 2,422 structure fires occurred 

in Maricopa County in 2008.
2008 Maricopa Co. PM10 Emission Inventory 58 June 2011 

Estimates of the material burned in a structure fire were determined by multiplying the number 

of structure fires by a fuel loading factor of 1.15 tons of material per fire, which factors in the 

estimated percentage of structural loss and content loss (US EPA, 2001c). The amount (tons) of 

material burned was estimated as follows:

Material burned in structure fires (tons/yr) = 2,422 fires/yr × 1.15 tons/fire

= 2,785 tons material burned/yr

Table 3.5–10. Material burned, emission and fuel loading factors for structure fires.

Estimated number 

of structure fires

Fuel loading 

factor (tons/fire)

Material burned 

(tons)

Emission factors (lbs/ton)

PM10 PM2.5* NOx SOx NH3

2,422 1.15 2,785 10.8 10.8 1.4 n/a n/a

* All PM10 is assumed to be PM2.5.

Annual emissions were then calculated by multiplying the amount of material burned by the 

emission factors listed in Table 3.5–10 (from US EPA, 2001c), as follows:

Annual PM10 emissions from = Quantity of material burned × emission factor × unit conversion factor

structure fires in Maricopa County

= 2,785 tons × 10.8 lbs/ton × (1 ton/2,000 lbs)

= 15.04 tons PM10/yr

Annual emissions for the PM10 nonattainment area were derived by multiplying Maricopa 

County annual emissions by the percentage of total residential population within the PM10 nonattainment area (100.41%), as shown in the example below. See Section 1.5.2 for a discussion of 

the population data used.

Annual PM10 emissions = Annual PM10 emissions × Percentage residential population within the NAA

within the PM10 NAA for Maricopa County

= 15.04 tons/yr × 100.41%

= 15.10 tons PM10/yr

Typical daily emissions for both Maricopa County and the PM10 nonattainment area were calculated by dividing annual emissions by 366, as activity is assumed to take place 7 days a week. 

Typical daily emissions for Maricopa County were derived using the following formula:

Typical daily PM10 emissions =

from structure fires 366 days/yr

annual PM10 emissions (lbs)

=

366

30,080 lbs

= 82.2 lbs/day

Table 3.5–11. Annual and typical daily emissions from structure fires in Maricopa County and the NAA.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NOx PM10 PM2.5 NOx

Maricopa County 15.04 15.04 1.95 82.2 82.2 10.7

PM10 NAA 15.10 15.10 1.96 82.5 82.5 10.7
2008 Maricopa Co. PM10 Emission Inventory 59 June 2011 

3.5.1.4 Vehicle fires

2008 vehicle fire data were from the Arizona Department of Fire, Building, and Life Safety 

(DFBLS) (DFBLS, 2009). The DFBLS coordinates reporting to the National Fire Incident 

Reporting System (NFIRS) for Arizona fire department. NFIRS is a national reporting system 

used by fire departments to report fires and other incidents to which they respond and to maintain 

records of these incidents in a uniform manner. Twenty-one of thirty-six fire departments in 

Maricopa County reported over 10,000 fires to NFIRS in 2008. This included over 2,100 

reported vehicle fires. Because the DFBLS data only included data reported by twenty-one of 

thirty-six fire departments in Maricopa County, the number of vehicle fires reported were scaled 

up to the entire inventory area based on population. The most recent population estimates for 

Maricopa County were used to scale up the number of vehicle fires (ADC, 2008). It was 

estimated that 2,403 vehicle fires occurred in Maricopa County in 2008.

Annual emissions from vehicle fires were calculated by first multiplying the number of vehicle 

fires by a fuel loading factor of per vehicle fire to estimate the annual amount of material burned 

in vehicle fires (US EPA, 2000). The amount of annual material burned in vehicle fires is then 

multiplied by emission factors for open burning of automobile components from AP-42 as listed 

in table 3.5–12 (US EPA, 1992).

Annual PM10 emissions = annual number × fuel loading factor × emission factor × unit conversion factor

from vehicle fires of vehicle fires

= 2,403 × 0.25 tons/vehicle × 100 lbs/ton × (1 ton / 2,000 lbs)

= 30.04 tons PM10/yr

Table 3.5–12. Estimated material burned, fuel loading factors, and emission factors for vehicle fires.

Vehicle fires 

reported

Fuel loading 

factor (tons/fire)

Material 

burned (tons)

Emission factors (lbs/ton)

PM10 PM2.5* NOx SOx NH3

2,403 0.25 600.75 100 100 4 n/a n/a

* All PM10 is assumed to be PM2.5.

Annual emissions for the PM10 nonattainment area were derived by multiplying Maricopa 

County annual emissions by the percentage of total residential population within the PM10 nonattainment area (100.41%). See Section 1.5.1 for a discussion of the population data used.

Annual PM10 emissions = annual PM10 emissions × percentage of total residential population

from vehicle fires in the for Maricopa County within the PM10 NAA

PM10 NAA

= 30.04 tons/yr × 100.41%

= 30.16 tons/yr

It is assumed that vehicle fires occur evenly throughout the year. Thus, typical daily emissions 

were derived by dividing the Maricopa County and nonattainment area annual emissions by 366

days/year. The results are shown in Table 3.5–13 below.

Table 3.5–13. Annual and typical daily emissions from vehicle fires.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NOx PM10 PM2.5 NOx

Maricopa County 30.04 30.04 1.20 164.1 164.1 6.6

PM10 NAA 30.16 30.16 1.21 164.8 164.8 6.6
2008 Maricopa Co. PM10 Emission Inventory 60 June 2011 

3.5.1.5 Engine testing

Annual emissions from engine testing facilities were derived from annual emission reports from 

permitted sources that were not considered point sources in this inventory. It was assumed that 

there were no significant unpermitted sources within Maricopa County. Typical daily emissions 

were calculated based on operating schedule information provided in the facilities’ annual emission reports.

Since all facilities considered in this section are located within the PM10 nonattainment area, total 

emission values for the county and the PM10 NAA are equal. Results are shown in Table 3.5–14.

Table 3.5–14. Annual and typical daily emissions from engine testing.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NOx SOx PM10 PM2.5 NOx SOx

Maricopa County 0.18 0.17 6.74 2.49 1.3 1.2 50.5 19.0

PM10 NAA 0.18 0.17 6.74 2.49 1.3 1.2 50.5 19.0

3.5.2 Agricultural activities

3.5.2.1 Tilling

Tillage emissions were estimated using the tillage emission factor equation and Maricopa County 

specific soil silt content for agricultural land (URS and ERG, 2001). The majority of planted 

acres were obtained from the 2008 Arizona Agricultural Statistics Bulletin (AASS, 2009). 

Planted acres for potatoes and sorghum for grain were obtained from the USDA National Agricultural Statistics Service for 2008 (USDA, 2008b) and vegetables and citrus acreage were 

obtained from the 2007 Census of Agriculture (USDA, 2007a). Crop-specific annual land preparation operations data were obtained from the Technical Support Document for Quantification of 

Agricultural Best Management Practices (URS and ERG, 2001). The agricultural tillage emission factor was calculated as follows:

EF = k (4.8) s

0.6

where:

EF = Agricultural emission tillage factor (lbs PM10/acre-pass)

k = Particle size multiplier (value of 0.15 for PM10)

s = Silt content of soil (%) = 35.2% (URS and ERG, 2001)

Thus: EF = 0.15 × 4.8 × (35.2)0.6

= 6.10 lbs PM10/acre-pass
2008 Maricopa Co. PM10 Emission Inventory 61 June 2011 

Annual PM10 emissions from agricultural tillage were calculated for each crop category using the 

following equation (URS and ERG, 2001; Pollack et al., 2003):

TillageCrop = EF × APCrop × ACrop

where:

TillageCrop = Annual PM10 emissions from tilling each crop type (lbs)

EF = Tillage emission factor (lbs PM10/acre-pass)

APCrop = Number of tillage passes per crop (passes)

ACrop = Total number of tilled acres for each crop type (acres)

For example, annual PM10 emissions from cotton tilling were calculated using:

EF = 6.10 lbs PM10/acre-pass

APcotton = 8.8 tillage passes for a cotton crop

APcotton = 19,300 acres cotton

Thus:

Tillagecotton = 6.10 × 8.8 × 19,300

= 1,036,024 lbs/yr

= 518.01 tons/yr

Table 3.5–15 lists crop types and acreage; typical number of land preparation operations and 

acre-passes; and annual uncontrolled PM10 emissions from agricultural tillage for Maricopa 

County.

Table 3.5–15. 2008 crop acreage, activity, and annual uncontrolled PM10 emissions in Maricopa County.

Crop

Acres

Planted

No. of land 

preparation 

operations/yr Acre-passes

Annual uncontrolled 

PM10 emissions (tons/yr)

Cotton 19,300 8.8 169,978 518.43

Corn 11,500 7.3 84,180 256.75

Wheat 30,500 3.1 93,488 285.14

Barley 10,100 2.1 20,856 63.61

Alfalfa (stand establishment)1 21,875 5.1 110,469 336.93

Potatoes 1,400 10.6 14,805 45.16

Sorghum for grain 16,500 3.1 50,575 154.25

Vegetables2 16,072 14.0 224,888 685.91

Citrus3 425 5.0 2,124 6.48

Totals: 127,672 2,352.66

1. Alfalfa is a multi-year crop and alfalfa stand establishment is assumed to occur once every 4 years to approximately 25% of the total alfalfa 

acreage (URS and ERG, 2001).

2. Including melons, not including potatoes.

3. 15 to 20% of citrus orchard acreage is non-bearing in a given year (URS and ERG, 2001); therefore, tillage is assumed to occur in 20% of the 

reported harvested acreage.

In November 2007, the agricultural PM10 general permit (Arizona Administrative Code R18-2-

610 and R18-2-611) was expanded to apply to commercial farming practices within the 

Maricopa County portion of Area A. Previously this rule only applied to the Maricopa County 

PM10 NAA. The agricultural PM10 general permit revisions also resulted in the requirement for 

commercial farmers to implement six agricultural best management practices (BMP) (up from 3 

BMPs) to control PM10 emissions generated from tillage and harvest, non-cropland, and 

cropland. Because no data is available on the additional BMPs being implemented, MCAQD 

used the net control efficiencies from the implementation of agricultural BMPs developed by 
2008 Maricopa Co. PM10 Emission Inventory 62 June 2011 

URS and ERG (2001) in the Technical Support Document for Quantification of Agricultural 

BMPs. URS and ERG quantified three BMPs for tillage: 1) combining tractor operations, 2) 

limited activity during high-wind events, and 3) multi-year crops. URS and ERG (2001) derived 

net control efficiencies by multiplying mid-point BMP control efficiency by a compliance factor 

and a relevancy factor for applicable crops. MCAQD has used the same mid-point BMP control 

efficiency and relevancy factor with a revised compliance factor of 55% (from 80%). The 

revised compliance factor was derived based on latest EPA rule effectiveness guidance (US 

EPA, 2005) which eliminates use of the 80% default rule effectiveness value. (Rule effectiveness 

calculations for agricultural activities are included as Appendix 3). To estimate controlled tillage 

emissions from agricultural operations taking place within the Maricopa County portion of Area 

A, the mid-point net control efficiency for each BMP were applied to 63.09% (the percent of 

agricultural land in the Maricopa County portion of Area A) of the uncontrolled annual 

emissions (MAG, 2009) as follows:

Controlled annual = Annual uncontrolled × (100% – mid-point net × % agricultural land

tillageCrop emissions PM10 emissions control efficiencycrop) in the Area A

Controlled annual = 518.01 tons PM10/yr × (100% – 22.8%) × 63.09%

tillageCotton emissions

= 252.30 tons PM10/yr

The uncontrolled portion of tillage emissions from agricultural operations taking place outside 

Area A but within Maricopa County were estimated by multiplying the uncontrolled annual 

PM10 emissions by the percentage of agricultural land located within Maricopa County but 

outside of Area A (100% – 63.09%) as follows:

Uncontrolled annual = Uncontrolled annual × 36.91%

tillageCrop emissions PM10 emissions

= 518.01 tons PM10/yr × 36.91%

= 191.20 tons PM10/yr

Controlled and uncontrolled emissions were then summed to estimate total annual PM10 emissions from agricultural tillage in Maricopa County. Annual PM2.5 emissions from agricultural 

tillage were calculated by multiplying the annual PM10 emissions by a conversion factor of 0.15 

(WRAP, 2006b). Annual PM10 and PM2.5 emissions from agricultural tillage in Maricopa 

County and Area A are shown in Table 3.5–16.
2008 Maricopa Co. PM10 Emission Inventory 63 June 2011 

Table 3.5–16. Annual emissions from agricultural tillage in Maricopa County and Area A (tons/yr).

Net 

control 

efficiency

Area A 

(controlled)

Outside

Area A 

(uncontrolled)

Maricopa Co. (Area 

A + outside Area A)

Crop (%) PM10 PM2.5 PM10 PM10 PM2.5

Cotton 22.8% 252.36 37.85 191.35 443.72 66.56

Corn 22.8% 124.98 18.75 94.77 219.75 32.96

Wheat 22.8% 138.80 20.82 105.24 244.04 36.61

Barley 22.8% 30.96 4.64 23.48 54.44 8.17

Alfalfa (stand establishment) 13.8% 183.23 27.49 124.36 307.60 46.14

Potatoes 16.8% 21.98 3.30 16.67 38.65 5.80

Sorghum for grain 22.8% 75.09 11.26 56.94 132.02 19.80

Vegetables 16.8% 359.82 53.97 253.17 612.99 91.95

Citrus 16.8% 3.40 0.51 2.39 5.79 0.87

Totals: 1,190.63 178.59 868.37 2,059.00 308.85

*Includes melons, excludes potatoes.

Annual PM10 emissions from agricultural tillage in the PM10 NAA were calculated in the same 

manner as the annual PM10 emissions for the Maricopa County portion of Area A; the only difference being the percent of agricultural land located within the Maricopa County PM10 NAA is 

44.14% (rather than 63.09% for Area A). Results are shown in Table 3.5–17.

Table 3.5–17. Annual emissions from agricultural tillage in the PM10 NAA (tons/yr).

Net Control 

Efficiency

Fraction of 

Ag Land in 

PM10 NAA

annual emissions

Crop (%) PM10 NAA PM10 PM2.5

Cotton 22.8% 44.14% 176.56 26.48

Corn 22.8% 44.14% 87.44 13.12

Wheat 22.8% 44.14% 97.11 14.57

Barley 22.8% 44.14% 21.66 3.25

Alfalfa (stand establishment) 13.8% 44.14% 128.20 19.23

Potatoes 16.8% 44.14% 16.57 2.49

Sorghum for grain 22.8% 44.14% 52.53 7.88

Vegetables 16.8% 44.14% 251.75 37.76

Citrus 16.8% 44.14% 2.38 0.36

Totals: 834.20 125.13

Typical daily emissions for Maricopa County, Area A, and the PM10 NAA were calculated by 

dividing the annual emissions by estimated days per year of tillage operation by crop. The 

number of days of tillage operations was estimated using the calendar of tillage operations by 

crop in the Technical Support Document for Quantification of Agricultural BMPs (URS and 

ERG, 2001) and assuming tillage activities occur 7 days per week during the months of tillage 

operations. Results are shown in Table 3.5–18. The calendar of tillage operations did not 

include months of tillage operations for citrus, thus, a conservative estimate of three (3) months 

per year was assumed.
2008 Maricopa Co. PM10 Emission Inventory 64 June 2011 

Table 3.5–18. Controlled typical daily emissions from tillage (in lbs/day).

Tillage 

operations1

(months/yr)

Tillage 

operations 

(days/yr)

Maricopa County Area A PM10 NAA

Crop PM10 PM2.5 PM10 PM2.5 PM10 PM2.5

Cotton 12 364 2,438.0 365.7 1,386.6 208.0 970.1 145.5

Corn 5 152 2,897.8 434.7 1,648.1 247.2 1,153.1 173.0

Wheat 8 243 2,011.3 301.7 1,143.9 171.6 800.3 120.1

Barley 8 243 448.7 67.3 255.2 38.3 178.6 26.8

Alfalfa (stand 

establishment) 3 91 6,760.3 1,014.1 4,027.1 604.1 2,817.5 422.6

Potatoes 6 182 424.7 63.7 241.6 36.2 182.1 27.3

Sorghum for grain 8 243 1,088.1 163.2 618.9 92.8 433.0 64.9

Vegetables 6 182 6,736.2 1,010.4 3,954.1 593.1 2,766.4 415.0

Citrus 3 91 127.2 19.1 37.3 5.6 26.1 3.9

Totals: 22,932.4 3,439.9 13,312.8 1,996.9 9,327.3 1,399.1

1 Source: URS and ERG (2001), Table 3-2, p. 3-5.

3.5.2.2 Harvesting

Harvest emissions were estimated using crop-specific emission factors (CARB, 2003). The 

majority of harvest acres were obtained from the 2008 Arizona Agricultural Statistics Bulletin 

(AASS, 2009). Harvest acres for potatoes were obtained from the USDA National Agricultural 

Statistics Service for 2008 (USDA, 2008b) and vegetables and citrus were obtained from the 

2007 Census of Agriculture (USDA, 2007a). Table 3.5–19 lists the crop types, acres harvested 

and associated PM10 emission factors used to calculate emissions from agricultural harvesting.

Table 3.5–19. Maricopa County harvested acres and emission factors.

Crop

PM10 emission

factor (lb/acre-yr)

2008

Acreage

Cotton 3.4 18,800

Wheat 5.8 30,100

Barley 5.8 9,900

Alfalfa Hay 0.0 83,000

Other Hay 1.68 4,500

Corn 1.68 700

Sorghum for Grain** 5.8 2,200

Potatoes 2.7 1,400

Vegetables* 0.08 16,072

Citrus 0.08 2,124

Total 168,796

*Includes melons, exclude potatoes.

** Assumed same emission factor, control efficiency, and number of harvest days per year as wheat and barley.

Annual PM10 emissions from agricultural harvesting were calculated using the following 

equation:

Uncontrolled annual = EFcrop × ACrop × ton / 2,000 lb

harvestCrop emissions

where:

harvestCrop = harvest emissions for each crop type (tons PM10/yr)

EFCrop = harvest emission factor (lbs PM10/acre)

ACrop = number of harvested acres for each crop type per year

Example:

EFCotton = 3.4 lbs PM10/acre for cotton
2008 Maricopa Co. PM10 Emission Inventory 65 June 2011 

ACotton = 18,800 acres of cotton

Uncontrolled annual = 3.4 lbs PM10/acre ×18,800 acres × 1 ton/2,000 lbs

HarvestCotton Emissions = 31.96 tons PM10/yr

In November 2007, the agricultural PM10 general permit program (Arizona Administrative Code 

R18-2-610 and 611) was expanded to apply to commercial farming practices within the 

Maricopa County portion of Area A. (Previously this requirement had only applied to the 

Maricopa County PM10 NAA.) The agricultural PM10 general permit revisions also resulted in 

the requirement for commercial farmers to implement six agricultural best management practices 

(BMP) (up from 3 BMPs) to control PM10 emissions generated from tillage and harvest, noncropland, and cropland. Because no data is available on the additional BMPs being 

implemented, MCAQD used the net control efficiencies from the implementation of agricultural 

BMPs developed by URS and ERG (2001) in the Technical Support Document for 

Quantification of Agricultural BMPs. URS and ERG quantified two BMPs for harvesting: 1) 

combining tractor operations, and 2) reduced harvest activity. URS and ERG (2001) derived net 

control efficiencies by multiplying mid-point BMP control efficiency by a compliance factor and 

a relevancy factor for applicable crops. MCAQD has used the same mid-point BMP control 

efficiency and relevancy factor with a revised compliance factor of 55% (from 80%). The 

revised compliance factor was derived based on latest EPA rule effectiveness guidance (US 

EPA, 2005) which eliminates use of the 80% default rule effectiveness value. (Rule effectiveness 

calculations for agricultural activities are included as Appendix 3). To estimate controlled 

harvest emissions from agricultural operations taking place within the Maricopa County portion 

of Area A, the mid-point net control efficiency for each BMP were applied to 63.09% of the 

uncontrolled annual emissions (the percent of agricultural land in the Maricopa County portion 

of Area A) (MAG, 2009) as follows:

Controlled annual = annual uncontrolled × (100% – mid-point net × % agricultural land

harvestCrop emissions PM10 emissions control efficiencycrop) in the Maricopa Co.

portion of Area A

Controlled annual

harvestCotton emissions

from within the Maricopa = 31.96 tons PM10/yr ×(100% – 25.6%) × 63.09%

Co. portion of Area A

= 15.01 tons PM10/yr

The uncontrolled portion of harvest emissions from agricultural operations outside the Maricopa 

County portion of Area A but within Maricopa County were estimated by multiplying the 

uncontrolled annual PM10 emissions by the percent of agricultural land located within Maricopa 

County but outside of the Area A (100% – 63.09%) as follows:

Uncontrolled annual = Uncontrolled PM10 × 36.91%

HarvestCotton emission emissions

from outside the Maricopa

Co. portion of Area A = 31.96 tons PM10/yr × 36.91%

= 11.80 tons PM10/yr

The total controlled and uncontrolled annual emissions were then summed to estimate total 

annual PM10 emissions from agricultural harvesting in Maricopa County as follows:
2008 Maricopa Co. PM10 Emission Inventory 66 June 2011 

Total annual harvestCotton = Uncontrolled annual + Controlled annual

emissions for Maricopa harvestCotton emissions harvestCotton emissions

County from outside Area A from within the Maricopa Co. portion of Area A

= 11.80 + 15.01

= 26.81 tons PM10/yr

Annual PM2.5 emissions from agricultural harvesting were calculated by multiplying the annual 

PM10 emissions by a conversion factor of 0.15 (WRAP, 2006c). Annual PM10 and PM2.5

emissions from harvesting in Maricopa Co. and Area A are shown in Table 3.5–20.

Table 3.5–20. Annual emissions from harvesting in Maricopa County and Area A (in tons/yr).

Crop

Net 

control 

efficiency

Maricopa 

Co. 

Uncontrolled 

Area A 

(controlled)

Outside Area 

A 

(uncontrolled)

Maricopa Co. (Area 

A + outside Area A)

(%) PM10 PM10 PM2.5 PM10 PM10 PM2.5

Cotton 25.5% 31.96 15.02 2.25 11.80 26.81 4.02

Wheat 23.5% 87.29 42.15 6.32 32.22 74.37 11.16

Barley 23.5% 28.71 13.86 2.08 10.60 24.46 3.67

Alfalfa Hay 27.6% 0.00 0.00 0.00 0.00 0.00 0.00

Other Hay 27.6% 3.78 1.73 0.26 1.40 3.12 0.47

Corn 23.5% 0.59 0.28 0.04 0.22 0.50 0.08

Sorghum for Grain** 23.5% 6.38 3.08 0.46 2.35 5.44 0.82

Potatoes 23.5% 1.89 0.91 0.14 0.70 1.61 0.24

Vegetables* 23.5% 0.64 0.31 0.05 0.24 0.55 0.08

Citrus 23.5% 0.08 0.04 0.01 0.03 0.07 0.01

Total 161.33 77.39 11.61 59.54 136.93 20.54

*Includes melons, excludes potatoes.

** Assumed same emission factor, control efficiency, and number of harvest days per year as wheat and barley.

Annual PM10 emissions from agricultural harvesting in the PM10 NAA were calculated in the 

same manner as the annual PM10 emissions for the Maricopa County portion of Area A. The 

only difference being the percent of agricultural land located within the Maricopa County PM10

NAA is 44.14% (rather than 63.09% for Area A). Results are shown in Table 3.5–21.

Table 3.5–21. Annual emissions from harvesting in the PM10 NAA (tons/yr).

Crop

Net control 

efficiency

Fraction of 

Ag land in 

PM10 NAA 

(controlled)

(%) PM10 NAA PM10 PM2.5

Cotton 25.5% 44.1% 10.51 1.58

Wheat 23.5% 44.1% 29.49 4.42

Barley 23.5% 44.1% 9.70 1.45

Alfalfa Hay 27.6% 44.1% 0.00 0.00

Other Hay 27.6% 44.1% 1.21 0.18

Corn 23.5% 44.1% 0.20 0.03

Sorghum for Grain** 23.5% 44.1% 2.16 0.32

Potatoes 23.5% 44.1% 0.64 0.10

Vegetables* 23.5% 44.1% 0.22 0.03

Citrus 23.5% 44.1% 0.03 0.00

Total 54.14 8.12

*Includes melons, excludes potatoes.

** Assumed same emission factor, control efficiency, and number of harvest days per year as wheat and barley.
2008 Maricopa Co. PM10 Emission Inventory 67 June 2011 

Typical daily emissions for Maricopa County, Area A, and the PM10 NAA were calculated by 

dividing the annual emissions by the number of harvest days per year and multiplying the result 

by 2000 lbs/ton (URS and ERG, 2001). Because acres harvested were not reported for 

individual vegetables and citrus fruit, an average number of harvest days per year were used for 

vegetables and citrus (116 and 188 harvest days per year, respectively). Results are shown in 

Table 3.5–22.

Table 3.5–22. Typical daily emissions from harvesting, by crop (in lbs/day).

Crop

Harvest 

days/yr

Maricopa County Area A PM10 NAA

PM10 PM2.5 PM10 PM2.5 PM10 PM2.5

Cotton 143 375.0 56.2 210.0 31.5 146.9 22.0

Wheat 60 2,479.0 371.8 1,405.1 210.8 983.0 147.5

Barley 60 815.3 122.3 462.2 69.3 323.3 48.5

Alfalfa Hay 294 0.0 0.0 0.0 0.0 0.0 0.0

Other Hay 294 21.2 3.2 11.7 1.8 8.2 1.2

Corn 91 11.0 1.7 6.2 0.9 4.4 0.7

Sorghum for Grain** 60 181.2 27.2 102.7 15.4 71.8 10.8

Potatoes 70 46.0 6.9 26.1 3.9 18.2 2.7

Vegetables* 116 9.4 1.4 5.3 0.8 3.7 0.6

Citrus 188 0.8 0.1 0.4 0.1 0.3 0.0

Total 3,938.9 590.8 2,229.9 334.5 1,560.0 234.0

*Includes melons, excludes potatoes.

** Assumed same emission factor, control efficiency, and number of harvest days per year as wheat and barley.

3.5.2.3 Travel on unpaved agricultural roads

Resuspended PM10 emissions from travel on unpaved agricultural roads were estimated using an 

unpaved road emission factor derived from AP-42 13.2.2 (US EPA, 2006b). The unpaved road 

emission factor equation is shown below:

Unpaved road emission factor (EF) (lb/VMT) = k (s/12)a (W/3)b

where:

s = surface material silt content = 11.90% (MAG, 2000)

W = mean vehicle weight (tons) = 2.80 (URS and ERG, 2001)

k = 1.5 (PM10 constant; US EPA, 2006b)

a = 0.9 (PM10 constant; US EPA, 2006b)

b = 0.45 (PM10 constant; US EPA, 2006b)

Unpaved road emission factor (lb/VMT) = 1.5 (11.9/12)0.9 (2.8/3)0.45

= 1.444 lb/VMT

Emissions were estimated using farm vehicle activity data obtained from the Technical Support 

Document for Quantification of Agricultural Best Management Practices (URS and ERG, 2001).

URS and ERG (2001) estimated average daily vehicle miles traveled per 1,000 acres to be 49.5 

VMT.

Daily emissions from travel on unpaved agricultural roads were then estimated as follows:

Daily uncontrolled PM10 = unpaved road EF × VMT/1000 acres × 2008 harvested acres
2008 Maricopa Co. PM10 Emission Inventory 68 June 2011 

emissions from ag roads = 1.444 lbs/VMT ×49.5 VMT/1000 acres × 168,796 acres

= 12,065 lbs/day

In November 2007, the agricultural PM10 general permit (Arizona Administrative Codes R18-2-

610 and 611) was expanded to apply to commercial farming practices within the Maricopa 

County portion of Area A. Previously this rule only applied to the Maricopa County PM10 NAA.

The agricultural PM10 general permit revisions also resulted in the requirement for commercial 

farmers to implement six agricultural best management practices (BMP) (up from 3 BMPs) to 

control PM10 emissions generated from tillage and harvest, non-cropland, and cropland. Because 

no data is available on the additional BMPs being implemented, MCAQD used the net control 

efficiencies from the implementation of agricultural BMPs developed by URS and ERG (2001) 

in the Technical Support Document for quantification of Agricultural BMPs.

Two BMPs were quantified for unpaved road travel: 1) access restriction and 2) reduced vehicle 

speed. A 2001 study (URS and ERG, 2001) estimated net control efficiencies by multiplying a 

midpoint BMP control efficiency by a compliance factor and a relevancy factor for applicable 

crops. MCAQD has used the same mid-point BMP control efficiency and relevancy factor with 

a revised compliance factor of 55% (from 80%). The revised compliance factor was derived 

based on latest EPA rule effectiveness guidance (US EPA, 2005) which eliminates use of the 

80% default rule effectiveness value. (Rule effectiveness calculations for agricultural activities 

are included as Appendix 3).

To estimate controlled daily emissions from travel on unpaved agricultural roads within Area A, 

the mid-point net control efficiency for each BMP (0.4% and 11.6 %, respectively) were applied 

to 63.09 % (the percent of agricultural land in Area A) of the uncontrolled daily PM10 emissions 

as follows:

Controlled daily = Daily uncontrolled × (100%-mid-point net × % agricultural land

unpaved ag road PM10 emissions control efficiency) in Area A

emissions within

Area A = 12,065 lbs/day × (100% – 12.0%) × 63.09%

= 6,698.4 lbs/day

The uncontrolled portion of unpaved agricultural road daily emissions outside the Maricopa 

County portion of Area A but within Maricopa County were estimated by multiplying uncontrolled daily PM10 emissions by the percent of agricultural land located within Maricopa County 

but outside of Area A (100% – 63.09%) as follows:

Uncontrolled daily unpaved ag = Uncontrolled PM10 emissions × (100% - 63.09%)

road emissions from outside

of Area A = 12,065 lbs/day × 36.91%

= 4,453 lbs/day

Total controlled and uncontrolled daily emissions were then summed to estimate total daily PM10

emissions from travel on unpaved agricultural roads in Maricopa County as follows:

Total daily unpaved = Uncontrolled daily + Controlled daily

ag road emissions for unpaved ag road emissions unpaved ag road emissions

Maricopa County from outside Area A from within Area A

= 4,453 + 6,698
2008 Maricopa Co. PM10 Emission Inventory 69 June 2011 

= 11,151 lbs PM10/day

Daily PM10 emissions from unpaved agricultural roads in the PM10 NAA were calculated in the 

same manner as the daily PM10 emissions for the Maricopa County portion of Area A. The only 

difference being the percent of agricultural land located within the Maricopa County PM10 NAA 

is 44.14% (rather than 63.09% for Area A). Results are shown in Table 3.5–21.

Annual emissions for Maricopa County, Area A and the PM10 NAA were calculated by multiplying daily emission estimates by 312 (=6 days per week × 52 weeks per year).

Annual and daily PM2.5 emission from travel on unpaved agricultural roads were calculated by 

multiplying the annual and daily PM10 emissions by a conversion factor of 0.10 (WRAP, 2006c).

Annual and daily PM10 and PM2.5 emissions from unpaved agricultural roads are shown in Table 

3.5–23.

Table 3.5–23. Annual and typical daily emissions from travel on unpaved agricultural roads.

Annual emissions 

(tons/yr)

Typical daily emissions 

(lbs/day)

Geographic area PM10 PM2.5 PM10 PM2.5

Maricopa County (Area A + outside Area A) 1,739.52 173.95 11,150.8 1,115.1

Area A (controlled) 1,044.92 104.49 6,698.2 669.8

PM10 NAA (controlled) 731.03 73.10 4,686.1 468.6

3.5.2.4 Cotton ginning

Annual emissions from cotton ginning were derived from annual emission reports from all 

permitted cotton gins in the county. Typical daily emissions were calculated based on the 

operating schedule data reported by surveyed facilities. Annual and typical daily emissions for 

the PM10 nonattainment area were derived based on the location data of the individual facilities.

Table 3.5–24 summarizes annual and typical daily emissions from cotton gins in both Maricopa 

County and the PM10 nonattainment area.

Table 3.5–24. Annual and typical daily emissions from area-source cotton ginning.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 PM10 PM2.5

Maricopa County 17.90 5.11 103.8 29.7

PM10 NAA 4.86 1.39 26.7 7.6

3.5.2.5 Fertilizer application 

Annual NH3 emissions from synthetic nitrogen fertilizers for 2008 were obtained from the US 

EPA 2008 National Emissions Inventory (US EPA, 2010).

In 2005, MCAQD used the CMU Ammonia Model v.3.6 to calculate NH3 emissions from 

synthetic nitrogen fertilizers (MCAQD, 2007). The CMU Ammonia Model used semiannual 

sales data for 2002 from the Association of American Plant Food Control Officials and crop 

calendar information from National Agricultural Statistics Service (NASS) to estimate monthly 
2008 Maricopa Co. PM10 Emission Inventory 70 June 2011 

fertilizer application rates for each county. The activity data in the CMU Ammonia Model v.3.6 

has not been updated and therefore, MCAQD was unable to use the model to calculated 2008 

NH3 emissions. EPA, however, obtained county-level fertilizer consumption data for 2002 and 

2007 from the Fertilizer Institute’s Commercial Fertilizer 2002 and 2007 reports and calculated 

the percent change in county-level fertilizer quantities applied between 2002 and 2007. EPA 

used the percent change in applied fertilizer quantity to grow the fertilizer activity files provided 

with the CMU Ammonia Model v.3.6. EPA then ran the CMU Ammonia Model with the 

updated county-level fertilizer quantities to calculate NH3 emissions. Typical daily NH3

emissions were derived by dividing annual emissions by 366 days/year. Annual and typical 

daily emissions for the PM10 nonattainment area were derived by multiplying the county annual 

and typical daily emissions by the percentage of agricultural land located in the PM10 NAA 

(44.1%). See Section 1.5.2 for a discussion of the land use data used. Annual and typical daily 

NH3 emissions from fertilizer application are shown in Table 3.5–25.

Table 3.5–25. Annnual and typical daily NH3 emissions from fertilizer application.

Maricopa County PM10 NAA

Fertilizer Category

Annual 

Emissions 

(tons/year)

Daily NH3

Emissions 

(lbs/day)

Annual NH3

Emissions 

(tons/year)

Daily NH3

Emissions 

(lbs/day)

Anhydrous ammonia 70.64 386.0 31.18 170.4

Aqueous ammonia 3.75 20.5 1.65 9.0

Ammonium nitrate 0.00 0.0 0.00 0.0

Ammonium sulfate 74.40 406.5 32.84 179.5

Ammonium thiosulfate 0.00 0.0 0.00 0.0

N-P-K (multi-grade nutrient 

fertilizers) 0.00 0.0 0.00 0.0

Calcium ammonium nitrate 0.00 0.0 0.00 0.0

Nitrogen solutions 1,397.66 7637.5 616.93 3371.2

Urea 496.42 2712.7 219.12 1197.4

Diammonium phosphate 2.66 14.6 1.18 6.4

Monoammonium phosphate 71.77 392.2 31.68 173.1

Liquid ammonium 

polyphosphate 38.94 212.8 17.19 93.9

Potassium nitrate 0.95 5.2 0.42 2.3

Miscellaneous 119.24 651.6 52.63 287.6

Total 2,276.43 12,439.5 1,004.82 5,490.8

3.5.3 Livestock

PM10 and PM2.5 emissions estimates were derived using Maricopa County cattle inventory 

estimates for 2008 from Arizona Agricultural Statistics Bulletin (AASS, 2009) and emission 

factor for PM10 for dairy cattle, and feedlot cattle from the California Air Resources Board 

(CARB, 2004). PM2.5 was presumed to be 11% of PM10 per WRAP Fugitive Dust Handbook 

(WRAP, 2006d).

The number of “cattle on feed” was not available from the Arizona Agricultural Statistics 

Bulletin (AASS, 2009) for 2005 through 2008; therefore, 2004 numbers were used. Beef cows 

were excluded from the inventory as information provided by Arizona Agricultural Statistics 

staff (Koong, 2004) indicated that the majority of beef cows that are not on feed are grazed on 

range and pastures. Cattle on feed, milk cows, and other cattle (heifers, steers, bulls, and calves

on dairies and ranches) were included in the PM10 and PM2.5 emission estimates for livestock. 
2008 Maricopa Co. PM10 Emission Inventory 71 June 2011 

The 2008 Maricopa County cattle inventory and applicable PM emission factors are contained in 

Table 3.5–26.

Table 3.5–26. Maricopa County cattle populations and PM emission factors.

Animal type

No. of 

Head

PM10 Emission Factor 

(lb/1000 head/day ) PM2.5:PM10 Ratio

Cattle on feed 5,000 28.9 0.11

Milk cows 100,000 6.7 0.11

Other cattle 58,000 28.9 0.11

Total: 170,000

Typical daily PM10 emissions from livestock in Maricopa County were calculated using the 

following formula:

Typical daily emissions = milk cow inventory (1,000 head) × emission factor (lbs PM10/1,000 head/day)

(lbs/day) from dairy cattle = 100 × 6.7

= 670.0 lbs PM10/day

It was assumed that livestock emissions occur evenly throughout the year. Annual PM10 and 

PM2.5 emissions were derived by multiplying typical daily emissions by 366 days/year.

NH3 emissions from livestock in Maricopa County were estimated by growing the 2005 NH3

emissions by the percentage change in Maricopa County cattle and calve numbers from 2002 to 

2008 (AASS, 2003; AASS, 2009)2

. The cattle and calf populations declined 8.11% from 2002 to 

2008; as shown in Table 3.5–27 below. The estimated 2005 and 2008 NH3 emissions from 

livestock emissions are shown in Table 3.5–28.

Table 3.5–27. Maricopa County cattle inventory for 2002 and 2008.

Maricopa Co. Percentage

2002 2008 Change

All cattle & calves 185,000 170,000 -8.1%

Table 3.5–28. Annual and typical daily NH3 emissions from livestock in Maricopa County.

Annual emissions 

(tons/year)

Typical daily 

emissions (lbs/day)

2005 Emissions 10,429.53 57,148.1

% Change in cattle and calves, 2002 to 2008 –8.11% -8.11%

2008 Emissions 9,583.89 52,514.5

MCAQD determined through GIS analysis of confined animal feeding operation (CAFO) locations and animal numbers in Maricopa County that 57.3% of CAFO animals are located within 

the nonattainment area. Therefore, annual and typical daily emissions for the nonattainment area 

were calculated by multiplying the Maricopa County emission totals by 57.3%.

Table 3.5–29 summarizes the annual and typical daily emissions from livestock for Maricopa 

County and the PM10 nonattainment area.

 2 The 2005 NH3 emissions were calculated using the CMU Ammonia Model (CMU, 2004). The activity levels in 

the CMU model are based on the 2002 Census of Agriculture; therefore, emissions were grown using the percentage 

change in cattle and calve numbers from 2002 to 2008.
2008 Maricopa Co. PM10 Emission Inventory 72 June 2011 

Table 3.5–29. Annual and typical daily emissions from livestock.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NH3 PM10 PM2.5 NH3

Maricopa County 455.80 50.14 9,583.89 2,490.7 274.0 52,514.5

PM10 NAA 260.95 28.70 5,486.90 1,426.0 156.9 30,065.2

3.5.4 Health services: crematories

Emissions from human and animal crematories were calculated from annual emissions inventory 

reports from all crematories located within the county. Typical daily emissions were calculated 

based on the operating schedule data reported by surveyed facilities. Annual and typical daily 

emissions for the PM10 nonattainment area were derived based on the location data of the individual facilities.

Table 3.5–30 summarizes annual and typical daily emissions from crematories in both Maricopa 

County and the PM10 nonattainment area.

Table 3.5–30. Annual and typical daily emissions from crematories.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 NOx SOx PM10 PM2.5 NOx SOx

Maricopa County 0.93 0.62 12.39 1.58 7.0 4.7 93.1 11.9

PM10 NAA 0.93 0.62 12.36 1.58 7.0 4.6 92.6 11.8

3.5.5 Accidental releases

As part of its air quality permit compliance program, MCAQD keeps an “upset log”, for each 

calendar year that records excess emissions and accidental releases at permitted facilities. 

Annual emissions inventory reports also provide for recording of accidental releases. Data from 

these two sources documented the release of 0.01 tons of PM10 and 0.06 tons of NOx for the year 

2008. To be conservative, PM2.5 amounts are assumed to be equal to PM10 amounts. (No 

accidental releases of SOx or NH3 were reported).

Typical daily emissions were calculated by summing reported releases and dividing the total by 

366 days. Emissions in the PM10 nonattainment area were calculated based on locations of 

facilities that reported releases. The resulting estimates are shown in Table 3-5–31 below.

Table 3.5–31. Annual and typical daily emissions from accidental releases.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5* NOx PM10 PM2.5* NOx

Maricopa County 0.01 0.01 0.06 0.1 0.1 0.3

PM10 NAA 0.01 0.01 0.06 0.1 0.1 0.3

* As a conservative estimate, all PM10 emissions are assumed to be PM2.5.

3.5.6 Humans

A literature review by Battye et al. (1994) recommended using a per-capita emission factor 

developed for the National Acid Precipitation Assessment Program (NAPAP) inventory in 1985. 

This factor was applied to MAG population estimates for the county and PM10 nonattainment 
2008 Maricopa Co. PM10 Emission Inventory 73 June 2011 

areas (see section 1.5 for population information). Daily emissions were calculated by dividing 

annual values by 366. The resulting estimates are shown in Table 3-5–32.

Table 3.5–32. Annual and typical daily NH3 emissions from human activity.

Geographic Area Population

Emission factor 

(lbs/ person-yr)

Annual NH3

emissions (tons/yr)

Typical daily NH3

emissions (lbs/day)

Maricopa County 4,279,760 0.55 1,176.93 6,431.3

PM10 NAA 4,297,140 0.55 1,181.71 6,457.5

3.5.7 Leaf blower fugitive dust

Fugitive dust emissions from leaf blowers are the result of blowing loose material from the area 

being cleared by the leaf blowers. Exhaust emissions from gasoline-powered leaf blowers are 

covered under the Nonroad Mobile Sources section of this report (Chapter 4). Fugitive dust 

emission estimates are developed with the use of three sources: EPA’s NONROAD model, 

California Air Resources Board report to legislature on leaf blowers (CARB, 2000), and a recent 

research effort done by the University of Riverside (Fitz et al., 2005).

EPA’s 2008NONROAD model was used to estimate the number of gasoline-powered leaf 

blowers in Maricopa County (n = 109,787), along with the average activity figures for those leaf 

blowers. Total leaf blower population estimates were derived from CARB (2000), which 

estimated that 60% of all leaf blowers sold are electric. Thus assuming the remaining 40% are 

gasoline-powered, the total population was estimated as: 

Total leaf blower population = Gas-powered leaf blower population ÷ 40%

= 109,787 ÷ 0.4

= 274,468 units

The remaining 164,681 units [= 274,468 – 109,787] are thus assumed to be electric-powered.

Fitz et al. (2005) developed emission factors for PM10 and PM2.5 fugitive dust emissions from 

leaf blowers. For this report, the most conservative (highest) emission factors were chosen to 

estimate emissions. Given these two data sources, Table 3.5–33 lists the equipment population 

numbers, activity estimates and emission factors for leaf blowers in Maricopa County.

Table 3.5–33. Leaf blower equipment populations, activity levels and emission factors for Maricopa County.

Leaf blower description Population

Annual activity 

(hrs/yr)

PM10 emission 

factors (mg/m2)

PM2.5 Emission 

factors (mg/m2)

Commercial 2-stroke gasoline 3,345 626 70 30

Commercial 4-stroke gasoline 1,639 626 70 30

Residential 2-stroke gasoline 99,624 10 70 30

Residential 4-stroke gasoline 5,179 10 70 30

Electric 164,681 10 130 40

Total: 274,468 n/a n/a n/a
2008 Maricopa Co. PM10 Emission Inventory 74 June 2011 

CARB (2000) estimates that approximately 1600m2 of surface can be cleared in one hour of leaf 

blower operation. Therefore, annual emission estimates were calculated by using the following 

formula, as in this example for electric leaf blowers:

Annual PM10 emissions = population × activity × emission factor × area covered

from electric leaf blowers (hrs/yr) (mg/m2

) (m2/hr)

= 164,681 × 10 hrs/yr × 130 mg/m2 × 1600 m2/hr

= 342,536,480,000 mg/yr

= 377.24 tons PM10/yr

The activity hours associated with leaf blowers can occur at any time during the year in Maricopa County due to the temperate climate, with no substantial seasonal variation. Therefore, 

typical daily emissions were estimated by dividing annual totals by 366 days per year. Emissions for the PM10 nonattainment area are allocated based on the ratio of population in the 

County to the nonattainment area (see Section 1.5 for information on population). Table 3.5–34

lists annual and daily fugitive emissions from leaf blowers for Maricopa County and the PM10

nonattainment area.

Table 3.5–34. Annual and typical daily emissions from leaf blower fugitive dust.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 PM10 PM2.5

Maricopa County 891.36 336.41 4,870.8 1,838.3

PM10 NAA 894.98 337.78 4,890.6 1,845.8

3.5.8 Offroad recreation vehicles fugitive dust

The EPA NONROAD2008 model estimates exhaust emissions for offroad recreational vehicles. 

These emissions are included in the nonroad emissions category of the 2008 particulate emissions inventory. Particulate emissions are also generated by recreational vehicles traveling on 

unpaved surfaces. For the 2008 periodic inventory, these emissions were estimated by MAG 

using mileage and activity data for offroad recreational vehicles in Maricopa County from the 

NONROAD2008 model. The methodology and assumptions for calculating fugitive dust emissions from offroad recreational vehicles traveling are described in this section.

The EPA NONROAD2008 model provides annual mileage and number of vehicles by county for 

all-terrain vehicles (ATVs), offroad motorcycles (ORMs), and specialty vehicles/carts (SVCs). 

The NONROAD2008 default values for annual mileage and number of vehicles by type for 

Maricopa County in 2008 are shown in Table 3.5–35.

To be consistent with the 2005 Periodic Emissions Inventory for PM10 (MCAQD, 2007), it was 

assumed that 75 percent of the annual travel by offroad recreational vehicles occurs on unpaved 

surfaces inside Maricopa County, with the remaining 25 percent occurring on paved surfaces 

within Maricopa County and paved and unpaved surfaces outside of Maricopa County. The 

product of the mileage, number of vehicles, and 75 percent produces the annual vehicle miles 

traveled (VMT) on unpaved surfaces, shown in Table 3.5–35. Dividing annual VMT totals by 

366 produces a daily estimated offroad recreational vehicle travel on unpaved surfaces in 

Maricopa County in 2008.
2008 Maricopa Co. PM10 Emission Inventory 75 June 2011 

Table 3.5–35. 2008 offroad recreational vehicle travel on unpaved surfaces in Maricopa County.

Vehicle Type

Annual 

Mileage

Number of 

Vehicles

2008 Annual 

VMT

2008 Daily 

VMT

ATV 1,608 30,424 36,691,344 100,250

ORM 1,600 7,359 8,830,800 24,128

SVC (Non-Diesel) 65 1,718 83,753 229

SVC (Diesel) 435 150 48,938 134

The VMTs above were multiplied by emission factors for unpaved industrial roads from AP-42 

(US EPA, 2006b), assuming a silt content of 11.9 percent and an average vehicle weight of onehalf of a ton. The resultant PM10 emission factor for ATVs and SVCs is 0.594 pounds per vehicle mile traveled. This emission factor was reduced by 50 percent for ORMs (i.e., 0.297 pounds 

per mile) to account for two wheels generating dust instead of four. Applying the AP-42 equation results in a PM2.5 emission factor for ATVs and SVCs of 0.059 pounds per mile, while the 

comparable PM2.5 emission factor for ORMs is 0.0295 pounds per mile.

The AP-42 emission rates were multiplied by the annual and daily VMTs in Table 3.5–36 to 

obtain uncontrolled fugitive dust emissions in pounds per day and tons per year. The results for 

Maricopa County are shown in Table 3.5–37.

The emissions for the PM10 nonattainment area were derived by applying geographic information 

systems (GIS) to MAG 2009 land use data1 to obtain the acreage of passive open space in the 

PM10 nonattainment area and Maricopa County. Passive open space includes open desert, mountains and washes. The detailed calculations for deriving the PM10 nonattainment area emissions 

are shown below:

Passive Open Space in the PM10 nonattainment area (NAA) = 262,662 acres

Passive Open Space in Maricopa County = 1,476,922 acres

Ratio of Passive Open Space in PM10 NAA vs. Maricopa County = 17.8%

PM10 NAA Emissions = 0.178 × Maricopa County Emissions

Application of the ratio above to Maricopa County emissions produces the uncontrolled annual 

and typical daily PM10 NAA emissions shown in Table 3.5–36. The PM10 and PM2.5 emissions

for all offroad recreational vehicle types (i.e., ATVs, ORMs and SVCs) are summed in this table. 

These uncontrolled emissions do not include the 2008 emission reductions attributed to the committed measures in the MAG 2007 Five Percent Plan.

Table 3.5–36. 2008 uncontrolled emissions from offroad recreational vehicles.

Annual emissions (tons/yr) Typical Daily Emissions (lbs/day)

Geographic Area PM10 PM2.5 PM10 PM2.5

Maricopa County 12,248.11 1,216.56 66,929.6 6,647.9

PM10 NAA 2,180.16 216.55 11,913.5 1,183.3

Two committed measures that reduce emissions from offroad recreational vehicles were quantified in the MAG 2007 Five Percent Plan for PM10 (MAG, 2007). The benefit taken in 2008 for 

these measures in the Five Percent Plan is shown in Table 3.5–37.

 

1. Draft, as of March 24, 2010.
2008 Maricopa Co. PM10 Emission Inventory 76 June 2011 

Table 3.5–37. Benefits of measures that reduce offroad recreational vehicle emissions.

2008 PM10 Emission Reductions

Committed Measures in Five Percent Plan tons/yr lbs/day

1. Reduce offroad vehicle use in areas with high 

offroad vehicle activity (Measure 19) 140.3 766.5

2. Ban ATV use on high pollution days (Measure 23) 25.7 140.6

Total 2008 PM10 emission reductions for offroad recreational vehicles 166.0 907.0

The emission benefits in Table 3.5–37 were subtracted from the uncontrolled PM10 emissions in 

Table 3.5–36. The 2008 PM10 emission reduction of 166.0 tons per year represents 7.6% of the 

uncontrolled emissions in the PM10 NAA of 2,180.16 tons per year. This percent reduction was 

applied to the uncontrolled PM2.5 emissions in the PM10 NAA; then the absolute reduction in 

PM2.5 emissions due to the control measures was applied to the uncontrolled PM2.5 emissions in 

Maricopa County. The annual and daily controlled emission estimates are shown in Table 3.5–

38 below.

Table 3.5–38. 2008 controlled emissions from offroad recreational vehicles. 

Annual Emissions (tons/yr) Typical Daily Emissions (lbs/day)

Geographic Area PM10 PM2.5 PM10 PM2.5

Maricopa County 12,082.12 1,200.11 66,022.5 6,558.0

PM10 NAA 2,014.17 200.09 11,006.4 1,093.4

3.5.9 Unpaved parking lots fugitive dust

Fugitive dust emissions from vehicles traveling on unpaved parking lots were developed by 

MAG based on land area devoted to unpaved parking lots, vehicle activity on unpaved parking 

lots, and emission rates from AP-42 (US EPA, 2006b). The methodology, assumptions and 

calculations involved in estimating fugitive dust from vehicles traveling on unpaved parking lots 

are described in this section.

The vehicle miles traveled on unpaved parking lots in the PM10 nonattainment area (NAA) were

derived using assumptions from the Phase I windblown dust modeling for the Western Regional 

Air Partnership (ENVIRON, 2004). This study estimated that eight percent of the vacant land in 

core urban areas is disturbed and thirty percent of the land under development is disturbed. For 

the 2008 periodic emissions inventory, the core urban area is defined as the carbon monoxide 

maintenance area. In addition, the thirty percent of disturbed land under development has been 

reduced by two-thirds (i.e., from thirty percent to ten percent) to mirror a 67 percent decline in 

total permitted construction acreage in the PM10 NAA between 2005 and 2008. GIS was applied 

to 2009 MAG land use data2 to estimate that there are 171,785 acres of vacant land in the core 

urbanized area and 64,519 acres of land under development in the PM10 NAA. Multiplying the 

vacant disturbed percentages by these land areas produces:

171,785 acres × 0.08 = 13,743 acres of vacant disturbed land in the urbanized core

64,519 acres × 0.10 = 6,452 acres of vacant disturbed land under development

Summing the vacant disturbed acres in the urbanized core and areas under development produces 

a total of 20,195 acres of vacant disturbed land in the PM10 NAA. In estimating fugitive dust 

emissions from unpaved parking lots, the MAG Serious Area PM10 Plan assumed that 24 percent 

 

2. Ibid.
2008 Maricopa Co. PM10 Emission Inventory 77 June 2011 

of the disturbed vacant non-agricultural land is devoted to unpaved parking areas (MAG, 2000). 

Applying this percentage to the acres of vacant disturbed land results in 4,847 acres of unpaved 

parking lots in the PM10 NAA.

The MAG Serious Area PM10 Plan also assumed that the average size of an unpaved parking lot 

is 625 square meters (i.e., 0.154 acres), an average of ten vehicles travel on each lot per day, and 

each vehicle travels an average distance of 0.031 miles on a lot. Multiplying 10 vehicles per day 

times 0.031 miles per vehicle and dividing by 0.154 acres produces 2.0 vehicle miles of travel 

(VMT) per acre per day. Multiplying 2.0 by 4,847 acres yields 9,694 VMT per day on unpaved 

parking lots in the PM10 NAA.

The emission factors for unpaved parking lots were derived from the AP-42 equation for 

unpaved industrial roads (US EPA, 2006b), assuming a silt content of 11.9 percent and an 

average vehicle weight of 3.18 tons. The resultant AP-42 emission factors are 1.365 pounds per 

mile for PM10 and 0.137 pounds per mile for PM2.5.

These AP-42 emission factors were applied to the unpaved parking lot VMT of 9,694 to obtain 

uncontrolled emissions in pounds per day. The pounds per day were converted to tons per year, 

assuming 366 days in 2008. The results for the PM10 NAA are shown in Table 3.5–40.

To estimate emissions for Maricopa County, GIS was applied to 2009 MAG land use data3 to 

obtain 2,227,981 acres of vacant land in Maricopa County. Removing the vacant land in the 

Maricopa County portion of the PM10 NAA (i.e., 466,553 acres) results in 1,761,428 vacant acres 

located inside Maricopa County, but outside the PM10 NAA.

Assuming one percent of the vacant land outside the PM10 NAA is disturbed (Clark County, 

2006) and 24 percent of the disturbed vacant land is unpaved parking areas (MAG, 2000), results 

in 4,227 acres of unpaved parking areas inside Maricopa County, but outside the PM10 NAA. 

Multiplying by 2.0 VMT per acre per day results in 8,454 VMT per day. Applying the AP-42 

emission rates produces the unpaved parking lot emissions inside Maricopa County, but outside 

the PM10 NAA of 11,539.7 pounds per day of PM10 and 1,158.2 pounds per day of PM2.5.

The final step in estimating Maricopa County emissions requires removing the Pinal County 

portion of the PM10 NAA. The unpaved parking lot emissions in the Pinal County portion of the 

PM10 NAA are assumed to be proportional to the acres of vacant land. These were derived using 

GIS and 2009 MAG land use data4, with the results shown below:

Vacant land in the Pinal County portion of the PM10 NAA = 6,278 acres

Vacant land in the PM10 NAA = 472,831 acres

Ratio = 6,278/472,831 = 1.3%; Pinal County portion = 1.3% × PM10 NAA emissions

Pinal County portion of PM10 emissions = 1.3% × 13,232.3 = 172.0 pounds per day

Pinal County portion of PM2.5 emissions = 1.3% × 1,158.2 = 17.3 pounds/day

Adding the emissions inside and outside the PM10 NAA and subtracting the Pinal County portion 

produces total Maricopa County emissions attributable to vehicles traveling on unpaved parking 

 

3. Ibid.

4. Ibid.
2008 Maricopa Co. PM10 Emission Inventory 78 June 2011 

lots in pounds per day. Pounds per day were multiplied by 366 [= no. days in 2008] to derive 

annual totals. The resultant 2008 uncontrolled emissions for Maricopa County are shown in 

Table 3.5–39. Uncontrolled emissions do not include the 2008 emission reductions attributed to 

the committed measure in the MAG 2007 Five Percent Plan.

Table 3.5–39. 2008 uncontrolled emissions from vehicles traveling on unpaved parking lots.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 PM10 PM2.5

Maricopa County 4,501.80 451.83 24,600.0 2,469.0

PM10 NAA 2,421.51 243.04 13,232.3 1,328.1

One committed measure that reduces emissions from unpaved parking lots was quantified in the 

MAG 2007 Five Percent Plan for PM10 (MAG, 2007). The benefit taken in 2008 for this 

measure in the Five Percent Plan is shown in Table 3.5–40.

Table 3.5–40. Benefits of measure that reduces unpaved parking lot emissions.

2008 PM10 emission 

reduction

Committed Measure in Five Percent Plan tons/yr lbs/day

1. Pave or stabilize existing unpaved parking lots (Measure 25) 56.4 308.4

The emission benefit in Table 3.5–40 was subtracted from the uncontrolled PM10 emissions in 

Table 3.5–39. The 2008 PM10 emission reduction of 56.4 tons per year represents 2.3% of the 

uncontrolled emissions in the PM10 NAA of 2,421.51 tons per year. This percent reduction was 

applied to the uncontrolled PM2.5 emissions in the PM10 NAA; then the absolute reduction in 

PM2.5 emissions due to the control measure was applied to the uncontrolled PM2.5 emissions in 

Maricopa County. The annual and daily controlled emission estimates are shown in Table 3.5–

41 below.

Table 3.5–41. Annual and typical daily controlled emissions from unpaved parking lots.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM10 PM2.5 PM10 PM2.5

Maricopa County 4,445.36 446.24 24,291.6 2,438.5

PM10 NAA 2,365.07 237.45 12,923.9 1,297.5
2008 Maricopa Co. PM10 Emission Inventory 79 June 2011 

3.5.10 Windblown dust

Windblown dust emissions were calculated using a combination of local meteorology conditions, 

land use and vertical flux emission rates. A full description of the methodology can be found in 

Appendix 4. Tables 3.5–42 and 3.5–43 summarize annual and typical daily emissions from windblown dust by major land use category for Maricopa County and the PM10 nonattainment area.

Table 3.5–42. Annual and typical daily emissions from fugitive windblown dust for Maricopa County.

Annual Emissions (tons/yr) Avg. Daily Emissions (lb/day)

Land Use Category PM10 PM2.5 PM10 PM2.5

Active open space 215.94 32.39 1,180.0 177.0

Agriculture – active 61.69 9.25 337.1 50.6

Agriculture – inactive 345.86 51.88 1,890.1 283.5

Auto test tracks 49.23 7.38 269.0 40.4

Developing 394.98 59.25 2,158.4 323.8

Landfill 6.33 0.95 34.6 5.2

Mining 25.37 3.81 138.7 20.8

Passive open space / wash 2,755.11 413.27 15,058.1 2,258.7

Sand & gravel 108.47 16.27 592.7 88.9

Vacant 2,846.15 426.92 15,555.8 2,333.4

Total 6,809.13 1,021.37 37,214.6 5,582.2

Table 3.5–43. Annual and typical daily emissions from fugitive windblown dust for the PM10 NAA.

Annual Emissions (tons/yr) Avg. Daily Emissions (lb/day)

Land Use Category PM10 PM2.5 PM10 PM2.5

Active open space 213.93 32.09 1,169.0 175.4

Agriculture – active 57.82 8.67 315.9 47.4

Agriculture – inactive 296.42 44.46 1,619.8 243.0

Auto test tracks 42.93 6.44 234.6 35.2

Developing 391.00 58.65 2,136.6 320.5

Landfill 6.33 0.95 34.6 5.2

Mining 23.75 3.56 129.8 19.5

Passive open space / wash 1,822.61 273.39 9,959.6 1,493.9

Sand & gravel 107.82 16.17 589.2 88.4

Vacant 1,852.19 277.83 10,121.2 1,518.2

Total 4,814.80 722.22 26,310.4 3,946.6
2008 Maricopa Co. PM10 Emission Inventory 80 June 2011 

3.5.11 Summary of all miscellaneous area sources

Tables 3.5–44 and 3.5–45 provide a summary of annual and typical daily emissions from all 

miscellaneous area sources, for Maricopa County and the PM10 nonattainment area, respectively.

Table 3.5–44. Annual and typical daily emissions from all miscellaneous area sources for Maricopa County.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Source Category PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Wildfires 470.39 403.43 103.79 28.46 21.76 6,271.8 5,379.0 1,383.8 379.4 290.2

Prescribed fires 0.51 0.51 0.39 0.11 0.03 169.3 169.3 131.2 36.0 10.6

Structure fires 15.04 15.04 1.95 82.2 82.2 10.7

Vehicle fires 30.04 30.04 1.20 164.1 164.1 6.6

Engine testing 0.18 0.17 6.74 2.49 1.3 1.2 50.5 19.0

Tilling 2,059.00 308.85 22,932.4 3,439.9

Harvesting 136.93 20.54 3,938.9 590.8

Unpaved ag roads 1,739.52 173.95 11,150.8 1,115.1

Cotton ginning 17.90 5.11 103.8 29.7

Fertilizer 2,276.43 12,439.5

Livestock 455.80 50.14 9,583.89 2,490.7 274.0 52,514.5

Crematories 0.93 0.62 12.39 1.58 7.0 4.7 93.1 11.9

Accidental releases 0.01 0.01 0.06 0.1 0.1 0.3

Humans 1,176.93 6,431.3

Leaf blowers dust 891.36 336.41 4,870.8 1,838.3

Offroad rec. veh. dust 12,082.12 1,200.11 66,022.5 6,558.0

Unpaved parking lots 4,445.36 446.24 24,291.6 2,438.5

Windblown dust 6,809.13 1,021.37 37,214.6 5,582.2

Total: 29,154.21 4,012.53 126.52 32.64 13,059.05 179,712.0 27,667.0 1,676.1 446.4 71,686.1

Table 3.5–45. Annual and typical daily emissions from all miscellaneous area sources for the PM10 NAA.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Source Category PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Wildfires 423.56 363.27 93.46 25.62 19.60 9,412.5 8,072.7 2,076.8 569.4 435.5

Prescribed fires 0.21 0.21 0.16 0.04 0.01 104.0 104.0 80.6 22.1 6.5

Structure fires 15.10 15.10 1.96 82.5 82.5 10.7

Vehicle fires 30.16 30.16 1.21 164.81 164.81 6.59

Engine testing 0.18 0.17 6.74 2.49 1.3 1.2 50.5 19.0

Tilling 834.20 125.13 9,327.3 1,399.1

Harvesting 54.14 8.12 1,560.0 234.0

Unpaved ag roads 731.03 73.10 4,686.1 468.6

Cotton ginning 4.86 1.39 26.7 7.6

Fertilizer 1,004.82 5,490.8

Livestock 260.95 28.70 5,486.90 1,426.0 156.9 30,065.2

Crematories 0.93 0.62 12.36 1.58 7.0 4.6 92.6 11.8

Accidental releases 0.01 0.01 0.06 0.1 0.1 0.3

Humans 1,181.71 6,457.5

Leaf blowers dust 894.98 337.78 4,890.6 1,845.8

Offroad rec. veh. dust 2,014.17 200.09 11,006.4 1,093.4

Unpaved parking lots 2,365.07 237.45 12,923.9 1,297.5

Windblown dust 4,814.80 722.22 26,310.4 3,946.6

Total: 12,444.36 2,143.52 115.94 29.74 7,693.04 81,929.6 18,879.4 2,318.0 622.4 61,982.0
2008 Maricopa Co. PM10 Emission Inventory 81 June 2011 

3.6 Summary of all area sources

Tables 3.6–1 and 3.6–2 summarize the total annual and typical daily emissions from all area 

sources addressed in this chapter, for both Maricopa County and the PM10 nonattainment area, 

respectively.

Table 3.6–1. Summary of annual and typical daily emissions from all area sources in Maricopa County.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Source Category PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Fuel Combustion

Industrial natural gas 30.78 30.78 575.29 2.42 12.70 197.3 197.3 3,687.7 15.5 81.4

Industrial fuel oil 458.79 458.79 6,375.08 609.61 26.25 2,941.0 2,941.0 40,865.9 3,907.8 168.3

Comm./inst. natural gas 66.54 66.54 1,267.11 5.23 4.20 426.5 426.5 8,122.5 33.5 26.9

Comm./inst. fuel oil 224.14 224.14 3,273.40 271.27 8.13 1,436.8 1,436.8 20,983.3 1,738.9 52.1

Residential natural gas 61.75 61.75 763.81 4.88 337.5 337.5 4,173.8 26.6

Residential wood 461.59 429.28 34.69 5.34 4,334.2 4,030.8 325.7 50.1

Residential fuel oil 0.01 0.01 0.25 0.10 0.1 0.1 2.3 0.9

All fuel combustion 1,303.61 1,271.30 12,289.62 898.83 51.27 9,673.4 9,370.0 78,161.3 5,773.3 328.7

Industrial Processes

Chemical manufacturing 187.43 151.42 0.00 0.34 0.03 1,445.8 1,164.5 0.0 2.6 0.6

Commercial cooking 988.99 917.18 5,434.0 5,039.5

Grain processing 20.59 6.71 149.3 49.5

Cold storage 1,678.43 10.759.2

Secondary metal prod. 60.56 52.16 49.73 18.65 .004 442.7 386.2 358.8 142.7 0.0

Mineral processes 192.82 95.47 1,337.7 659.3

Mining & quarrying 181.01 55.20 1,239.2 362.6

Wood product mfg. 217.26 203.25 1,668.6 1,548.3

Rubber/plastic mfg. 140.94 105.96 953.3 698.8

Fabricated metal mfg. 51.48 42.62 4.50 538.1 460.6 28.9

Residential construction 1,845.79 184.58 11,832.0 1,183.2

Commercial construction 4,320.77 432.08 27,697.2 2,769.7

Road construction 2,695.73 269.57 17,280.3 1,728.0

Other construction 194.36 19.44 1,245.9 124.6

Electrical equip mfg. 13.94 9.64 20.45 0.18 31.55 76.9 53.2 112.4 1.1 193.7

ADEQ-permitted

portable sources 59.00 29.50 282.18 88.93 492.9 246.5 2.275.7 721.7

Road travel at

industrial sites 566.30 271.29 3,880.4 1,847.2

Industrial processes NEC 144.60 107.24 10.22 21.49 16.79 953.3 726.4 69.6 137.7 94.6

All Industrial Processes 11,881.57 2,953.30 362.58 129.60 1,731.34 76,667.6 19,048.2 2,816.5 1,005.8 11,077.2

Waste Treatment/disposal

On-site incineration 0.06 0.04 5.01 0.01 0.7 0.4 38.9 0.1

Open burning 111.46 111.46 29.96 902.2 902.2 242.4

Landfills 86.21 75.92 24.11 7.57 486.1 425.4 132.9 41.7

POTWs 1,484.01 8,131.5

Other waste 32.78 16.93 18.39 50.62 224.1 110.9 101.0 278.1

All Waste Treatment/ 

Disposal 230.52 204.35 77.47 58.20 1,484.01 1,613.0 1,438.8 515.3 320.0 8,131.5
2008 Maricopa Co. PM10 Emission Inventory 82 June 2011 

Table 3.6–1. Summary of annual and typical daily emissions from all area sources in Maricopa County.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Category PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Misc. Area Sources

Wildfires fires 470.39 403.43 103.79 28.46 21.76 6,271.8 5,379.0 1,383.8 379.4 290.2

Prescribed fires 0.51 0.51 0.39 0.11 0.03 169.3 169.3 131.2 36.0 10.6

Structure fires 15.04 15.04 1.95 82.2 82.2 10.7

Vehicle fires 30.04 30.04 1.20 164.1 164.1 6.6

Engine testing 0.18 0.17 6.74 2.49 1.3 1.2 50.5 19.0

Tilling 2,059.00 308.85 22,932.4 3,439.9

Harvesting 136.93 20.54 3,938.9 590.8

Unpaved ag roads 1,739.52 173.95 11,150.8 1,115.1

Cotton ginning 17.90 5.11 103.8 29.7

Fertilizer application 2,276.43 12,439.5

Livestock 455.80 50.14 9,583.89 2,490.7 274.0 52,514.5

Crematories 0.93 0.62 12.39 1.58 7.0 4.7 93.1 11.9

Accidental releases 0.01 0.01 0.06 0.1 0.1 0.3

Humans 1,176.93 6,431.3

Leaf blowers dust 891.36 336.41 4,870.8 1,838.3

Offroad rec. veh. dust 12,082.12 1,200.11 66,022.5 6,558.0

Unpaved parking lots 4,445.36 446.24 24,291.6 2,438.5

Windblown dust 6,809.13 1,021.37 37,214.6 5,582.2

All Misc. Sources 29,154.21 4,012.53 126.52 32.64 13,059.05 179,712.0 27,667.0 1,676.1 446.4 71,686.1

TOTAL, ALL AREA 

SOURCES 42,569.90 8,441.49 12,856.18 1,119.27 16,329.74 267,665.9 57,524.0 83,169.2 7,545.5 91,223.5

Table 3.6–2. Summary of annual and typical daily emissions from all area sources in the PM10 NAA.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Category PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Fuel Combustion

Industrial natural gas 30.70 30.70 573.79 2.41 12.66 196.8 196.8 3,678.2 15.5 81.2

Industrial fuel oil 457.60 457.60 6,358.50 608.03 26.19 2,933.3 2,933.3 40,759.6 3,897.6 167.9

Comm./inst. natural gas 66.20 66.20 1,260.65 5.20 4.18 424.4 424.4 8,081.1 33.3 26.8

Comm./inst. fuel oil 223.00 223.00 3,256.70 269.88 8.09 1,429.5 1,429.5 20,876.3 1,730.0 51.8

Residential natural gas 61.73 61.73 763.51 4.87 337.3 337.3 4,172.2 26.6

Residential wood 461.41 429.11 34.67 5.33 4,332.5 4,029.2 325.6 50.1

Residential fuel oil 0.01 0.01 0.25 0.10 0.1 0.1 2.3 0.9

All fuel combustion 1,300.65 1,268.35 12,248.07 895.83 51.11 9,653.8 9,350.6 77,895.2 5,754.1 327.6

Industrial Processes

Chemical manufacturing 186.94 151.03 0.00 0.34 0.03 1,442.0 1161.5 0.0 2.6 0.9

Commercial cooking 993.04 920.94 5,456.3 5,060.1

Grain processing 16.73 5.68 125.3 43.0

Cold storage 1,674.1 10,731.2

Secondary metal prod. 60.56 52.16 49.73 18.65 0.04 442.7 386.2 358.8 142.7 0.0

Mineral processes 187.73 91.92 1,302.8 635.6

Mining & quarrying 156.60 46.81 1,075.7 307.2

Wood product mfg. 216.69 202.72 1,664.3 1,544.3

Rubber/plastic mfg. 140.57 105.68 950.9 697.0

Fabricated metal mfg. 51.35 42.51 4.49 536.7 459.4 28.8

Residential construction 1,692.38 169.24 10,920.3 1,092.0

Commercial construction 4,057.29 405.73 25,897.4 2,589.7

Road construction 2,051.78 205.18 13,156.8 1,315.7

Other construction 162.41 16.24 1,043.9 104.4

Electrical equip mfg 13.94 9.64 20.45 0.18 31.55 76.9 53.2 112.4 1.1 193.7

ADEQ-permitted

portable sources 59.00 29.50 282.18 88.93 492.9 246.5 2,275.7 721.7

Road travel at

industrial sites 472.36 217.08 3,273.9 1,500.1

Industrial processes NEC 136.00 99.12 8.12 21.47 14.10 906.0 681.7 55.4 137.6 79.8

All Industrial Processes 10,655.39 2,771.19 360.48 129.58 1,724.27 68,764.6 17,877.6 2,802.3 1,005.7 11,034.4
2008 Maricopa Co. PM10 Emission Inventory 83 June 2011 

Table 3.6–2 (cont’d). Summary of annual and typical daily emissions from all area sources in the PM10 NAA.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Category PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Fuel Combustion

Waste Treatment/disposal

On-site incineration 0.06 0.04 5.01 0.01 0.7 0.4 38.9 0.1

Open burning 27.67 27.67 7.44 232.6 232.6 62.5

Landfills 60.25 50.78 19.47 6.22 342.4 286.6 107.4 34.3

POTWs 1,494.12 8,164.6

Other waste 32.78 16.93 18.39 50.62 224.1 110.9 101.0 278.1

All Waste Treatment/ 

Disposal 120.77 95.42 50.30 56.85 1,494.12 799.8 630.5 309.9 312.6 8,164.6

Misc. Area Sources

Wildfires 423.56 363.27 93.46 25.62 19.60 9,412.5 8,072.7 2,076.8 569.4 435.5

Prescribed fires 0.21 0.21 0.16 0.04 0.01 104.0 104.0 80.6 22.1 6.5

Structure fires 15.10 15.10 1.96 82.5 82.5 10.7

Vehicle fires 30.16 30.16 1.21 164.81 164.81 6.59

Engine testing 0.18 0.17 6.74 2.49 1.3 1.2 50.5 19.0

Tilling 834.20 125.13 9,327.3 1,399.1

Harvesting 54.14 8.12 1,560.0 234.0

Unpaved ag roads 731.03 73.10 4,686.1 468.6

Cotton ginning 4.86 1.39 26.7 7.6

Fertilizer application 1,004.82 5,490.8

Livestock 260.95 28.70 5,486.90 1,426.0 156.9 30,065.2

Crematories 0.93 0.62 12.36 1.58 7.0 4.6 92.6 11.8

Accidental releases 0.01 0.01 0.06 0.1 0.1 0.3

Humans 1,181.71 6,457.5

Leaf blowers dust 894.98 337.78 4,890.6 1,845.8

Offroad rec. veh. dust 2,014.17 200.09 11,006.4 1,093.4

Unpaved parking lots 2,365.07 237.45 12,923.9 1,297.5

Windblown dust 4,814.80 722.22 26,310.4 3,946.6

All Misc. Sources 12,444.36 2,143.52 115.94 29.74 7,693.04 81,929.6 18,879.4 2,318.0 622.4 42,455.4

TOTAL, ALL AREA 

SOURCES: 24,521.17 6,278.48 12,774.79 1,112.00 10,962.54 161,147.8 46,738.0 83,325.3 7,694.7 61,982.0

3.7 Quality assurance/quality control procedures

Quality assurance and quality control (QA/QC) activities for the area source emissions inventory 

were driven by the goal of creating a comprehensive, accurate, representative and comparable 

inventory of area source emissions for Maricopa County and the nonattainment area. During 

each step of creating, building and reviewing the area source emissions inventory, quality checks 

and assurances were performed to establish confidence in the inventory structure and data.

Area source categories were selected for inclusion in the inventory based on the latest Emission 

Inventory Improvement Program (EIIP) guidance available. EPA’s guidance for area source 

categories included in the draft 2002 National Emission Inventory (NEI) was also evaluated, as 

area source emissions from this inventory will be submitted to EPA for the 2008 NEI. The list of 

area source categories developed based on these guidance documents was modified to fit the 

characteristics of Maricopa County, with some area source categories determined to be insignificant (such as industrial coal combustion and oil and gas production). The 1999 Maricopa 

County Periodic Ozone and Carbon Monoxide Emission Inventories and other regional emission 

inventories were also consulted to confirm the completeness of the area source categories chosen 

for inclusion.

Data for area source emission calculations were gathered from a wide universe of resources.

Whenever applicable, local surveyed data (such as annual emissions report) was used as this data 

best reflects activity in the county and the nonattainment area. When local data was not 
2008 Maricopa Co. PM10 Emission Inventory 84 June 2011 

available, state data from Arizona State agencies (such as the Arizona Department of Transportation) and regional bodies (such as the Western Regional Air Partnership, WRAP) were used. 

National-level data (such as those from the US Census Bureau) was used when no local, state or 

regional data was available. In addition, the most recent EIIP guidance for area sources was 

consulted for direction in determining the most relevant data source for use in emissions calculations.

Emissions calculations for area sources were performed by three air quality planners and one unit 

manager. All area source emission estimates were calculated in spreadsheets to ensure the 

calculations could be verified and reproduced. Whenever possible or available, the “preferred 

method” described in the most recent EIIP guidance documents for area sources was used to 

calculate emissions. Emissions were estimated using emission factors from EIIP guidance, AP42, and local source testing. Local seasonal and activity data were used when available, with 

EPA and EIIP guidance used when no local seasonal or activity data existed. All calculations 

were evaluated to ensure that emissions from point sources were not being double-counted and to 

determine if rule effectiveness applied.

Once area source emission estimates had been produced, several quality control checks were 

performed to substantiate the calculations. Most area source calculations were peer-reviewed by 

two other planners, with all area sources being reviewed by at least one other planner. Peer 

review ensured that all emission calculations were reasonable and could be reproduced.

Sensitivity analyses and computational method checks were performed on area sources when 

emissions seemed to be outside the expected ranges. When errors were found, the appropriate 

changes were made by the author of the calculations to ensure consistency of the emissions 

calculations. The peer-reviewed emissions estimates were combined into a draft area source 

chapter. This draft chapter was read through in its entirety by the unit manager and the three air 

quality planners for final review, with any identified errors corrected by the author of the section.

The draft version of the area source chapter was sent to the Arizona Department of Environmental Quality, the Arizona Department of Transportation, and the Maricopa Association of 

Governments for a quality assurance review. These agencies provided comments which were 

addressed and incorporated into the final area source chapter. Further quality analysis was 

performed by inputting the emission estimates into EPA’s “QA/QC basic format and content 

checker”, prior to submitting the data to the 2008 NEI.

The QA/QC activities described here have produced high levels of confidence in the area source 

emissions estimates detailed in this chapter, and represent the best efforts of the inventory 

preparers.
2008 Maricopa Co. PM10 Emission Inventory 85 June 2011 

3.8 References

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Service, September 2003.

AASS, 2009. 2008 Arizona Agricultural Statistics Bulletin, Arizona Agricultural Statistics 

Service, September 2009.

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ADOC, 2010. Arizona Department of Commerce. Heating Degree Days: Phoenix. Internet 

address: http://www.azcommerce.com/doclib/ENERGY/Degreedays.pdf

ASLD, 2009. Glen Buettner [glenbuettner@azstatefire.org], Forestry Division, Arizona State 

Land Department, Re: 2008 wildland fire data for Maricopa County, e-mail message, April 

20, 2009.

Battye, R., W. Battye, C. Overcash and S. Fudge, 1994. Development and Selection of 

Ammonia Emission Factors, p. 6-3. Prepared for U.S. Environmental Protection Agency, 

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CARB, 2000. A report to the California legislature on the potential health and environmental 

impacts of leaf blowers. February, 2000

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revised January 2003. Internet address: http://www.arb.ca.gov/ei/areasrc/index7.htm.

CARB, 2004. Area Source Methodologies – Section 7.6 (Cattle Feedlot Dust). California Air 

Resources Board, Sacramento, CA. Revised May 2004. Internet address: 

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Sacramento, CA. Internet address

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Clark County, 2001. PM10 State Implementation Plan for Clark County (Nevada), Appendix B: 

Emissions Inventory Methodology, Emission Factors, and Emission Estimates, June 2001, p. 

B-59. Internet address: 

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http://www.co.clark.nv.us/daqem/aq/plans/pm10sip2001.html

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Las Vegas Valley Using Remote Sensing Imagery. Prepared by Environmental Quality 

Management, Inc. and Midwest Research Institute for the Clark County (Nevada) 

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and Life Safety (DFBLS), Re: data request - 2008 fire data for Maricopa County, e-mail 

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Prepared by ENVIRON for the Western Governors’ Association. March 12, 2004.

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federal wildland fire occurrence data downloaded on Aug. 18, 2009.

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chief/conference/ei15/ session5/fitz.pdf
2008 Maricopa Co. PM10 Emission Inventory 86 June 2011 

Koong, 2004. Dennis Koong, Arizona Agricultural Statistical Service, pers. commun. February 

3, 2004.

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Area. Prepared by the Maricopa Association of Governments. December 2007.

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11, 2009.

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MCAQD, and Dena Konopka, MCAQD, November 2006.

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for PM10 for the Maricopa County, Arizona, Nonattainment Area, May 2007, Available at: 

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http://factfinder.census.gov

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Housing Units. 2008 American Community 1-Year Estimates, Fuel oil, kerosene, etc. for 

Maricopa County and Arizona State [Owner occupied and renter occupied]. Internet address: 

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Service, 2007 Census of Agriculture, Volume 1, Chapter 2: County Level Data. Table 32. 

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y_Level/Arizona/index.asp.
2008 Maricopa Co. PM10 Emission Inventory 87 June 2011 

USDA, 2007b. United States Department of Agriculture, National Agricultural Statistics 

Service, 2007 Census of Agriculture, Volume 1, Chapter 2: County Level Data. Table 42. 

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y_Level/Arizona/index.asp.

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Web Applications (FAMWEB), Previous Years ICS-209s. Internet address: 

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Quick Stats, U.S. & All States County Data – Crops, Potatoes, 2008. Available at: 

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Sales for Industrial Use: Distillate Fuel Oil, Residual Fuel Oil, and Kerosene, 2008 (Table 

21)

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Sales for Commercial Use: Distillate Fuel Oil, Residual Fuel Oil, and Kerosene, 2008 (Table 

20)

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Sales/Deliveries to Residential Consumers. Internet address: 

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US EPA, 1997. Compilation of Air Pollution Emission Factors (AP-42). Fifth Ed. Vol. I: 

Stationary Point and Area Sources. Section 13.2.1: Paved Roads. US Environmental 

Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, 

NC.

US EPA, 1998a. Compilation of Air Pollution Emission Factors (AP-42). Fifth Ed. Vol. I: 

Stationary Point and Area Sources. Section 1.4: Natural Gas Combustion. US 

Environmental Protection Agency, Office of Air Quality Planning and Standards, Research 

Triangle Park, NC. Internet address: http://www.epa.gov/ttn/chief/ap42/ch01/final/ 

c01s04.pdf

US EPA, 1998b. Compilation of Air Pollution Emission Factors (AP-42). Fifth Ed. Vol. I: 

Stationary Point and Area Sources. Section 13.2.2: Unpaved Roads. US Environmental 

Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, 

NC.

.

US EPA, 2000. Area Source Category Method Abstract: Vehicle Fires. Emission Inventory 

Improvement Program (EIIP), May 2000. Internet address: 

http://www.epa.gov/ttn/chief/eiip/techreport/volume03/vehclf13.pdf

US EPA, 2001a. Introduction to Area Source Emission Inventory Development. Emission 

Inventory Improvement Program (EIIP) Vol. III, Chap. 1. Prepared by Eastern Research 

Group, Revised Final, Jan. 2001. Internet address: http://www.epa.gov/ttn/chief/eiip/

techreport/volume03/iii01_apr2001.pdf.
2008 Maricopa Co. PM10 Emission Inventory 88 June 2011 

US EPA, 2001b. Residential Wood Combustion. Emission Inventory Improvement Program 

(EIIP) Vol. III, Chap. 2. Revised Final, Jan. 2001. Prepared by Eastern Research Group, Inc. 

for the Area Source Committee, EIIP. Internet address: http://www.epa.gov/ttn/chief/eiip/ 

techreport/volume03/iii02_apr2001.pdf

US EPA, 2001c. Structure Fires. Emission Inventory Improvement Program (EIIP) Vol. III, 

Chap. 18. Revised Final, Jan. 2001. Prepared by Eastern Research Group, Inc. for the Area 

Source Committee, EIIP. Internet address: 

.

http://www.epa.gov/ttn/chief/eiip/techreport/ 

volume03/iii18_apr2001.pdf

US EPA, 2002. Residential Construction – Fugitive Dust. Emission Inventory Improvement 

Program (EIIP) Vol. IX: Particulate Emissions. Internet address: 

.

http://www.epa.gov/ttn/ 

chief/eiip/techreport/volume09/residn3.pdf

US EPA, 2005. Emissions Inventory Guidance for Implementation of Ozone and Particulate 

Matter National Ambient Air Quality Standards (NAAQS) and Regional Haze Regulations. 

USEPA Office of Air Quality Planning and Standards, Research Triangle Park, NC. August 

2005, updated Nov. 2005. Available at: 

.

http://www.epa.gov/ttn/chief/eidocs/eiguid/.

US EPA, 2006a. Documentation for the 2002 Preliminary Nonpoint Source National Emission 

Inventory for Criteria and Hazardous Air Pollutants (Feb. 2006 Version). Appendix A: 

Criteria and HAP Emissions Estimation Methodology, Commercial Cooking, pp. A-16. 

Prepared by E.H. Pechan & Associates, Inc. for Emission Factor and Inventory Group. 

Internet address: 

ftp://ftp.epa.gov/EmisInventory/2002finalnei/documentation/nonpoint/2002nei_final_nonpoi

nt_documentation0206version.pdf

US EPA, 2006b. Compilation of Air Pollution Emission Factors (AP-42). Fifth Ed. Vol. I: 

Stationary Point and Area Sources. Section 13.2.2: Unpaved Roads. November 2006. 

Internet address: http://www.epa.gov/ttn/chief/ap42/ch13/final/c13s0202.pdf

USGS, 2008. United States Geological Survey, GeoMAC (Geospatial Multi-Agency 

Coordination) Wildland Fire Support database. Internet address: http://www.geomac.gov/

USFS, 1993. Cliff Dills, US Forest Service, Payson Ranger Station, Payson AZ, pers. comm.

USFS, 2009. Ronald Sherron [Sherron.Ronald@azdeq.gov], US Forest Service , Re: Data 

Request - 2008 Maricopa County Prescribed Fire Data and Tonto Natl Forest Wildfire Data 

Needed, e-mail message, July 28, 2009.

WGA/WRAP, 2005. 2002 Fire Emission Inventory for the WRAP Region – Phase II. Project 

No. 178-6. Western Governors Association/Western Regional Air Partnership. July 22, 2005.

Tables 5 and 6. Internet address: 

http://www.wrapair.org/forums/fejf/documents/WRAP_2002_PhII_EI_Report_20050722.pdf

WRAP 2006a. Fugitive Dust Handbook. Chapter 3.0 Construction and Demolition, September 

2006. Internet address: http://wrapair.org/forums/dejf/fdh/index.html

WRAP 2006b. Fugitive Dust Handbook. Chapter 2.0 Agricultural Tilling, September 2006. 

Internet address: 

.

http://wrapair.org/forums/dejf/fdh/index.html

WRAP 2006c. Fugitive Dust Handbook. Chapter 10.0 Agricultural Harvesting, September 2006. 

Internet address: 

.

http://wrapair.org/forums/dejf/fdh/index.html

WRAP 2006c. Fugitive Dust Handbook. Chapter 6.0 Unpaved Roads, September 2006. Internet 

address: 

.

http://wrapair.org/forums/dejf/fdh/index.html

WRAP 2006d. Fugitive Dust Handbook. Chapter 13.0 Livestock Husbandry, September 2006. 

Internet address: 

.

http://wrapair.org/forums/dejf/fdh/index.html.
2008 Maricopa Co. PM10 Emission Inventory 89 June 2011 

4. Nonroad Mobile Sources

4.1 Introduction

Nonroad mobile sources are defined as those that move or are moved within a 12-month period 

and are not licensed or certified as highway vehicles. Nonroad mobile sources are vehicles and 

engines that fall under the following categories:

• Agricultural equipment, such as tractors, combines and balers;

• Airport ground support equipment, such as baggage tugs and terminal tractors;

• Commercial equipment, such as generators and pumps;

• Industrial equipment, such as forklifts and sweepers;

• Construction and mining equipment, such as graders, back hoes and trenchers;

• Lawn and garden equipment, such as leaf blowers and lawn mowers;

• Logging equipment (not present in Maricopa County);

• Pleasure craft, such as power boats and personal watercraft;

• Railway maintenance equipment, such as rail straighteners;

• Recreational equipment, such as all-terrain vehicles and off-road motorcycles;

• Underground mining and oil field equipment (not present in Maricopa County);

• Aircraft, such as jet and piston engines; and

• Locomotives, such as switching and line haul trains.

Emission calculations for most nonroad mobile source categories except aircraft, airport ground 

support equipment (GSE) and locomotives were derived using EPA’s NONROAD model, ver. 

2008.1.0 (Core version 2008, April 2009). Aircraft and airport GSE emission estimates were 

made using the Federal Aviation Administration’s EDMS (Emissions Dispersion Modeling 

System) model, ver. 5.1.1. Locomotive emission calculations were derived from surveys of the 

three railroad companies that have operations in the county (Burlington Northern Santa Fe, 

Union Pacific and Amtrak).

County specific temperature and fuel-related inputs are required for the operation of the NONROAD model. Monthly temperature and fuel data were provided by the Arizona Department of 

Weights and Measures. The following table lists the local county inputs used:
2008 Maricopa Co. PM10 Emission Inventory 90 June 2011 

Table 4.1–1. NONROAD model county temperature- and fuel-related inputs.

Month

Temperatures (°F)

Fuel 

RVP 

(psi)

Diesel 

Sulfur 

(ppm)

Gasoline 

Sulfur 

(ppm)

Ethanol (EtOH) Blend

EtOH 

(Vol %)

Market 

Share (%)

Total Oxygen 

Max. Min. Average (wt%)

January 64 45 54.90 8.8 6 35 9.47 100 3.49

February 69 48 58.45 8.4 6 23 9.24 100 3.42

March 79 54 66.84 8.4 7 49 9.18 100 3.41

April 87 61 74.23 7.8 7 23 5.57 100 2.06

May 91 66 78.74 6.8* 6 * 27* 0.00* 0* 0.00*

June 107 80 93.40 6.6 6 25 0.00 0 0.00

July 106 84 95.16 7.0 4 19 0.00 0 0.00

August 104 82 93.16 6.8 6 29 0.00 0 0.00

September 101 79 90.07 6.5 6 35 0.00 0 0.00

October 91 65 78.13 7.9 7 † 25 6.79 100 2.52

November 81 56 68.67 8.4 7 † 15 8.78 100 3.27

December 65 46 56.03 8.3† 7 28† 8.17† 100† 3.03†

* Since measurements were not available, the average of June, July, August and September data was used.

† Since measurements were not available, the average of October, November, January, February, March and April data was used.

EPA recommends adjusting default NONROAD model values (such as equipment population, 

activity levels of equipment, growth factors, etc.) where local data is available, as the default 

values in the model are derived from national averages. The NONROAD model defaults were 

adjusted in the following manner:

• Equipment population numbers and activity levels for commercial lawn and garden 

equipment were adjusted based on 2003 survey results of the commercial lawn and 

garden industry performed by ENVIRON as part of an inventory developed to study the 

impact of visibility impairing pollutants (ENVIRON et al., 2003). Survey results show 

that for most categories of lawn and garden equipment, the equipment populations for 

Maricopa County are significantly lower than EPA default values, while the average 

annual hours of operation for most equipment types are slightly higher than EPA's values. 

Using these new local data results is a considerable decrease in emissions from this 

category, compared with earlier results using EPA default data.

The NONROAD model does not calculate emission values for NH3. Ammonia emission calculations for the NONROAD model were derived by using a multiplier of NOx emissions 

developed by ENVIRON (2003).

Spatial allocation factors were developed (based on EPA guidance documents) to apportion nonroad emissions to the PM10 nonattainment area. The approaches used are described in each 

section of this chapter.

Temporal allocations (used to calculate PM10 average-day emissions) for nonroad equipment 

categories modeled in the NONROAD model come from EPA recommendations on weekday 

and weekend day activity levels for each nonroad equipment category (US EPA, 1999). Table 

4.1–2 lists the weighted activity level allocation fractions for each equipment class for weekdays 

and weekend days. For this report, the most conservative (highest) allocation fraction in each 

nonroad equipment class was used to calculate average-day emissions.
2008 Maricopa Co. PM10 Emission Inventory 91 June 2011 

Table 4.1–2. Default weekday and weekend day activity allocation fractions.

Equipment category Weekday Weekend day

Agricultural 0.1666667 0.0833334

Airport ground support 0.1428571 0.1428571

Commercial 0.1666667 0.0833334

Construction and mining 0.1666667 0.0833334

Industrial 0.1666667 0.0833334

Lawn and garden (residential) 0.1111111 0.2222222

Lawn and garden (commercial) 0.1600000 0.1000000

Logging 0.1666667 0.0833334

Pleasure craft 0.0600000 0.3500000

Railway maintenance 0.1800000 0.0500000

Recreational 0.1111111 0.2222222

4.2 Agricultural equipment

Annual emissions from agricultural equipment in Maricopa County were calculated using EPA’s 

NONROAD model as discussed above. County-wide results are shown in Table 4.2–1.

Table 4.2–1. Annual emissions (tons/yr) from agricultural equipment in Maricopa County.

PM10 PM2.5 NOx SOx NH3

34.27 33.24 365.55 0.14 0.67

Annual emissions for the PM10 nonattainment area were calculated based on EIIP guidance (US 

EPA, 2002) which recommends using the ratio of agricultural land inside the nonattainment area 

to agricultural land inside the county. See Section 1.5.2 for a discussion of land use data used.

PM10 NAA emissions from = Total County PM10 emissions × Agricultural land use allocation factor

agricultural equipment from agricultural equipment

= 34.27 tons × 44.14%

= 15.13 tons PM10 /yr

Table 4.2–2. Annual emissions (tons/yr) from agricultural equipment in the PM10 NAA.

PM10 PM2.5 NOx SOx NH3

15.13 14.67 161.35 0.06 0.30

County average-day emissions were calculated by multiplying annual emissions (generated by 

the NONROAD model) by the most conservative weekday/weekend day activity allocation factor for agricultural equipment listed in Table 4.1–2, and dividing the product by the number of 

weeks (52) in the year (US EPA, 1999), as follows:

Average County PM10 = Annual PM10 × daily activity allocation factor × 2000 ÷ 52

daily emissions emissions for agricultural equipment (lbs/ton) (wks/yr)

(lbs/day) (tons/yr) (week/day)

= 34.27 × 0.166667 × 2000 ÷ 52

= 219.7 lbs/day

Table 4.2–3. Typical daily emissions (lbs/day) from agricultural equipment in Maricopa County.

PM10 PM2.5 NOx SOx NH3

219.7 213.1 2,343.3 0.9 4.3
2008 Maricopa Co. PM10 Emission Inventory 92 June 2011 

PM10 nonattainment area average-day emissions were calculated by multiplying County averageday emissions by the agricultural land use allocation factor:

PM10 NAA average- = Maricopa County PM10 × Agricultural land use allocation factor

day emissions average-day emissions

= 219.7 lbs/day × 44.14%

= 100.4 lbs/day

Table 4.2–4. Typical daily emissions (lbs/day) from agricultural equipment in the PM10 nonattainment area.

PM10 PM2.5 NOx SOx NH3

97.0 94.0 1,034.3 0.4 1.9

4.3 Airport ground support equipment and auxiliary power units

Annual emissions from airport ground support equipment (GSE) and auxiliary power units 

(APUs) at most airports in the county were estimated using the Emissions Dispersion Modeling 

System (EDMS, v. 5.1.1) from the U.S. Federal Aviation Administration (FAA). The model can 

estimate emissions from affiliated ground support equipment (GSE) and auxiliary power units 

(APUs), by using either default equipment profiles, or user-specified data on equipment populations and activity patterns. In most cases, activity data on 2008 aircraft operations and GSE / 

APU usage was obtained from individual airport surveys issued by MAG and/or MCAQD. 

Where survey responses were incomplete or information was otherwise unavailable, activity data 

was estimated using commercially available data, and EDMS default assumptions where appropriate. Further details concerning the modeling input data and results are presented in Section 

4.11 of this report.

For Luke Air Force Base (AFB), emissions estimates for ground support equipment were obtained from a recent base-wide mobile source emissions inventory for calendar year 2008 that 

had recently been completed for the US Air Force (Weston, 2010). Using data on the frequency 

and intensity of usage for each type of equipment, annual emissions were calculated as in the 

following example for a light cart equipped with a diesel engine:

Epol = ELHP × OT × LF × EF / CF

where:

Epol = Annual emissions of a particular pollutant (lb/yr)

ELHP = Maximum horsepower rating of engine (hp) e.g. 10.7 hp

OT = Operating time (hr/yr) e.g. 52,560 hr/yr

LF = Typical load factor that the engine operates (% of max) e.g. 51%

EF = Emission factor (g/hp-hr) e.g. 7.8 g/hp-hr

CF = Conversion factor to convert grams to pounds (453.59 g/lb)

Thus, total annual NOx emissions all similar pieces of this type of GSE was calculated as: 

ENOx = 10.7 (hp) × 52,560 (hrs/yr) × 51% × 7.8 (g/hp-hr) / 453.59 (g/lb)

= 4,932 (lb/yr) / 2,000 (lb/ton) 

= 2.47 tpy
2008 Maricopa Co. PM10 Emission Inventory 93 June 2011 

GSE emissions from the Luke AFB study were added to the EDMS-estimated emissions from 

the other airports in the County. (The Luke study assumed APU usage, and thus emissions, to be 

negligible.) A simplifying assumption was made for all airports; i.e., that activity is spread fairly 

evenly throughout the week and year; thus daily emissions were estimated by dividing annual 

totals by 366 (= days/yr in 2008). Tables 4.3–1 and 4.3–2 below present the totals for all airport 

GSE and APU usage within both Maricopa County and the PM10 nonattainment area, on an 

annual and typical daily basis, respectively. 

Table 4.3–1. Annual emissions (tons/yr) from all airport ground support equipment (GSE) and auxiliary 

power units (APUs).

Maricopa County PM10 nonattainment area

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

GSE 14.92 14.39 497.97 13.62 * 14.72 14.21 490.28 13.42 *

APUs 12.29 12.29 88.76 12.82 * 12.27 12.27 88.68 12.80 *

Total: 27.21 26.68 586.73 26.43 26.99 26.48 578.95 26.22

* At present, EDMS does not include calculation of ammonia emissions from aircraft operations.

Table 4.3–2. Typical daily emissions (lb) from airport GSE and APU usage.

Maricopa County PM10 nonattainment area

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

GSE 81.5 78.7 2,721.1 74.4 * 80.4 77.7 2,679.1 73.3 *

APUs 67.1 67.1 485.0 70.0 * 67.1 67.1 484.6 70.0 *

Total: 148.7 145.8 3,206.1 144.4 147.5 144.7 3,163.7 143.3

* At present, EDMS does not include calculation of ammonia emissions from aircraft operations.

4.4 Commercial equipment

Annual emissions from commercial equipment in Maricopa County were calculated using EPA’s 

NONROAD model, as described in Section 4.1. Annual emissions for the PM10 nonattainment 

area for this category were derived by applying the ratio of industrial employment in the nonattainment area to Maricopa County-level totals, as data on the number of wholesale establishments recommended by EIIP guidance (US EPA, 2002) was not available. See Section 1.5.1 for 

a discussion of the industrial employment data used.

Table 4.4–1. Annual emissions (tons/yr) from commercial equipment usage.

Maricopa County PM10 nonattainment area

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

117.97 112.98 1,395.23 2.40 21.12 117.66 112.69 1,391.61 2.39 21.06

County average-day emissions were calculated by multiplying Maricopa County annual emissions (generated by the NONROAD model) by the most conservative weekday/weekend day 

activity allocation factor for commercial equipment (0.1666667) listed in Table 4.1–2, and 

dividing the product by the number of weeks (52) in the year (US EPA, 1999). PM10 nonattainment area average-day emissions were calculated based on industrial employment ratios as 

described above.

Table 4.4–2. Typical daily emissions (lbs/day) from commercial equipment usage.

Maricopa County PM10 nonattainment area

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

756.2 724.2 8,943.8 15.4 135.4 754.2 722.4 8,920.6 15.3 135.0
2008 Maricopa Co. PM10 Emission Inventory 94 June 2011 

4.5 Construction and mining equipment

Annual emissions from construction and mining equipment in Maricopa County were calculated 

using EPA’s NONROAD model as described in Section 4.1. Annual emissions for the PM10

nonattainment area for this category were derived by applying the ratio of construction employment in the nonattainment area to Maricopa County-level totals as a conservative estimate, as the 

EIIP-recommended allocation factor of total dollar value of construction was unavailable (US 

EPA, 2002). See Section 1.5.1 for a discussion of the employment data used.

Table 4.5–1. Annual emissions (tons/yr) from construction and mining equipment usage.

Maricopa County PM10 nonattainment area

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

1,260.98 1,220.75 14,796.63 6.60 28.10 1,249.88 1,210.00 14,666.42 6.55 27.85

County average-day emissions were calculated by multiplying Maricopa County annual emissions (generated by the NONROAD model) by the most conservative weekday/weekend day 

activity allocation factor for construction/mining equipment (0.1666667) listed in Table 4.1–2, 

and dividing the product by the number of weeks (52) in the year (US EPA, 1999). PM10

nonattainment area average-day emissions were calculated based on population ratios as 

described above.

Table 4.5–2. Typical daily emissions (lbs/day) from construction and mining equipment usage.

Maricopa County PM10 nonattainment area

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

8,083.2 7,825.3 94.850.2 42.3 180.1 8,012.1 7,756.4 94,015.6 42.0 178.5

4.6 Industrial equipment

Annual emissions from industrial equipment in Maricopa County were calculated using EPA’s 

NONROAD model, as described in Section 4.1. Annual emissions for the PM10 nonattainment 

area for this category were derived by applying the ratio of industrial employment in the nonattainment area to Maricopa County-level totals as a conservative estimate, as the number of 

employees in manufacturing recommended by EIIP guidance (US EPA, 2002) was unavailable. 

See Section 1.5.1 for a discussion of the industrial employment data used.

Table 4.6–1. Annual emissions (tons/yr) from industrial equipment usage.

Maricopa County PM10 nonattainment area

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

101.69 98.96 2,593.13 3.22 56.23 101.42 98.71 2,586.39 3.21 56.09

County average-day emissions were calculated by multiplying Maricopa County annual emissions (generated by the NONROAD model) by the most conservative weekday/weekend day 

activity allocation factor for industrial equipment (0.1666667) listed in Table 4.1–2, and dividing 

the product by the number of weeks (52) in the year (US EPA, 1999). PM10 nonattainment area 

average-day emissions were calculated based on industrial employment ratios as described 

above.

Table 4.6–2. Typical daily emissions (lbs/day) from industrial equipment usage.

Maricopa County PM10 nonattainment area

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

651.8 634.4 16,622.7 20.6 360.5 650.1 632.7 16,579.4 20.6 359.5
2008 Maricopa Co. PM10 Emission Inventory 95 June 2011 

4.7 Lawn and garden equipment

Annual emissions from lawn and garden equipment in Maricopa County were calculated using 

EPA’s NONROAD model, as described in Section 4.1. These results reflect revised equipment 

population and usage estimates from survey work done in early 2003 for the Arizona Department 

of Environmental Quality (discussed in further detail in Section 4.1). Annual emissions for the 

PM10 nonattainment area for this category were derived by applying the ratio of population in the 

nonattainment area to Maricopa County-level totals (since data on housing units was unavailable, 

it was not possible to implement the EIIP-recommended calculation approach (US EPA, 2002). 

See Section 1.5.1 for a discussion of the population data used.

Table 4.7–1. Annual emissions (tons/yr) from lawn and garden equipment.

Maricopa County PM10 nonattainment area

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

182.28 168.79 798.14 3.16 19.63 183.02 169.48 801.41 3.17 19.71

County average-day emissions were calculated by multiplying Maricopa County annual emissions (generated by the NONROAD model) by the most conservative weekday/weekend day 

activity allocation factor for lawn and garden equipment (0.1600000 for the commercial segment, 0.2222222 for residential) listed in Table 4.1–2, and dividing the product by 52 (the 

number of weeks in a year; US EPA, 1999). PM10 nonattainment area average-day emissions 

were calculated by applying a population-based ratio as described in Section 4.7 above.

Table 4.7–2. Typical daily emissions (lbs/day) from lawn and garden equipment.

Maricopa County PM10 nonattainment area

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

1,250.1 1,156.9 5,571.5 23.1 144.6 1,255.3 1,161.6 5,594.4 23.2 145.2

4.8 Pleasure craft

Annual emissions from pleasure craft equipment in Maricopa County were calculated using 

EPA’s NONROAD model, as described in Section 4.1. Annual emissions for the PM10 nonattainment area for this category were derived by applying the ratio of water surface area in the 

nonattainment area to Maricopa County-level totals, as recommended by EIIP guidance (US 

EPA, 2002). See Section 1.5.2 for a discussion of the land use data used.

Table 4.8–1. Annual emissions (tons/yr) from pleasure craft equipment.

Maricopa County PM10 nonattainment area

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

9.25 8.54 77.74 0.85 1.73 7.02 6.48 59.03 0.64 1.32

County average-day emissions were calculated by multiplying Maricopa County annual emissions (generated by the NONROAD model) by the most conservative weekday/weekend day 

activity allocation factor for pleasure craft (0.3500000) listed in Table 4.1–2, and dividing the 

product by the number of weeks (52) in the year (US EPA, 1999). PM10 nonattainment area 

average-day emissions were calculated based on water surface area as described above.

Table 4.8–2. Typical daily emissions (lbs/day) from pleasure craft equipment.

Maricopa County PM10 nonattainment area

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

124.5 114.9 1,046.5 11.4 23.3 94.5 87.3 794.6 8.6 17.7
2008 Maricopa Co. PM10 Emission Inventory 96 June 2011 

4.9 Railway maintenance equipment

Annual emissions from railway maintenance equipment in Maricopa County were calculated 

using EPA’s NONROAD model, as described in Section 4.1. Annual emissions for the PM10

nonattainment area for this category were derived by applying the ratio of population in the 

nonattainment area to Maricopa County-level totals, as recommended by EIIP guidance (US 

EPA, 2002). See Section 1.5.1 for a discussion of the population data used.

Table 4.9–1. Annual emissions (tons/yr) from railway maintenance equipment.

Maricopa County PM10 nonattainment area

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

1.13 1.09 9.23 0.00 0.02 1.13 1.10 9.26 0.00 0.02

County average-day emissions were calculated by multiplying Maricopa County annual emissions (generated by the NONROAD model) by the most conservative weekday/weekend day 

activity allocation factor for railway maintenance equipment (0.1800000) listed in Table 4.1–2, 

and dividing the product by the number of weeks (52) in the year (US EPA, 1999). PM10 nonattainment area average-day emissions were calculated based on the population ratio as described 

above.

Table 4.9–2. Typical daily emissions (lbs/day) from railway maintenance equipment.

Maricopa County PM10 nonattainment area

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

7.8 7.6 63.9 0.0 0.1 7.8 7.6 64.1 0.0 0.1

4.10 Recreational equipment

Annual emissions from recreational equipment in Maricopa County were calculated using EPA’s 

NONROAD model, as described in Section 4.1. Annual emissions for the PM10 nonattainment 

area for this category were derived by applying the ratio of passive open space and vacant land 

use in the nonattainment area to Maricopa County-level totals as recommended by EIIP guidance 

(US EPA, 2002). See Section 1.5.2 for a discussion of the land use data used.

Table 4.10–1. Annual emissions (tons/yr) from recreational equipment.

Maricopa County PM10 nonattainment area

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

45.58 41.98 63.80 0.42 2.10 7.68 7.08 10.76 0.07 0.35

County average-day emissions were calculated by multiplying Maricopa County annual emissions (generated by the NONROAD model) by the most conservative weekday/weekend day 

activity allocation factor for recreational equipment (0.2222222) listed in Table 4.1–2, and 

dividing the product by the number of weeks (52) in the year (US EPA, 1999). PM10 nonattainment area average-day emissions were calculated based on land use as described above.

Table 4.10–2. Typical daily emissions (lbs/day) from recreational equipment.

Maricopa County PM10 nonattainment area

PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

389.6 358.8 545.3 3.6 18.0 65.7 60.5 91.9 0.6 3.0
2008 Maricopa Co. PM10 Emission Inventory 97 June 2011 

4.11 Aircraft

Emissions from aircraft operations at the largest civilian airports in Maricopa County were estimated using the Federal Aviation Administration’s Emissions and Dispersion Model (EDMS, 

v. 5.1.1). The EDMS model combines specified aircraft type and activity levels with default 

emission factors in order to estimate annual emissions inventories for a specific airport. The 

model calculates emissions of sulfur oxides (SOx), oxides of nitrogen (NOx), carbon monoxide 

(CO), and volatile organic compounds (VOC), and, for a small subset of aircraft and engine 

types), PM10 and PM2.5 as well. The model also estimates emissions from affiliated ground support equipment (GSE) and auxiliary power units (APUs); these emissions are reported separately 

and are summarized in Section 4.3.

MCAQD surveyed all medium and large airports in Maricopa County to gather data on aircraft 

type and activity level of aircraft operations. Specifically, the number of landing and takeoff 

cycles (LTO’s) or touch and go operations (TGOs), along with information on the types of 

aircraft that comprise the airport’s typical fleet mix, and other operational data, such as typical 

usage patterns of ground support equipment (GSE) and auxiliary power units (APUs), average 

taxi/idle times, etc. Where survey responses were unavailable or incomplete, aircraft activity 

data from publicly accessible databases, such as the FAA’s Air Traffic Activity System 

(ATADS) and Enhanced Traffic Management System Counts (ETMSC), were used. 

All emission estimates in this section have been developed using the EDMS model, with the 

exception of Luke Air Force Base (AFB), whose emissions calculations have been prepared as 

part of a base-wide 2008 mobile source emissions inventory that has recently been completed 

(Weston, 2010). Luke AFB’s emissions reported as ‘aircraft activity’ actually comprise three 

distinct, though related, types of activity: (1) the operation of aircraft stationed at the base, (2) a 

much smaller level of “transient” aircraft traffic within Luke’s airspace, and (3) emissions 

produced during on-wing engine testing – considered a “mobile source” emission category. 

As with all other airports included in this inventory, emissions from ground support equipment 

(GSE) at Luke AFB are addressed in Section 4.3, Airport ground support equipment and 

auxiliary power units.

In addition to the LTOs (and occasional TGO activity) reported by other airports in the area, 

Luke reported two additional, types of aircraft operations: aircraft low fly bys (LFB), and aircraft 

low fly patterns (LFP). Each of these types of operations can be characterized by a distinctive 

combination of the times in mode (TIM); (e.g., approach, taxi in/out, takeoff and climb out.)

Luke AFB’s emissions are not based on the number of LTOs, but rather the aggregate annual 

operational time in modes (TIMs) for all aircraft of similar type. For the F-16, an LTO cycle 

includes five modes of operation: idle (taxi in/out), intermediate, approach, military and afterburner. The F-16 emissions were estimated using the annual TIMs provided by Luke AFB and 

emission factors from military guidance documents.

Table 4.11–1 lists the data sources for each airport’s activity level, as well as fleet mix. The total 

number of aircraft operations in 2008 is also listed. For all airports other than Luke AFB, aircraft emissions were estimated for four aircraft categories:

• Air carriers (abbreviated “AC”): Larger commercial aircraft with at least 60 seats or 

18,000 lbs payload capacity, used for scheduled service to transport passengers and/or 

freight;
2008 Maricopa Co. PM10 Emission Inventory 98 June 2011 

• Air taxis (“AT”): Smaller commercial turbine- or piston-powered aircraft with less than 

60 seats or 18,000 lbs payload capacity; 

• General aviation (“GA”): Aircraft used on an unscheduled basis for recreational flying, 

personal transportation, and other activities, including business travel; and 

• Military (“ML”): Aircraft used to support military operations.

Table 4.11–1. Annual airport operations (by aircraft category), and related data sources.

Airport

Airport 

Code

Operations Data 

Source1

Fleet Mix Data 

Source2

Aircraft 

Type

2008 

Operations

Buckeye Municipal BXK airnav.com Generic GA profile GA 26,535

Chandler Municipal CHD FAA/ATADS FAA/ETMSC AT 2,882

GA 233,713

ML 247

Falcon Field FFZ FAA/ATADS FAA/ETMSC AC 6

AT 3,813

GA 313,448

ML 2,152

Gila Bend Municipal E63 airnav.com Generic GA profile GA 1,768

Glendale Municipal GEU FAA/ATADS, FAA/ETMSC AT 1,873

Survey response GA 134,282

ML 57

Luke Air Force Base LUF [ Emission totals provided by Luke AFB are based on times-in-mode. ]

Phoenix Deer Valley DVT Survey response Survey response, AC 284

FAA/ETMSC AT 6,217

GA 370,003 *

ML 130

Phoenix Goodyear GYR Survey response Survey response, AC 140

FAA/ETMSC AT 1962

GA 169,177 *

ML 6,747

Phoenix-Mesa Gateway IWA FAA/ATADS, FAA/ETMSC AC 3,876

(formerly Williams Survey response AT 5,937

Gateway) GA 211,674

ML 5,939

Phoenix Sky Harbor PHX Survey response Survey response, AC 391,518

FAA/ETMSC AT 77,354

GA 30,868

ML 2,759

Pleasant Valley P48 airnav.com Generic GA profile GA 23,535

Scottsdale SDL FAA/ATADS FAA/ETMSC AT 11,232

GA 179,619

ML 560

Sky Ranch at Carefree 18AZ Survey response Generic GA profile GA 1,515

Stellar Airpark P19 airnav.com Generic GA profile GA 19,528

Wickenburg Municipal E25 Survey responses Generic GA profile GA 6,000

1. FAA/ATADS: Federal Aviation Administration’s Air Traffic Activity Data System (database); http://aspm.faa.gov.

2. FAA/ETMSC: Federal Aviation Administration’s Enhanced Traffic Management System Counts (database); http://aspm.faa.gov.

* includes touch-and-go (TGO) operations levels reported by the airport. 

The following section describes how activity and emissions were estimated for a representative 

airport, Chandler Municipal (CHD). The FAA’s Air Traffic Activity System (ATADS, 

http://www.aspm.faa.gov) provided data on 2008 activity by aircraft type; these results are 

contained in Table 4.11–1. While ATADS reported a total of 233,713 general aviation operations at this airport in 2008, further information on the aircraft types comprising this activity was 
2008 Maricopa Co. PM10 Emission Inventory 99 June 2011 

needed. The FAA’s Enhanced Traffic Management System Counts (ETMSC) database was used 

to “grow” available aircraft-specific operational data as described below.

The ETMSC database on general aviation activity at CHD in 2008 comprises 152 different aircraft types, totaling 3,589 operations, (See Table 4.11–2). To simplify modeling input requirements, this aircraft-specific activity data was ranked in order of decreasing frequency and 

activity data for the most frequently reported aircraft was then grown to represent all general 

aviation (“GA”) activity, as shown in Table 4.11–2 below.

Table 4.11–2. Example showing how most common aircraft-specific activity was grown for EDMS modeling. 

Rank Aircraft Type

ETMSCreported 

operations

% of total 

reported 

operations

Cumulative

Percent

“Grown” 

operations for 

EDMS modeling

1 BE20 - Beech 200 Super King 240 6.7% 21,919

2 BE58 - Beech 58 233 6.5% 21,280

3 PA28 - Piper Cherokee 233 6.5% 21,280

4 C525 - Cessna CitationJet/CJ1 232 6.5% 21,189

5 C182 - Cessna Skylane 182 203 5.7% 31.8% 18,540

6 C172 - Cessna Skyhawk 172/Cutlass 194 5.4% 17,718

7 TBM7 - Socata TBM-7 166 4.6% 15,161

8 R22 - Robinson R-22 Mariner 138 3.8% 12,604

9 BE9L - Beech King Air 90 106 3.0% 9,681

10 BE36 - Beech Bonanza 36 97 2.7% 51.3% 8,859

11 BE55 - Beech Baron 55 90 2.5% 8,220

12 BE35 - Beech Bonanza 35 87 2.4% 7,946

13 C210 - Cessna 210 Centurion 75 2.1% 6,850

14 PA32 - Piper Cherokee Six 73 2.0% 6,667

15 P28R - Cherokee Arrow/Turbo 71 2.0% 62.4% 6,484

16 P46T - Piper Malibu Meridian 67 1.9% 6,119

17 SR22 - Cirrus SR 22 67 1.9% 6,119

18 BE30 - Raytheon 300 Super King Air 65 1.8% 5,936

19 MO20 - Mooney M-20 62 1.7% 5,662

20 C560 - Cessna Citation V/Ultra/Encore 60 1.7% 71.3% 5,480

    

152 XL2 - Liberty XL-2 1 < 0.1% 100.0% (n/a)

Totals: 3,589 233,713

This approach of ranking reported activity, and then growing the most frequently occurring subset of aircraft typically resulted in a set comprised of 10 to 30 aircraft types being modeled for 

each airport/aircraft class combination, representing 60 to 100% of all reported activity. Since 

the EDMS model includes estimates of PM10 emissions only for a relatively small number of

aircraft/engine types, all model output files were reviewed for missing data. For those aircraft/

engine combinations for which the EDMS model indicated zero PM10 emissions, the default EPA 

emission factors listed in Table 4.11–3 (US EPA, 2003) were incorporated into the EDMS output 

data files, and total PM emissions recalculated.

Table 4.11–3. EPA’s default PM10 emission factors for aircraft, by activity type.

Activity type PM10 Emission Factor (lb/LTO)

Air Carrier, Air Taxi, Military 0.60333

General Aviation 0.2367
2008 Maricopa Co. PM10 Emission Inventory 100 June 2011 

Following EPA guidance (US EPA, 2003), PM2.5 emissions were estimated to be 92% of PM10

levels. For ease in modeling computation and the assessment of emissions, all activity was 

assumed to occur evenly throughout the year. Thus, average daily emissions were calculated by 

dividing annual totals by 366 (= days per year in 2008). Tables 4.11–4 and 4.11–5 list the total 

annual emissions and average daily emissions of each airport and aircraft type, and for airports

within and outside the PM10 NAA, respectively.

Table 4.11–4. Annual and average daily emissions, by airport and aircraft type, from airports within the 

PM10 NAA.

Category

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Airport PM10 PM2.5 NOx SOx PM10 PM2.5 NOx SOx

Chandler Municipal AT 0.27 0.27 0.94 0.24 1.5 1.5 5.1 1.3

GA 12.68 11.79 18.51 6.43 69.3 64.4 101.1 35.1

ML 0.04 0.04 0.12 0.02 0.2 0.2 0.6 0.1

Total 12.99 12.10 19.56 6.68 71.0 66.1 106.9 36.5

Falcon Field AC 0.00 0.00 0.00 - 0.0 0.0 0.0 0.0

AT 0.23 0.23 2.94 0.49 1.3 1.2 16.0 2.7

GA 18.49 17.07 14.34 6.16 101.0 93.3 78.3 33.7

ML 0.31 0.29 0.40 0.13 1.7 1.6 2.2 0.7

Total 19.03 17.59 17.67 6.78 104.0 96.1 96.6 37.0

Glendale Municipal AT 1.06 1.05 9.70 2.43 5.8 5.7 53.0 13.3

GA 6.90 6.41 5.51 2.20 37.7 35.0 30.1 12.0

ML 0.01 0.01 0.12 0.02 0.0 0.0 0.6 0.1

Total 8.17 7.66 15.51 4.71 44.6 41.8 84.8 25.7

Luke Air Force Base† ML 62.82 62.82 382.40 31.81 343.3 343.3 2,089.6 173.8

Phoenix Deer Valley AC 0.04 0.04 0.05 0.01 0.2 0.2 0.3 0.1

AT 0.41 0.41 3.97 0.76 2.2 2.2 21.7 4.2

GA 10.10 9.43 62.81 14.61 55.2 51.5 343.2 79.8

ML 0.02 0.02 0.07 0.02 0.1 0.1 0.4 0.1

Total 10.57 9.90 66.91 15.40 57.8 54.1 365.6 84.1

Phoenix Goodyear AC 0.02 0.01 0.36 0.05 0.1 0.1 1.9 0.3

AT 0.19 0.19 1.61 0.28 1.1 1.0 8.8 1.5

GA 0.66 0.66 18.86 5.25 3.6 3.6 103.0 28.7

ML 0.96 0.89 3.66 1.07 5.2 4.8 20.0 5.8

Total 1.83 1.74 24.48 6.64 10.0 9.5 133.8 36.3

Phoenix Sky Harbor 

Intl.

AC 22.38 22.38 1,751.85 185.77 122.3 122.3 9,573.0 1,015.2

AT 4.24 4.02 116.92 17.51 23.2 22.0 638.9 95.7

GA 3.37 3.21 12.81 2.83 18.4 17.6 70.0 15.4

ML 0.45 0.43 23.48 2.34 2.5 2.4 128.3 12.8

30.45 30.05 1,905.06 208.45 166.4 164.2 10,410.2 1,139.1

Phoenix-Mesa 

Gateway Airport

AC 0.16 0.15 13.25 1.72 0.9 0.8 72.4 9.4

AT 0.63 0.62 3.02 0.64 3.4 3.4 16.5 3.5

GA 12.99 12.04 17.41 5.48 71.0 65.8 95.2 29.9

ML 0.58 0.55 26.56 3.14 3.2 3.0 145.1 17.1

14.35 13.36 60.24 10.98 78.4 73.0 329.2 60.0

Pleasant Valley GA 0.36 0.33 1.65 0.34 1.9 1.8 9.0 1.8

Scottsdale AT 1.03 1.02 7.84 1.37 5.7 5.6 42.8 7.5

GA 19.83 18.86 116.13 21.79 108.4 103.1 634.6 119.1

ML 0.08 0.08 0.24 0.06 0.5 0.4 1.3 0.3

20.95 19.96 124.21 23.22 114.5 109.1 678.8 126.9

Skyranch at Carefree GA 0.18 0.17 0.39 0.10 1.0 0.9 2.1 0.5

Stellar Airpark GA 2.31 2.13 2.42 0.97 12.6 11.6 13.2 5.3

PM10 NAA totals: 183.80 177.61 2,620.31 316.00 1,004.3 970.5 14,318.6 1,726.8

† Sum of emissions from the following categories, as reported in Weston (2010): (1) aircraft stationed at Luke AFB, (2) transient aircraft, and 

(3) on-wing aircraft engine testing.
2008 Maricopa Co. PM10 Emission Inventory 101 June 2011 

Table 4.11–5. Annual and average daily emissions, by aircraft type, from airports outside the PM10 NAA.

Facility

Category

Annual emissions (tons/yr) Average daily emissions (lbs/day)

PM10 PM2.5 NOx SOx PM10 PM2.5 NOx SOx

Buckeye Municipal GA 3.14 2.89 2.70 0.97 17.2 15.8 14.8 5.3

Gila Bend Municipal GA 0.21 0.19 0.18 0.06 1.1 1.1 1.0 0.3

Wickenburg Municipal GA 0.77 0.73 2.75 0.61 4.2 4.0 15.0 3.3

Maricopa County totals: 187.91 181.42 2,625.94 317.64 1,026.8 991.4 14,349.4 1,735.8

4.12 Locomotives

Annual emissions from locomotives were calculated based on diesel fuel usage data provided by 

Burlington Northern/Santa Fe Railway (BNSF), Union Pacific Railway (UP) and Amtrak. 

Railway operations from these companies fall into two categories: Class I haul lines and yard/

switching operations. Annual emissions from these two activity categories were calculated by 

multiplying diesel fuel usage by the emission factors listed in Table 4.12–1 (US EPA, 2009).

Table 4.12–1. Emission factors for locomotives.

Activity type

Emission factors (lbs/gal diesel)

PM10 PM2.5 NOx SOx NH3

Class I haul line 0.015 0.014 0.394 0.004 0.0001

Yard/switch operations 0.015 0.014 0.421 0.004 0.0001

The example below illustrates how emissions were calculated for each locomotive activity type. 

Fuel use reported by railroads, and emission totals are summarized in Table 4.12–2.

PM10 emissions from = Diesel use (gals/yr) × PM10 emission factor (lbs/gal) ÷ 2,000 lbs/ton

UP Class I haul lines

= 7,780,284 gals/yr × 0.015 lbs/gal ÷ 2,000 lbs/ton

= 58.35 tons PM10/yr

Table 4.12–2. Total diesel use and annual emissions from locomotives in Maricopa County.

Locomotive type

Diesel use 

(gals/yr)

Annual emissions (tons/yr)

PM10 PM2.5 NOx SOx NH3

BNSF Class I haul line 750,094 5.63 5.25 147.77 1.50 0.36

UP Class I haul line 7,780,284 58.35 54.46 1,532.72 15.56 3.70

BNSF yard/switch operations 400,000 3.00 2.80 84.20 0.80 0.19

UP yard/switch operations 378,199 2.84 2.65 79.61 0.76 0.18

Amtrak 52,416 0.39 0.37 10.33 0.10 0.02

Totals: 9,360,993 70.21 65.53 1,854.62 18.72 4.45

PM10 nonattainment area emissions were calculated by multiplying Maricopa County emissions 

by the percentage of track miles within the PM10 nonattainment area, determined by GIS 

mapping. Results are shown in Table 4.12–3.

PM10 nonattainment area emissions = County PM10 emissions × Percentage of track miles within 

from UP Class I haul lines (tons/yr) (tons/yr) the PM10 nonattainment area

= 58.35 tons PM10/yr × 44.27%

= 25.83 tons PM10/yr
2008 Maricopa Co. PM10 Emission Inventory 102 June 2011 

Table 4.12–3. Annual emissions (in tons/yr) from locomotives in the PM10 NAA.

Locomotive type

Track in 

nonattainment 

area (%)

Annual emissions (tons/yr)

PM10 PM2.5 NOx SOx NH3

BNSF Class I haul line 44.27 2.49 2.32 65.42 0.66 0.16

UP Class I haul line 44.27 25.83 24.11 678.53 6.89 1.64

BNSF yard/switch operations 100.00 3.00 2.80 84.20 0.80 0.19

UP yard/switch operations 100.00 2.84 2.65 79.61 0.76 0.18

Amtrak 0.00 0.00 0.00 0.00 0.00 0.00

Totals: 34.16 31.88 907.76 9.11 2.16

PM10 typical daily emissions for both the county (shown in Table 4.12–4) and the PM10 nonattainment area (Table 4.12–5) were calculated by dividing annual totals by 366 days (since 2008 

was a leap year), as locomotive activity is assumed to be uniform throughout the year.

PM10 typical daily = Annual PM10 emissions (tons) × 2000 lbs/ton ÷ 366 days

emissions from haul lines

= 58.35 tons PM10/yr × 2000 lbs/ton ÷ 366 days

= 318.9 lbs PM10/day

Table 4.12–4. Typical daily emissions (in lbs/day) from locomotives in Maricopa County.

Locomotive type PM10 PM2.5 NOx SOx NH3

BNSF Class I haul line 30.7 28.7 807.5 8.2 1.9

UP Class I haul line 318.9 297.6 8,375.5 85.0 20.2

BNSF yard/switch operations 16.4 15.3 460.1 4.4 1.0

UP yard/switch operations 15.5 14.5 435.0 4.1 1.0

Amtrak 2.1 2.0 56.4 0.6 0.1

Totals: 383.6 358.1 10,134.5 102.3 24.3

Table 4.12–5. Typical daily emissions (in lbs/day) from locomotives in the PM10 nonattainment area.

Locomotive type PM10 PM2.5 NOx SOx NH3

BNSF Class I haul line 13.6 12.7 357.5 3.6 0.9

UP Class I haul line 141.2 131.8 3,707.8 37.6 8.9

BNSF yard/switch operations 16.4 15.3 460.1 4.4 1.0

UP yard/switch operations 15.5 14.5 435.0 4.1 1.0

Amtrak 0.0 0.0 0.0 0.0 0.0

Totals: 186.7 174.2 4,960.4 49.8 11.8
2008 Maricopa Co. PM10 Emission Inventory 103 June 2011 

4.13 Summary of all nonroad mobile source emissions

Table 4.13–1 summarizes annual and daily emissions of PM10, PM2.5, NOx, SOx and NH3 from 

nonroad mobile sources in Maricopa County. Table 4.13–2 shows annual and typical daily emissions for these pollutants for the PM10 nonattainment area.

Table 4.13–1. Annual and typical daily emissions from nonroad mobile sources in Maricopa County.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Category PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Agricultural 34.27 33.24 365.55 0.14 0.67 219.7 213.1 2,343.3 0.9 4.3

Airport GSE 27.21 26.68 586.73 26.43 148.7 145.8 3,206.1 144.4

Commercial 117.97 112.98 1,395.23 2.40 21.12 756.2 724.2 8,943.8 15.4 135.4

Construction & mining 1,260.98 1,220.75 14,796.63 6.60 28.10 8,083.2 7,825.3 94,850.2 42.3 180.1

Industrial 101.69 98.96 2,593.13 3.22 56.23 651.8 634.4 16,622.7 20.6 360.5

Lawn & garden 182.28 168.79 798.14 3.16 19.63 1,250.1 1,156.9 5,571.5 23.1 144.6

Pleasure craft 9.25 8.54 77.74 0.85 1.73 124.5 114.9 1,046.5 11.4 23.3

Railway maintenance 1.13 1.10 9.23 0.00 0.02 7.8 7.6 63.9 0.0 0.1

Recreational 45.58 41.98 63.80 0.42 2.10 389.6 358.8 545.3 3.6 18.0

Aircraft 187.91 181.41 2,625.94 317.64 1,026.8 991.3 14,349.4 1,735.8

Locomotives 70.21 65.53 1,854.62 18.72 4.45 383.6 358.1 10,134.5 102.3 24.3

Totals: 2,038.46 1,959.95 25,166.75 379.58 134.06 13,042.0 12,530.3 157,677.4 2,099.8 890.6

Table 4.13–2. Annual and typical daily emissions from nonroad mobile sources in the PM10 NAA.

Annual emissions (tons/yr) Typical daily emissions (lbs/day)

Category PM10 PM2.5 NOx SOx NH3 PM10 PM2.5 NOx SOx NH3

Agricultural 15.13 14.67 161.35 0.06 0.30 97.0 94.0 1,034.3 0.4 1.9

Airport GSE 26.99 26.48 578.95 26.22 147.5 144.7 3,163.7 143.3

Commercial 117.66 112.69 1,391.61 2.39 21.06 754.2 722.4 8,920.6 15.3 135.0

Construction & mining 1,249.88 1,210.00 14,666.42 6.55 27.85 8,012.1 7,756.4 94,015.6 42.0 178.5

Industrial 101.42 98.71 2,586.39 3.21 56.09 650.1 632.7 16,579.4 20.6 359.5

Lawn & garden 183.02 169.48 801.41 3.17 19.71 1,255.3 1,161.6 5,594.4 23.2 145.2

Pleasure craft 7.02 6.48 59.03 0.64 1.32 94.5 87.3 794.6 8.6 17.7

Railway maintenance 1.13 1.10 9.26 0.00 0.02 7.8 7.6 64.1 0.0 0.1

Recreational 7.68 7.08 10.76 0.07 0.35 65.7 60.5 91.9 0.6 3.0

Aircraft 183.80 177.60 2,620.31 316.00 1,004.3 970.5 14,318.6 1,726.8

Locomotives 34.16 31.88 907.76 9.11 2.16 186.7 174.2 4,960.4 49.8 11.8

Totals: 1,927.89 1,856.17 23,793.26 367.42 128.87 12,275.2 11,811.9 149,537.7 2,030.5 852.9

4.14 Quality assurance procedures

Established procedures were used to check, and correct when necessary, the nonroad mobile 

sources emissions estimates. All NONROAD model input and output files, and Excel spreadsheets used to calculate the emissions, were checked by personnel not involved in developing the 

modeling inputs/outputs and spreadsheets being reviewed. In addition, the emissions estimates 

were reviewed for reasonableness by external agency staff.

4.15 References

ENVIRON et al., 2003. Maricopa County 2002 Comprehensive Emission Inventory for the Cap 

and Trade Oversight Committee, Final Rep. prepared for Arizona Dept. of Environmental 

Quality, Oct. 9, 2003.

ERG, 2001. Documentation for the Draft 1999 Base Year Aircraft, Commercial Marine Vessels, 

and Locomotive National Emissions Inventory for Criteria and Hazardous Air Pollutants. 

Prepared by Eastern Research Group, Morrisville, NC for the US Environmental Protection 

Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC, Oct. 29, 

2001. Available at: http://www.epa.gov/ttn/chief/eidocs/partllsec4.pdf.
2008 Maricopa Co. PM10 Emission Inventory 104 June 2011 

US EPA, 1992. Procedures for Emission Inventory Preparation – Vol. IV: Mobile Sources. 

Office of Air and Radiation, EPA Rep. EPA420-R-92-009, December.

US EPA, 1998. National Air Pollutant Emission Trends Procedures Document, 1900-1996. 

Office of Air Quality Planning and Standards, Rep. EPA-454/R-98-008, Research Triangle 

Park, NC. May.

US EPA, 1999. Weekday and Weekend Day Temporal Allocation of Activity in the NONROAD 

Model. EPA Office of Transportation and Air Quality, Rep. EPA420-P-99-033, March. 

Available at: http://www.epa.gov/otaq/models/nonrdmdl/p99033.pdf

US EPA, 2002. Geographic Allocation of State Level Nonroad Engine Population Data to the 

County Level. EPA Office of Transportation and Air Quality, Rep. EPA420-P-02-009, July. 

Available at: 

.

http://www.epa.gov/otaq/models/nonrdmdl/p02009.pdf

US EPA, 2003. Documentation for the NONROAD Model Criteria Air Pollutant Component of 

the National Emissions Inventory (NEI) for Base Years 1970–2001. Rept. prepared by E.H. 

Pechan & Associates for US EPA Office of Air Quality Planning and Standards, Sept. 2003. 

Available at: 

.

ftp://ftp.epa.gov/EmisInventory/finalnei99ver3/criteria/documentation/nonroad/

nonroad_neimethods.pdf

US EPA, 2010. 2008 National Emissions Inventory, Nonpoint: Fertilizer Application, May 

2010. Internet address: 

.

http://www.epa.gov/ttn/chief/net/2008inventory.html.

US EPA, 2009. Emission Factors for Locomotives. Office of Transportation and Air Quality. 

Rep. EPA420-F-09-025, April 2009. Internet address: http://www.epa.gov/otaq/regs/

nonroad/locomotv/420f09025.pdf

Weston Solutions Inc., 2010. 2008 Mobile Source Air Emissions Inventory for Luke Air Force 

Base. Rept. prepared for Air Education and Training Command (AETC), US Air Force, 

Randolph AFB, TX. June 2010.

.
2008 Maricopa Co. PM10 Emission Inventory 105 June 2011 

5. Onroad Mobile Sources

5.1 Introduction

Onroad mobile source emissions have been calculated for particulate matter for the 2008 

Periodic Emissions Inventory for the Maricopa County area. For the purposes of this particulate 

matter inventory, the following pollutants were included: PM10, PM2.5, nitrogen oxides (NOx), 

sulfur dioxides (SO2), and ammonia (NH3). PM10 refers to all particles less than or equal to 10 

micrometers in diameter and PM2.5 refers to particles less than or equal to 2.5 micrometers in 

diameter.

Onroad mobile source emissions were estimated for the PM10 nonattainment area (NAA) 

(approximately 3,000 sq. mi.), as well as for Maricopa County (approximately 9,000 sq. mi.). 

Emission factors were calculated using the Motor Vehicle Emission Simulator (MOVES2010a)

model, the most recent model developed by the U.S. EPA for the purpose of estimating motor 

vehicle emission factors, and AP-42, which is the EPA Compilation of Air Pollutant Emission 

Factors. AP-42 emission factors were used to calculate fugitive dust emissions, while 

MOVES2010a was used to estimate emissions from exhaust, tire wear, and brake wear.

The MOVES2010a modeling accounted for the oxygenated fuel and the Arizona Vehicle Inspection/Maintenance (I/M) programs applied in Maricopa County in 2008. The fuel use assumptions, including oxygen content and Reid Vapor Pressure (RVP), were derived from the 2008 

fuel inspection results provided by the Arizona Department of Weights and Measures.

In order to develop the 2008 onroad mobile source emissions, the 2008 vehicle miles of travel 

(VMT) estimates by facility type and road type were derived from the 2008 Highway Performance Monitoring System (HPMS) data provided by the Arizona Department of Transportation 

(ADOT). The distribution of VMT by vehicle type is based on the July 2008 vehicle registration 

data for Maricopa County provided by ADOT. The VMT by vehicle type was provided as local 

input data for MOVES2010a to produce onroad exhaust, tire wear, and brake wear emissions.

Paved road fugitive dust emission estimates were derived from the AP-42 equation published by 

EPA in January 2011. The 2008 VMTs for freeways, high traffic arterials, and low traffic 

arterials were derived from the 2008 traffic assignment produced by the MAG travel demand 

model. Low traffic arterials carry less than 10,000 vehicles on an average weekday, while high 

traffic arterials carry 10,000 or more vehicles on an average weekday. These traffic assignment 

VMTs were normalized to 2008 HPMS VMTs and multiplied by the appropriate particulate 

emission factors derived from the AP-42 equation for paved roads. The 2008 benefits of the 

committed measures in the MAG 2007 Five Percent Plan for the Maricopa County PM10 Nonattainment Area (MAG, 2007) were applied to estimate 2008 paved road particulate emissions 

for the PEI.

Unpaved road VMT was derived from the MAG 2009 Unpaved Road Inventory (MAG, 2010). 

Unpaved alley VMT was derived from a GIS analysis of 2009 aerial photographs conducted by 

MAG. The unpaved road and alley VMTs were multiplied by the appropriate AP-42 emission 

factors. The 2008 benefits of the committed measures in the MAG 2007 Five Percent Plan were 

applied to estimate 2008 unpaved road and alley particulate emissions for this inventory.
2008 Maricopa Co. PM10 Emission Inventory 106 June 2011 

The main references for preparing the onroad mobile source portion of the 2008 emissions 

inventory were:

• Emission Inventory Requirements for Ozone State Implementation Plans (EPA, 1991);

• Procedures for Emission Inventory Preparation Volume IV: Mobile Sources (EPA, 

1992a);

• Compilation of Air Pollutant Emissions Factors, AP-42 (EPA, 2006);

• Technical Guidance on the Use of MOVES2010 for Emission Inventory Preparation in 

State Implementation Plans and Transportation Conformity (EPA, 2010a); 

• User’s Guide for the SMOKE-MOVES Integration Tool (EPA, 2010b); and

• Motor Vehicle Emission Simulator (MOVES) - User Guide for MOVES2010a, (EPA, 

2010c).

5.2 Exhaust, tire wear, and brake wear emissions

Vehicle exhaust emission factors for PM10, PM2.5, NOx, SO2, and NH3, as well as tire wear and 

brake wear emission factors for PM10 and PM2.5, were calculated using MOVES2010a. The 

exhaust PM10 and PM2.5 estimates include the components of sulfate and carbon (organic and 

elemental). The MOVES2010a runs were executed by MAG. The contact person for the 

MOVES2010a emission estimates is Ieesuck Jung (602-254-6300).

5.2.1 MOVES2010a model

The emissions not related to fugitive dust were calculated using MOVES2010a, the U.S. EPA’s 

state-of-the-art emissions modeling tool, which replaces EPA’s previous mobile source 

emissions model, MOBILE6.2. MOVES2010a is intended for official use to estimate national, 

state, and county level inventories of criteria air pollutants from highway vehicles. The user of 

MOVES2010a is allowed to specify vehicle types, time periods, geographical areas, pollutants, 

vehicle operating characteristics, and road types for the particular scenario to be modeled by 

creating a Run Specification (RunSpec).

In order to calculate vehicle emissions for the calendar year 2008, MOVES2010a was executed 

using local input data for each month of the year and each geographical area (Maricopa County 

and the PM10 NAA). Each scenario was created using the County Domain/Scale and the Inventory Calculation Type. The specific MOVES2010a model RunSpec and RunSpec summaries are 

described in Appendix 5.

5.2.2 MOVES2010a local input data

Compared with MOBILE6.2, MOVES2010a requires a more detailed level of local data, 

including fuel data, I/M program, meteorological data, vehicle population, source type age 

distribution, annual VMT, monthly/daily/hourly VMT fractions, road type distribution, average 

speed distribution, and ramp fraction.

5.2.2.1 Fuel data

Regarding the fuel local input data, MOVES2010a provides two MOVES tables, which are 

[fuelsupply] and [fuelformulation]. The fuel data for each month were derived from the 2008 

fuel inspection results in Maricopa County provided by the Arizona Department of Weights and 

Measures. The fuel data for Maricopa County were also applied to the PM10 NAA. The specific 

MOVES tables for fuel data are presented in Appendix 5.
2008 Maricopa Co. PM10 Emission Inventory 107 June 2011 

5.2.2.2 I/M programs

MOVES2010a has an [IMCoverage] table for I/M programs; this table was prepared using 

MOBILE6.2 input. This table reflects the actual proportions of vehicles subject to the specified 

levels of inspection. The term “I/M vehicles” denotes vehicles which are required to undergo an 

emission test and/or inspection under the Vehicle Inspection/Maintenance Program. It is important to note that participation in the I/M program is required for all vehicles registered in the 

PM10 NAA, with the exception of certain model years and vehicle classes. However, it is 

assumed that 91.6 percent of the vehicles operating within the PM10 NAA and Maricopa County 

participate in the I/M program and the remaining 8.4 percent do not participate in the program. 

These percentages reflect the control measures “Tougher Enforcement of Vehicle Registration 

and Emissions Test Compliance” and “Expansion of Area A Boundaries,” described in the MAG 

Eight-Hour Ozone Redesignation Request and Maintenance Plan for the Maricopa Nonattainment Area (MAG, 2009). This percentage is directly applied to the Compliance Factor in the 

[IMCoverage] table. The same I/M programs were applied for Maricopa County and the PM10

NAA. The specific MOVES table for I/M programs is presented in Appendix 5.

5.2.2.3 Meteorological data

MOVES2010a requires hourly temperature and relative humidity data by specific month of the 

year. Meteorological data for the Phoenix Sky Harbor International Airport in 2008 were 

obtained from the National Climatic Data Center (http://www7.ncdc.noaa.gov/IPS/lcd/lcd.html?_ 

page=1&state=AZ&wban=23183&_target2=Next+%3E). The same hourly average temperature 

and relative humidity data for each month were applied for Maricopa County and the PM10

NAA. The specific MOVES table [ZoneMonthHour] for meteorological data is presented in 

Appendix 5.

5.2.2.4 Vehicle population

In order to capture start, evaporative, and extended idle emissions, MOVES2010a introduced a 

new mobile source emission category called off-network emissions. In MOVES2010a, these offnetwork emissions are directly determined by the population of vehicles in an area. The vehicle 

population in Maricopa County was obtained from the July 2008 vehicle registration data 

provided by ADOT. The vehicle population data were allocated to the 28 MOBILE6.2 vehicle 

types based on MOBILE6.2 VMT fractions for 2008. Then, the vehicle population data 

allocated to the 28 MOBILE6.2 vehicle types were assigned to the 13 MOVES source types 

using the match-up table (Table A.1) in the EPA’s technical guidance (EPA, 2010a). The 

vehicle population in the PM10 NAA was estimated by applying the population ratio of the two 

geographical areas to the vehicle population in Maricopa County. The population ratio for 2008 

was derived from the MAG socioeconomic data, which is 4,005,000 people for the PM10 NAA 

and 3,988,000 people for Maricopa County. The specific MOVES table [SourceTypeYear] for 

vehicle population is presented in Appendix 5.
2008 Maricopa Co. PM10 Emission Inventory 108 June 2011 

5.2.2.5 Source type age distribution

MOVES2010a categorizes vehicles according to different vehicle classes and model years. The 

source type age distribution was prepared using EPA’s data converter that takes the registration 

distribution input file created for MOBILE6.2 and converts it to the appropriate MOVES age 

distribution input table [SourceTypeAgeDistribution]. The same source type age distribution 

was applied for Maricopa County and the PM10 NAA. The specific MOVES table for source 

type age distribution is presented in Appendix 5.

5.2.2.6 Annual VMT

The 2008 daily VMTs by facility type were used to estimate onroad exhaust, tire wear, and brake 

wear emissions. The 2008 VMT distributions by facility type for the PM10 NAA and Maricopa 

County were obtained from the 2008 Maricopa County Estimates of Daily Vehicle Travel by 

Highway Functional Classification provided by ADOT. The 2008 VMT distributions were 

multiplied by the 2008 HPMS VMT for the PM10 NAA and Maricopa County. The resultant 

VMT estimates by facility type for the PM10 NAA and Maricopa County are shown in Table 

5.2–1.

Table 5.2–1. 2008 daily VMT by facility type (annual average daily traffic).

Facility Type

PM10 NAA

(thousand miles/day)

Maricopa County

(thousand miles/day)

Rural

Interstate 2,581 3,223

Other Principal Arterial 1,035 1,293

Minor Arterial 529 661

Major Collector 1,347 1,682

Minor Collector 164 205

Local 630 787

Urban

Interstate 10,606 10,939

Other Freeway/Expressway 19,158 19,760

Other Principal Arterial 21,961 22,651

Minor Arterial 14,476 14,930

Collector 4,717 4,865

Local 9,949 10,261

Totals: 87,153 91,257

Since MOVES2010a requires annual VMTs by HPMS vehicle type as a local input, the daily 

VMTs by HPMS vehicle type were derived from the 2008 traffic assignment data provided by 

the MAG Transportation Modeling Group in March 2011 and the daily VMTs by facility type 

and the estimated percentages of daily vehicle travel by vehicle type and highway functional 

classification provided by ADOT. Then, the daily VMTs by HPMS vehicle type were multiplied 

by 366 days to obtain the annual VMTs by HPMS vehicle type. The specific MOVES table 

[HPMSvTypeYear] for annual VMT is presented in Appendix 5.

5.2.2.7 Road type distribution

MOVES2010a requires the distribution of VMTs by road type as a local input. The road type 

VMT distribution by HPMS vehicle type was derived from the 2008 traffic assignment data and 

the daily VMTs by HPMS vehicle type mentioned in the previous section. As suggested in 

EPA’s technical guidance (EPA, 2010a), the same road type distribution by HPMS vehicle type 

was used for all MOVES source types within an HPMS vehicle class. The specific MOVES 

table [RoadTypeDistribution] for road type distribution is presented in Appendix 5.
2008 Maricopa Co. PM10 Emission Inventory 109 June 2011 

5.2.2.8 VMT fraction

Since VMT varies by month, day of week, and hour, MOVES2010a requires month/day/hour 

VMT fractions as a local input in order to derive hourly VMT for each weekday/weekend and 

month from the annual VMT. The month/day/hour VMT fractions were developed from data 

recorded by continuous traffic counters on freeways (ADOT Freeway Management System) and 

arterials (Phoenix Automatic Traffic Recorders) during the year 2007. The specific MOVES 

tables [MonthVMTFraction], [DayVMTFraction], and [HourVMTFraction] for VMT fractions 

are presented in Appendix 5.

5.2.2.9 Average speed distribution

In MOVES2010a, vehicle power, speed, and acceleration have a significant effect on vehicle 

emissions for all pollutants. MOVES2010a estimates those emission effects by assigning 

activity to operating mode distributions, which are determined by the distribution of vehicle 

hours traveled (VHT) by average speed. As recommended in EPA’s technical guidance (EPA, 

2010a), local estimates of average speed were developed by post-processing the output from the 

2008 traffic assignment data provided by the MAG Transportation Modeling Group in March 

2011. To develop the average speed distribution, VHTs in sixteen speed bins were accumulated 

separately for each hour of the day, source type, and road type in Maricopa County. Then, the 

average speed distribution was calculated by normalizing VHTs in sixteen speed bins for each 

hour of the day, source type, and road type. The same methodology was applied to develop the 

speed estimates for the PM10 NAA. The specific MOVES table [AvgSpeedDistribution] for the 

average speed distribution is presented in Appendix 5.

5.2.2.10Ramp fraction

MOVES2010a requires the ramp fraction, which represents the percent of VHT on ramps, on 

both rural restricted roads (road type 2) and urban restricted roads (road type 4). The fraction of 

VHT on ramps was derived by dividing the total VHTs on ramps by the total VHTs for each 

restricted road type. Those VHTs were obtained from the 2008 traffic assignment data provided 

by the MAG Transportation Modeling Group in March 2011. The specific MOVES table 

[RoadType] for ramp fractions is presented in Appendix 5.

5.2.3 MOVES2010a outputs

MOVES2010a was executed with the RunSpec files described in Appendix 5 to obtain exhaust, 

tire wear, and brake wear emissions for PM10, PM2.5, NOx, SO2, and NH3. These values were 

obtained for the following twelve vehicle classes: light duty gasoline vehicles (LDGV), light 

duty gasoline trucks 1 & 2 (LDGT1), light duty gasoline trucks 3 and 4 (LDGT2), heavy duty 

gasoline vehicles 2B thru 8B and gasoline buses (HDGV), motorcycles (MC), light duty diesel 

vehicles (LDDV), light duty diesel trucks 1 thru 4 (LDDT), heavy duty diesel vehicles class 2B 

(2BHDDV), heavy duty diesel vehicles class 3, 4, and 5 (LHDDV), heavy duty diesel vehicles 

class 6 and 7 (MHDDV), heavy duty diesel vehicles class 8A and 8B (HHDDV), and heavy duty 

diesel buses (BUSES); by the following thirteen facility types: rural interstate, rural principal 

arterial, rural minor arterial, rural major collector, rural minor collector, rural local, urban interstate, urban freeway/expressway, urban principal arterial, urban minor arterial, urban collector, 

urban local, and off-network, which was newly added in MOVES2010a; by weekdays and weekend days; by month.
2008 Maricopa Co. PM10 Emission Inventory 110 June 2011 

5.2.4 MOVES2010a emission estimates

MOVES2010a was used to generate onroad emissions by vehicle class, facility type, weekdays/

weekend days, and month. The annual emissions were calculated by aggregating monthly onroad emissions derived by adding monthly weekday emissions, which is the product of daily 

weekday emissions estimated by MOVES2010a and the number of weekdays for a given month, 

and monthly weekend emissions, which is the product of daily weekend emissions estimated by 

MOVES2010a and the number of weekend days for a given month. The average daily emissions 

were calculated by dividing the annual emissions by 366 days.

Tables 5.2–2 and 5.2–3 show the calculated annual and average daily PM10, PM2.5, NOx, SO2, 

and NH3 emissions by facility type and vehicle class in the PM10 NAA and Maricopa County, 

respectively. Emission estimates for PM10 and PM2.5 in these tables represent exhaust, tire wear, 

and brake wear emissions.

Table 5.2–2. Annual and average daily onroad mobile source emissions by facility type and vehicle class in 

the PM10 NAA.

Facility

Type

Vehicle

Class SCC

Annual emissions (tons/year) Average daily emissions (lbs/day)

PM10 PM2.5 NOx SO2 NH3 PM10 PM2.5 NOx SO2 NH3

Rural

Interstate

LDGV 2201001110 4.03 2.36 113.80 1.39 8.47 PM10 PM2.5 621.8 7.6 46.3

LDGT1 2201020110 9.97 6.47 416.37 3.27 15.05 54.5 35.3 2,275.3 17.9 82.2

LDGT2 2201040110 5.13 3.33 214.49 1.68 7.75 28.1 18.2 1,172.1 9.2 42.4

HDGV 2201070110 2.16 1.30 116.05 0.71 2.44 11.8 7.1 634.1 3.9 13.4

MC 2201080110 0.27 0.24 6.28 0.05 0.34 1.5 1.3 34.3 0.3 1.9

LDDV 2230001110 0.05 0.05 0.73 0.00 0.01 0.3 0.2 4.0 0.0 0.0

LDDT 2230060110 1.69 1.58 26.36 0.02 0.19 9.2 8.6 144.0 0.1 1.0

2BHDDV 2230071110 0.71 0.66 11.70 0.01 0.08 3.9 3.6 63.9 0.1 0.5

LHDDV 2230072110 4.12 3.85 62.48 0.05 0.44 22.5 21.1 341.4 0.3 2.4

MHDDV 2230073110 14.60 13.06 299.34 0.24 0.99 79.8 71.4 1,635.7 1.3 5.4

HHDDV 2230074110 46.97 42.91 1,072.87 0.84 2.54 256.7 234.5 5,862.7 4.6 13.9

BUSES 2230075110 2.08 1.90 43.45 0.02 0.08 11.3 10.4 237.4 0.1 0.5

Rural

Principal

Arterial

LDGV 2201001130 4.47 2.00 99.90 1.25 6.86 24.4 10.9 545.9 6.9 37.5

LDGT1 2201020130 6.17 3.02 206.39 1.67 6.98 33.7 16.5 1,127.8 9.1 38.2

LDGT2 2201040130 3.18 1.55 106.32 0.86 3.60 17.4 8.5 581.0 4.7 19.7

HDGV 2201070130 1.03 0.52 40.56 0.27 0.99 5.6 2.9 221.6 1.5 5.4

MC 2201080130 0.43 0.36 11.30 0.09 0.56 2.3 2.0 61.8 0.5 3.1

LDDV 2230001130 0.04 0.03 0.76 0.00 0.00 0.2 0.2 4.2 0.0 0.0

LDDT 2230060130 0.94 0.85 15.35 0.01 0.09 5.1 4.7 83.9 0.1 0.5

2BHDDV 2230071130 0.40 0.36 6.84 0.01 0.04 2.2 2.0 37.4 0.0 0.2

LHDDV 2230072130 2.29 2.09 36.25 0.03 0.20 12.5 11.4 198.1 0.1 1.1

MHDDV 2230073130 3.51 3.04 62.16 0.05 0.21 19.2 16.6 339.7 0.3 1.2

HHDDV 2230074130 10.16 9.00 188.59 0.15 0.44 55.5 49.2 1,030.6 0.8 2.4

BUSES 2230075130 0.86 0.76 15.40 0.01 0.03 4.7 4.2 84.1 0.0 0.2
2008 Maricopa Co. PM10 Emission Inventory 111 June 2011 

Table 5.2–2. Annual and average daily onroad mobile source emissions by facility type and vehicle class 

in the PM10 NAA (continued). 

Facility

Type

Vehicle

Class SCC

Annual emissions (tons/year) Average daily emissions (lbs/day)

PM10 PM2.5 NOx SO2 NH3 PM10 PM2.5 NOx SO2 NH3

Rural

Minor

Arterial

LDGV 2201001150 4.34 1.94 97.07 1.22 6.66 23.7 10.6 530.4 6.7 36.4

LDGT1 2201020150 5.99 2.93 200.55 1.62 6.79 32.7 16.0 1,095.9 8.9 37.1

LDGT2 2201040150 3.09 1.51 103.31 0.83 3.50 16.9 8.3 564.6 4.6 19.1

HDGV 2201070150 1.00 0.51 39.41 0.26 0.96 5.5 2.8 215.4 1.4 5.2

MC 2201080150 0.42 0.35 10.98 0.09 0.55 2.3 1.9 60.0 0.5 3.0

LDDV 2230001150 0.04 0.03 0.74 0.00 0.00 0.2 0.2 4.1 0.0 0.0

LDDT 2230060150 0.91 0.83 14.92 0.01 0.08 5.0 4.5 81.5 0.1 0.5

2BHDDV 2230071150 0.39 0.35 6.64 0.00 0.04 2.1 1.9 36.3 0.0 0.2

LHDDV 2230072150 2.23 2.03 35.23 0.03 0.20 12.2 11.1 192.5 0.1 1.1

MHDDV 2230073150 3.41 2.96 60.40 0.05 0.21 18.7 16.2 330.1 0.3 1.1

HHDDV 2230074150 9.87 8.75 183.26 0.14 0.43 54.0 47.8 1,001.4 0.8 2.3

BUSES 2230075150 0.83 0.74 14.96 0.01 0.03 4.6 4.1 81.8 0.0 0.2

Rural

Major

Collector

LDGV 2201001170 0.81 0.36 18.09 0.23 1.24 4.4 2.0 98.9 1.2 6.8

LDGT1 2201020170 1.12 0.55 37.38 0.30 1.27 6.1 3.0 204.3 1.6 6.9

LDGT2 2201040170 0.58 0.28 19.26 0.16 0.65 3.1 1.5 105.2 0.8 3.6

HDGV 2201070170 0.19 0.09 7.35 0.05 0.18 1.0 0.5 40.1 0.3 1.0

MC 2201080170 0.08 0.06 2.05 0.02 0.10 0.4 0.4 11.2 0.1 0.6

LDDV 2230001170 0.01 0.01 0.14 0.00 0.00 0.0 0.0 0.8 0.0 0.0

LDDT 2230060170 0.17 0.15 2.78 0.00 0.02 0.9 0.8 15.2 0.0 0.1

2BHDDV 2230071170 0.07 0.07 1.24 0.00 0.01 0.4 0.4 6.8 0.0 0.0

LHDDV 2230072170 0.42 0.38 6.57 0.00 0.04 2.3 2.1 35.9 0.0 0.2

MHDDV 2230073170 0.64 0.55 11.26 0.01 0.04 3.5 3.0 61.5 0.0 0.2

HHDDV 2230074170 1.84 1.63 34.16 0.03 0.08 10.1 8.9 186.7 0.1 0.4

BUSES 2230075170 0.16 0.14 2.79 0.00 0.01 0.9 0.8 15.2 0.0 0.0

Rural

Minor

Collector

LDGV 2201001190 0.19 0.08 4.19 0.05 0.29 1.0 0.5 22.9 0.3 1.6

LDGT1 2201020190 0.26 0.13 8.65 0.07 0.29 1.4 0.7 47.3 0.4 1.6

LDGT2 2201040190 0.13 0.07 4.46 0.04 0.15 0.7 0.4 24.4 0.2 0.8

HDGV 2201070190 0.04 0.02 1.70 0.01 0.04 0.2 0.1 9.3 0.1 0.2

MC 2201080190 0.02 0.02 0.47 0.00 0.02 0.1 0.1 2.6 0.0 0.1

LDDV 2230001190 0.00 0.00 0.03 0.00 0.00 0.0 0.0 0.2 0.0 0.0

LDDT 2230060190 0.04 0.04 0.64 0.00 0.00 0.2 0.2 3.5 0.0 0.0

2BHDDV 2230071190 0.02 0.02 0.29 0.00 0.00 0.1 0.1 1.6 0.0 0.0

LHDDV 2230072190 0.10 0.09 1.52 0.00 0.01 0.5 0.5 8.3 0.0 0.0

MHDDV 2230073190 0.15 0.13 2.61 0.00 0.01 0.8 0.7 14.2 0.0 0.0

HHDDV 2230074190 0.43 0.38 7.91 0.01 0.02 2.3 2.1 43.2 0.0 0.1

BUSES 2230075190 0.04 0.03 0.65 0.00 0.00 0.2 0.2 3.5 0.0 0.0

Rural

Local

LDGV 2201001210 1.96 0.88 43.76 0.55 3.00 10.7 4.8 239.1 3.0 16.4

LDGT1 2201020210 2.70 1.32 90.41 0.73 3.06 14.8 7.2 494.0 4.0 16.7

LDGT2 2201040210 1.39 0.68 46.57 0.38 1.58 7.6 3.7 254.5 2.1 8.6

HDGV 2201070210 0.45 0.23 17.77 0.12 0.43 2.5 1.3 97.1 0.7 2.4

MC 2201080210 0.19 0.16 4.95 0.04 0.25 1.0 0.9 27.0 0.2 1.4

LDDV 2230001210 0.02 0.01 0.33 0.00 0.00 0.1 0.1 1.8 0.0 0.0

LDDT 2230060210 0.41 0.37 6.73 0.00 0.04 2.2 2.0 36.7 0.0 0.2

2BHDDV 2230071210 0.17 0.16 3.00 0.00 0.02 1.0 0.9 16.4 0.0 0.1

LHDDV 2230072210 1.00 0.92 15.88 0.01 0.09 5.5 5.0 86.8 0.1 0.5

MHDDV 2230073210 1.54 1.33 27.23 0.02 0.09 8.4 7.3 148.8 0.1 0.5

HHDDV 2230074210 4.45 3.94 82.61 0.06 0.19 24.3 21.6 451.4 0.4 1.1

BUSES 2230075210 0.38 0.33 6.74 0.00 0.01 2.1 1.8 36.9 0.0 0.1
2008 Maricopa Co. PM10 Emission Inventory 112 June 2011 

Table 5.2–2. Annual and average daily onroad mobile source emissions by facility type and vehicle class 

in the PM10 NAA (continued).

Facility

Type

Vehicle

Class SCC

Annual emissions (tons/year) Average daily emissions (lbs/day)

PM10 PM2.5 NOx SO2 NH3 PM10 PM2.5 NOx SO2 NH3

Urban

Interstate

LDGV 2201001230 34.07 19.77 826.32 10.12 59.49 186.2 108.0 4,515.4 55.3 325.1

LDGT1 2201020230 61.65 38.52 2,159.31 17.31 76.76 336.9 210.5 11,799.5 94.6 419.4

LDGT2 2201040230 31.76 19.84 1,112.37 8.92 39.54 173.6 108.4 6,078.5 48.7 216.1

HDGV 2201070230 13.64 7.78 662.41 4.08 12.90 74.5 42.5 3,619.7 22.3 70.5

MC 2201080230 4.11 3.60 78.03 0.65 4.24 22.4 19.6 426.4 3.5 23.2

LDDV 2230001230 0.43 0.38 5.36 0.01 0.04 2.4 2.1 29.3 0.0 0.2

LDDT 2230060230 9.50 8.78 145.30 0.12 0.92 51.9 48.0 794.0 0.6 5.1

2BHDDV 2230071230 4.02 3.70 64.53 0.05 0.41 21.9 20.2 352.6 0.3 2.3

LHDDV 2230072230 23.20 21.48 344.36 0.27 2.17 126.8 117.4 1,881.8 1.5 11.8

MHDDV 2230073230 84.59 74.53 1,618.55 1.29 5.20 462.2 407.3 8,844.5 7.1 28.4

HHDDV 2230074230 238.30 214.02 4,871.28 3.82 11.30 1,302.2 1,169.5 26,619.0 20.9 61.7

BUSES 2230075230 18.04 16.38 348.55 0.19 0.65 98.6 89.5 1,904.6 1.0 3.5

Urban

Freeway

And

Expressway

LDGV 2201001250 35.75 20.74 866.95 10.62 62.41 195.3 113.3 4,737.5 58.0 341.0

LDGT1 2201020250 64.69 40.41 2,265.51 18.16 80.53 353.5 220.8 12,379.8 99.2 440.1

LDGT2 2201040250 33.32 20.82 1,167.08 9.35 41.49 182.1 113.8 6,377.5 51.1 226.7

HDGV 2201070250 14.31 8.16 694.98 4.28 13.53 78.2 44.6 3,797.7 23.4 74.0

MC 2201080250 4.31 3.77 81.87 0.68 4.45 23.6 20.6 447.4 3.7 24.3

LDDV 2230001250 0.45 0.40 5.63 0.01 0.04 2.5 2.2 30.7 0.0 0.2

LDDT 2230060250 9.97 9.21 152.44 0.12 0.97 54.5 50.3 833.0 0.7 5.3

2BHDDV 2230071250 4.21 3.88 67.70 0.05 0.43 23.0 21.2 370.0 0.3 2.4

LHDDV 2230072250 24.34 22.53 361.30 0.28 2.27 133.0 123.1 1,974.3 1.5 12.4

MHDDV 2230073250 88.75 78.19 1,698.15 1.36 5.45 485.0 427.3 9,279.5 7.4 29.8

HHDDV 2230074250 250.02 224.55 5,110.85 4.00 11.85 1,366.2 1,227.0 27,928.1 21.9 64.8

BUSES 2230075250 18.92 17.19 365.69 0.20 0.68 103.4 93.9 1,998.3 1.1 3.7

Urban

Principal

Arterial

LDGV 2201001270 112.79 45.15 1,898.68 24.98 123.71 616.3 246.7 10,375.3 136.5 676.0

LDGT1 2201020270 150.63 61.39 3,540.67 31.15 114.87 823.1 335.5 19,347.9 170.2 627.7

LDGT2 2201040270 77.59 31.63 1,823.98 16.05 59.17 424.0 172.8 9,967.1 87.7 323.4

HDGV 2201070270 26.09 10.35 725.63 5.36 16.59 142.6 56.5 3,965.2 29.3 90.7

MC 2201080270 6.29 5.08 130.89 1.31 6.61 34.4 27.8 715.2 7.1 36.1

LDDV 2230001270 0.86 0.64 16.10 0.02 0.07 4.7 3.5 88.0 0.1 0.4

LDDT 2230060270 20.07 17.65 336.50 0.22 1.35 109.7 96.4 1,838.8 1.2 7.4

2BHDDV 2230071270 8.56 7.50 149.81 0.10 0.60 46.8 41.0 818.7 0.5 3.3

LHDDV 2230072270 49.11 43.37 797.14 0.49 3.16 268.3 237.0 4,356.0 2.7 17.3

MHDDV 2230073270 93.47 77.13 1,474.01 1.15 3.96 510.8 421.5 8,054.7 6.3 21.6

HHDDV 2230074270 268.61 229.65 4,055.08 3.18 7.98 1,467.8 1,254.9 22,158.9 17.4 43.6

BUSES 2230075270 20.39 17.43 301.38 0.16 0.50 111.4 95.2 1,646.9 0.9 2.7

Urban

Minor

Arterial

LDGV 2201001290 57.33 22.95 965.09 12.70 62.88 313.3 125.4 5,273.7 69.4 343.6

LDGT1 2201020290 76.56 31.20 1,799.71 15.83 58.39 418.4 170.5 9,834.5 86.5 319.1

LDGT2 2201040290 39.44 16.08 927.12 8.16 30.08 215.5 87.8 5,066.2 44.6 164.4

HDGV 2201070290 13.26 5.26 368.83 2.72 8.43 72.5 28.7 2,015.5 14.9 46.1

MC 2201080290 3.20 2.58 66.53 0.66 3.36 17.5 14.1 363.6 3.6 18.3

LDDV 2230001290 0.44 0.33 8.18 0.01 0.04 2.4 1.8 44.7 0.1 0.2

LDDT 2230060290 10.20 8.97 171.04 0.11 0.68 55.7 49.0 934.6 0.6 3.7

2BHDDV 2230071290 4.35 3.81 76.15 0.05 0.31 23.8 20.8 416.1 0.3 1.7

LHDDV 2230072290 24.96 22.05 405.18 0.25 1.61 136.4 120.5 2,214.1 1.4 8.8

MHDDV 2230073290 47.51 39.20 749.23 0.58 2.01 259.6 214.2 4,094.2 3.2 11.0

HHDDV 2230074290 136.53 116.73 2,061.18 1.62 4.06 746.1 637.9 11,263.3 8.8 22.2

BUSES 2230075290 10.37 8.86 153.19 0.08 0.25 56.6 48.4 837.1 0.5 1.4
2008 Maricopa Co. PM10 Emission Inventory 113 June 2011 

Table 5.2–2. Annual and average daily onroad mobile source emissions by facility type and vehicle class 

in the PM10 NAA (continued).

Facility

Type

Vehicle

Class SCC

Annual emissions (tons/year) Average daily emissions (lbs/day)

PM10 PM2.5 NOx SO2 NH3 PM10 PM2.5 NOx SO2 NH3

Urban

Collector

LDGV 2201001310 11.20 4.48 188.48 2.48 12.28 61.2 24.5 1,029.9 13.6 67.1

LDGT1 2201020310 14.95 6.09 351.47 3.09 11.40 81.7 33.3 1,920.6 16.9 62.3

LDGT2 2201040310 7.70 3.14 181.06 1.59 5.87 42.1 17.2 989.4 8.7 32.1

HDGV 2201070310 2.59 1.03 72.03 0.53 1.65 14.2 5.6 393.6 2.9 9.0

MC 2201080310 0.62 0.50 12.99 0.13 0.66 3.4 2.8 71.0 0.7 3.6

LDDV 2230001310 0.09 0.06 1.60 0.00 0.01 0.5 0.3 8.7 0.0 0.0

LDDT 2230060310 1.99 1.75 33.40 0.02 0.13 10.9 9.6 182.5 0.1 0.7

2BHDDV 2230071310 0.85 0.74 14.87 0.01 0.06 4.6 4.1 81.3 0.1 0.3

LHDDV 2230072310 4.87 4.31 79.13 0.05 0.31 26.6 23.5 432.4 0.3 1.7

MHDDV 2230073310 9.28 7.66 146.32 0.11 0.39 50.7 41.8 799.6 0.6 2.1

HHDDV 2230074310 26.66 22.80 402.53 0.32 0.79 145.7 124.6 2,199.6 1.7 4.3

BUSES 2230075310 2.02 1.73 29.92 0.02 0.05 11.1 9.5 163.5 0.1 0.3

Urban

Local

LDGV 2201001330 54.04 21.63 909.78 11.97 59.28 295.3 118.2 4,971.5 65.4 323.9

LDGT1 2201020330 72.17 29.42 1,696.57 14.93 55.04 394.4 160.7 9,270.9 81.6 300.8

LDGT2 2201040330 37.18 15.15 873.99 7.69 28.35 203.2 82.8 4,775.9 42.0 154.9

HDGV 2201070330 12.50 4.96 347.69 2.57 7.95 68.3 27.1 1,900.0 14.0 43.4

MC 2201080330 3.01 2.44 62.72 0.63 3.17 16.5 13.3 342.7 3.4 17.3

LDDV 2230001330 0.41 0.31 7.71 0.01 0.03 2.2 1.7 42.1 0.1 0.2

LDDT 2230060330 9.62 8.46 161.24 0.10 0.65 52.5 46.2 881.1 0.6 3.5

2BHDDV 2230071330 4.10 3.59 71.79 0.05 0.29 22.4 19.6 392.3 0.3 1.6

LHDDV 2230072330 23.53 20.78 381.96 0.24 1.51 128.6 113.6 2,087.2 1.3 8.3

MHDDV 2230073330 44.79 36.96 706.29 0.55 1.90 244.7 202.0 3,859.5 3.0 10.4

HHDDV 2230074330 128.71 110.04 1,943.05 1.52 3.82 703.3 601.3 10,617.8 8.3 20.9

BUSES 2230075330 9.77 8.35 144.41 0.08 0.24 53.4 45.6 789.1 0.4 1.3

OffNetwork

LDGV 2201001000 69.77 64.25 4,540.27 6.29 0.00 381.3 351.1 24,810.2 34.4 0.0

LDGT1 2201020000 20.34 18.73 1,572.71 1.46 0.00 111.2 102.4 8,594.0 8.0 0.0

LDGT2 2201040000 10.48 9.65 810.18 0.75 0.00 57.3 52.7 4,427.2 4.1 0.0

HDGV 2201070000 3.97 3.66 251.38 0.22 0.00 21.7 20.0 1,373.7 1.2 0.0

MC 2201080000 0.08 0.07 2.31 0.02 0.00 0.4 0.4 12.6 0.1 0.0

LDDV 2230001000 6.41 6.22 18.94 0.01 0.00 35.0 34.0 103.5 0.0 0.0

LDDT 2230060000 1.48 1.44 28.27 0.01 0.00 8.1 7.9 154.5 0.0 0.0

2BHDDV 2230071000 0.53 0.51 12.31 0.00 0.00 2.9 2.8 67.3 0.0 0.0

LHDDV 2230072000 3.33 3.23 66.71 0.02 0.00 18.2 17.6 364.5 0.1 0.0

MHDDV 2230073000 2.24 2.18 147.44 0.03 0.00 12.3 11.9 805.7 0.2 0.0

HHDDV 2230074000 31.74 30.79 2,629.48 0.44 0.00 173.4 168.2 14,368.7 2.4 0.0

BUSES 2230075000 0.24 0.24 4.00 0.01 0.00 1.3 1.3 21.9 0.0 0.0
2008 Maricopa Co. PM10 Emission Inventory 114 June 2011 

Table 5.2–3. Annual and average daily onroad mobile source emissions by facility type and vehicle class in 

Maricopa County.

Facility

Type

Vehicle

Class SCC

Annual emissions (tons/year) Average daily emissions (lbs/day)

PM10 PM2.5 NOx SO2 NH3 PM10 PM2.5 NOx SO2 NH3

Rural

Interstate

LDGV 2201001110 4.06 2.41 122.38 1.47 9.05 22.2 13.2 668.8 8.0 49.5

LDGT1 2201020110 12.43 8.28 561.77 4.35 20.14 67.9 45.2 3,069.8 23.8 110.1

LDGT2 2201040110 6.40 4.26 289.40 2.24 10.38 35.0 23.3 1,581.4 12.2 56.7

HDGV 2201070110 2.48 1.56 135.09 0.84 3.05 13.6 8.6 738.2 4.6 16.7

MC 2201080110 0.33 0.29 7.83 0.06 0.44 1.8 1.6 42.8 0.3 2.4

LDDV 2230001110 0.05 0.05 0.77 0.00 0.01 0.3 0.3 4.2 0.0 0.0

LDDT 2230060110 2.17 2.03 34.87 0.03 0.25 11.8 11.1 190.6 0.2 1.4

2BHDDV 2230071110 0.91 0.86 15.47 0.01 0.11 5.0 4.7 84.5 0.1 0.6

LHDDV 2230072110 5.28 4.96 82.73 0.07 0.59 28.9 27.1 452.1 0.4 3.2

MHDDV 2230073110 16.74 15.10 362.98 0.29 1.15 91.5 82.5 1,983.5 1.6 6.3

HHDDV 2230074110 62.15 57.25 1,498.95 1.17 3.49 339.6 312.8 8,191.0 6.4 19.1

BUSES 2230075110 2.07 1.90 44.50 0.02 0.08 11.3 10.4 243.1 0.1 0.5

Rural

Principal

Arterial

LDGV 2201001130 4.94 2.22 111.37 1.40 7.66 27.0 12.1 608.6 7.6 41.9

LDGT1 2201020130 7.96 3.93 270.70 2.18 9.19 43.5 21.5 1,479.2 11.9 50.2

LDGT2 2201040130 4.10 2.02 139.45 1.12 4.73 22.4 11.1 762.0 6.1 25.9

HDGV 2201070130 1.33 0.68 52.65 0.35 1.29 7.3 3.7 287.7 1.9 7.1

MC 2201080130 0.54 0.45 14.17 0.12 0.71 2.9 2.4 77.4 0.6 3.9

LDDV 2230001130 0.04 0.04 0.85 0.00 0.00 0.2 0.2 4.6 0.0 0.0

LDDT 2230060130 1.22 1.11 19.83 0.01 0.11 6.6 6.1 108.4 0.1 0.6

2BHDDV 2230071130 0.52 0.47 8.83 0.01 0.05 2.8 2.6 48.3 0.0 0.3

LHDDV 2230072130 2.97 2.71 46.80 0.03 0.27 16.2 14.8 255.7 0.2 1.5

MHDDV 2230073130 4.71 4.10 85.77 0.07 0.29 25.7 22.4 468.7 0.4 1.6

HHDDV 2230074130 14.61 13.03 286.25 0.22 0.68 79.8 71.2 1,564.2 1.2 3.7

BUSES 2230075130 1.09 0.97 19.60 0.01 0.04 5.9 5.3 107.1 0.1 0.2

Rural

Minor

Arterial

LDGV 2201001150 4.80 2.16 108.22 1.36 7.45 26.2 11.8 591.4 7.4 40.7

LDGT1 2201020150 7.74 3.82 263.05 2.12 8.93 42.3 20.9 1,437.4 11.6 48.8

LDGT2 2201040150 3.99 1.97 135.51 1.09 4.60 21.8 10.8 740.5 6.0 25.1

HDGV 2201070150 1.29 0.66 51.17 0.34 1.26 7.0 3.6 279.6 1.9 6.9

MC 2201080150 0.52 0.43 13.77 0.11 0.69 2.8 2.4 75.2 0.6 3.8

LDDV 2230001150 0.04 0.03 0.82 0.00 0.00 0.2 0.2 4.5 0.0 0.0

LDDT 2230060150 1.18 1.08 19.27 0.01 0.11 6.5 5.9 105.3 0.1 0.6

2BHDDV 2230071150 0.50 0.46 8.58 0.01 0.05 2.7 2.5 46.9 0.0 0.3

LHDDV 2230072150 2.89 2.64 45.48 0.03 0.26 15.8 14.4 248.5 0.2 1.4

MHDDV 2230073150 4.57 3.98 83.34 0.07 0.28 25.0 21.7 455.4 0.4 1.5

HHDDV 2230074150 14.20 12.66 278.16 0.22 0.66 77.6 69.2 1,520.0 1.2 3.6

BUSES 2230075150 1.06 0.94 19.04 0.01 0.04 5.8 5.1 104.1 0.1 0.2

Rural

Major

Collector

LDGV 2201001170 0.89 0.40 20.17 0.25 1.39 4.9 2.2 110.2 1.4 7.6

LDGT1 2201020170 1.44 0.71 49.03 0.40 1.66 7.9 3.9 267.9 2.2 9.1

LDGT2 2201040170 0.74 0.37 25.26 0.20 0.86 4.1 2.0 138.0 1.1 4.7

HDGV 2201070170 0.24 0.12 9.54 0.06 0.23 1.3 0.7 52.1 0.3 1.3

MC 2201080170 0.10 0.08 2.57 0.02 0.13 0.5 0.4 14.0 0.1 0.7

LDDV 2230001170 0.01 0.01 0.15 0.00 0.00 0.0 0.0 0.8 0.0 0.0

LDDT 2230060170 0.22 0.20 3.59 0.00 0.02 1.2 1.1 19.6 0.0 0.1

2BHDDV 2230071170 0.09 0.08 1.60 0.00 0.01 0.5 0.5 8.7 0.0 0.1

LHDDV 2230072170 0.54 0.49 8.48 0.01 0.05 2.9 2.7 46.3 0.0 0.3

MHDDV 2230073170 0.85 0.74 15.53 0.01 0.05 4.7 4.1 84.9 0.1 0.3

HHDDV 2230074170 2.65 2.36 51.84 0.04 0.12 14.5 12.9 283.3 0.2 0.7

BUSES 2230075170 0.20 0.18 3.55 0.00 0.01 1.1 1.0 19.4 0.0 0.0
2008 Maricopa Co. PM10 Emission Inventory 115 June 2011 

Table 5.2–3. Annual and average daily onroad mobile source emissions by facility type and vehicle class in 

Maricopa County (continued).

Facility

Type

Vehicle

Class SCC

Annual emissions (tons/year) Average daily emissions (lbs/day)

PM10 PM2.5 NOx SO2 NH3 PM10 PM2.5 NOx SO2 NH3

Rural

Minor

Collector

LDGV 2201001190 0.21 0.09 4.67 0.06 0.32 1.1 0.5 25.5 0.3 1.8

LDGT1 2201020190 0.33 0.16 11.35 0.09 0.39 1.8 0.9 62.0 0.5 2.1

LDGT2 2201040190 0.17 0.08 5.85 0.05 0.20 0.9 0.5 32.0 0.3 1.1

HDGV 2201070190 0.06 0.03 2.21 0.01 0.05 0.3 0.2 12.1 0.1 0.3

MC 2201080190 0.02 0.02 0.59 0.00 0.03 0.1 0.1 3.2 0.0 0.2

LDDV 2230001190 0.00 0.00 0.04 0.00 0.00 0.0 0.0 0.2 0.0 0.0

LDDT 2230060190 0.05 0.05 0.83 0.00 0.00 0.3 0.3 4.5 0.0 0.0

2BHDDV 2230071190 0.02 0.02 0.37 0.00 0.00 0.1 0.1 2.0 0.0 0.0

LHDDV 2230072190 0.12 0.11 1.96 0.00 0.01 0.7 0.6 10.7 0.0 0.1

MHDDV 2230073190 0.20 0.17 3.60 0.00 0.01 1.1 0.9 19.7 0.0 0.1

HHDDV 2230074190 0.61 0.55 12.00 0.01 0.03 3.3 3.0 65.6 0.1 0.2

BUSES 2230075190 0.05 0.04 0.82 0.00 0.00 0.2 0.2 4.5 0.0 0.0

Rural

Local

LDGV 2201001210 2.16 0.97 48.79 0.61 3.36 11.8 5.3 266.6 3.3 18.3

LDGT1 2201020210 3.49 1.72 118.58 0.96 4.02 19.1 9.4 648.0 5.2 22.0

LDGT2 2201040210 1.80 0.89 61.09 0.49 2.07 9.8 4.8 333.8 2.7 11.3

HDGV 2201070210 0.58 0.30 23.07 0.15 0.57 3.2 1.6 126.0 0.8 3.1

MC 2201080210 0.23 0.20 6.21 0.05 0.31 1.3 1.1 33.9 0.3 1.7

LDDV 2230001210 0.02 0.02 0.37 0.00 0.00 0.1 0.1 2.0 0.0 0.0

LDDT 2230060210 0.53 0.49 8.69 0.01 0.05 2.9 2.7 47.5 0.0 0.3

2BHDDV 2230071210 0.23 0.21 3.87 0.00 0.02 1.2 1.1 21.1 0.0 0.1

LHDDV 2230072210 1.30 1.19 20.50 0.01 0.12 7.1 6.5 112.0 0.1 0.6

MHDDV 2230073210 2.06 1.79 37.57 0.03 0.13 11.3 9.8 205.3 0.2 0.7

HHDDV 2230074210 6.40 5.71 125.39 0.10 0.30 35.0 31.2 685.2 0.5 1.6

BUSES 2230075210 0.48 0.42 8.59 0.00 0.02 2.6 2.3 46.9 0.0 0.1

Urban

Interstate

LDGV 2201001230 35.00 20.31 849.09 10.40 61.12 191.2 111.0 4,639.9 56.8 334.0

LDGT1 2201020230 63.55 39.72 2,226.82 17.85 79.15 347.3 217.0 12,168.4 97.5 432.5

LDGT2 2201040230 32.74 20.46 1,147.15 9.19 40.77 178.9 111.8 6,268.6 50.2 222.8

HDGV 2201070230 14.10 8.04 686.11 4.22 13.33 77.1 43.9 3,749.2 23.1 72.8

MC 2201080230 4.24 3.71 80.48 0.67 4.37 23.2 20.3 439.8 3.7 23.9

LDDV 2230001230 0.44 0.39 5.51 0.01 0.04 2.4 2.1 30.1 0.0 0.2

LDDT 2230060230 9.80 9.05 149.81 0.12 0.95 53.5 49.5 818.7 0.7 5.2

2BHDDV 2230071230 4.14 3.82 66.53 0.05 0.43 22.6 20.8 363.6 0.3 2.3

LHDDV 2230072230 23.92 22.14 355.07 0.28 2.24 130.7 121.0 1,940.3 1.5 12.2

MHDDV 2230073230 87.96 77.50 1,683.69 1.35 5.40 480.7 423.5 9,200.5 7.4 29.5

HHDDV 2230074230 248.09 222.83 5,074.27 3.98 11.77 1,355.7 1,217.7 27,728.2 21.7 64.3

BUSES 2230075230 18.74 17.02 362.14 0.20 0.67 102.4 93.0 1,978.9 1.1 3.7

Urban

Freeway

And

Express

way

LDGV 2201001250 36.72 21.31 890.85 10.91 64.12 200.6 116.4 4,868.1 59.6 350.4

LDGT1 2201020250 66.67 41.67 2,336.34 18.72 83.04 364.3 227.7 12,766.9 102.3 453.8

LDGT2 2201040250 34.35 21.47 1,203.57 9.65 42.78 187.7 117.3 6,576.9 52.7 233.8

HDGV 2201070250 14.79 8.43 719.85 4.43 13.99 80.8 46.1 3,933.6 24.2 76.4

MC 2201080250 4.45 3.89 84.44 0.70 4.59 24.3 21.3 461.4 3.8 25.1

LDDV 2230001250 0.46 0.41 5.78 0.01 0.04 2.5 2.2 31.6 0.0 0.2

LDDT 2230060250 10.28 9.50 157.18 0.13 1.00 56.2 51.9 858.9 0.7 5.5

2BHDDV 2230071250 4.34 4.00 69.81 0.06 0.45 23.7 21.9 381.5 0.3 2.4

LHDDV 2230072250 25.10 23.23 372.53 0.29 2.35 137.1 126.9 2,035.7 1.6 12.8

MHDDV 2230073250 92.29 81.32 1,766.50 1.41 5.67 504.3 444.3 9,653.0 7.7 31.0

HHDDV 2230074250 260.29 233.79 5,323.82 4.17 12.35 1,422.3 1,277.6 29,091.9 22.8 67.5

BUSES 2230075250 19.66 17.86 379.95 0.21 0.70 107.5 97.6 2,076.2 1.1 3.8
2008 Maricopa Co. PM10 Emission Inventory 116 June 2011 

Table 5.2–3. Annual and average daily onroad mobile source emissions by facility type and vehicle class in 

Maricopa County (continued).

Facility

Type

Vehicle

Class SCC

Annual emissions (tons/year) Average daily emissions (lbs/day)

PM10 PM2.5 NOx SO2 NH3 PM10 PM2.5 NOx SO2 NH3

Urban

Principal

Arterial

LDGV 2201001270 116.26 46.54 1,955.75 25.74 127.42 635.3 254.3 10,687.2 140.7 696.3

LDGT1 2201020270 155.34 63.31 3,649.06 32.11 118.39 848.9 345.9 19,940.2 175.5 646.9

LDGT2 2201040270 80.03 32.61 1,879.82 16.54 60.99 437.3 178.2 10,272.2 90.4 333.3

HDGV 2201070270 26.96 10.68 750.02 5.54 17.12 147.3 58.4 4,098.5 30.3 93.6

MC 2201080270 6.49 5.24 134.88 1.35 6.81 35.4 28.7 737.1 7.4 37.2

LDDV 2230001270 0.88 0.66 16.58 0.02 0.07 4.8 3.6 90.6 0.1 0.4

LDDT 2230060270 20.69 18.19 346.70 0.22 1.39 113.0 99.4 1,894.5 1.2 7.6

2BHDDV 2230071270 8.82 7.73 154.36 0.10 0.62 48.2 42.2 843.5 0.5 3.4

LHDDV 2230072270 50.62 44.71 821.30 0.51 3.26 276.6 244.3 4,488.0 2.8 17.8

MHDDV 2230073270 97.03 80.06 1,530.08 1.19 4.11 530.2 437.5 8,361.1 6.5 22.5

HHDDV 2230074270 278.56 238.17 4,204.75 3.30 8.27 1,522.2 1,301.5 22,976.8 18.0 45.2

BUSES 2230075270 21.19 18.11 313.11 0.17 0.51 115.8 99.0 1,711.0 0.9 2.8

Urban

Minor

Arterial

LDGV 2201001290 59.09 23.65 994.10 13.08 64.77 322.9 129.3 5,432.2 71.5 353.9

LDGT1 2201020290 78.96 32.18 1,854.80 16.32 60.18 431.5 175.8 10,135.5 89.2 328.8

LDGT2 2201040290 40.68 16.58 955.50 8.41 31.00 222.3 90.6 5,221.3 46.0 169.4

HDGV 2201070290 13.70 5.43 381.23 2.82 8.70 74.9 29.7 2,083.2 15.4 47.6

MC 2201080290 3.30 2.67 68.56 0.68 3.46 18.0 14.6 374.6 3.7 18.9

LDDV 2230001290 0.45 0.34 8.43 0.01 0.04 2.5 1.8 46.1 0.1 0.2

LDDT 2230060290 10.51 9.25 176.23 0.11 0.71 57.5 50.5 963.0 0.6 3.9

2BHDDV 2230071290 4.48 3.93 78.46 0.05 0.32 24.5 21.5 428.7 0.3 1.7

LHDDV 2230072290 25.73 22.72 417.46 0.26 1.65 140.6 124.2 2,281.2 1.4 9.0

MHDDV 2230073290 49.32 40.70 777.73 0.61 2.09 269.5 222.4 4,249.9 3.3 11.4

HHDDV 2230074290 141.59 121.06 2,137.26 1.68 4.20 773.7 661.5 11,679.0 9.2 23.0

BUSES 2230075290 10.77 9.20 159.15 0.09 0.26 58.9 50.3 869.7 0.5 1.4

Urban

Collector

LDGV 2201001310 11.54 4.62 194.14 2.56 12.65 63.1 25.2 1,060.9 14.0 69.1

LDGT1 2201020310 15.42 6.28 362.23 3.19 11.75 84.3 34.3 1,979.4 17.4 64.2

LDGT2 2201040310 7.94 3.24 186.60 1.64 6.05 43.4 17.7 1,019.7 9.0 33.1

HDGV 2201070310 2.68 1.06 74.45 0.55 1.70 14.6 5.8 406.8 3.0 9.3

MC 2201080310 0.64 0.52 13.39 0.13 0.68 3.5 2.8 73.2 0.7 3.7

LDDV 2230001310 0.09 0.07 1.65 0.00 0.01 0.5 0.4 9.0 0.0 0.0

LDDT 2230060310 2.05 1.81 34.42 0.02 0.14 11.2 9.9 188.1 0.1 0.8

2BHDDV 2230071310 0.88 0.77 15.32 0.01 0.06 4.8 4.2 83.7 0.1 0.3

LHDDV 2230072310 5.02 4.44 81.53 0.05 0.32 27.5 24.2 445.5 0.3 1.8

MHDDV 2230073310 9.63 7.95 151.89 0.12 0.41 52.6 43.4 830.0 0.6 2.2

HHDDV 2230074310 27.65 23.64 417.39 0.33 0.82 151.1 129.2 2,280.8 1.8 4.5

BUSES 2230075310 2.10 1.80 31.08 0.02 0.05 11.5 9.8 169.8 0.1 0.3

Urban

Local

LDGV 2201001330 55.71 22.30 937.13 12.33 61.05 304.4 121.8 5,120.9 67.4 333.6

LDGT1 2201020330 74.44 30.33 1,748.50 15.39 56.73 406.8 165.8 9,554.7 84.1 310.0

LDGT2 2201040330 38.35 15.63 900.74 7.93 29.22 209.5 85.4 4,922.1 43.3 159.7

HDGV 2201070330 12.92 5.12 359.38 2.65 8.20 70.6 28.0 1,963.8 14.5 44.8

MC 2201080330 3.11 2.51 64.63 0.65 3.26 17.0 13.7 353.2 3.5 17.8

LDDV 2230001330 0.42 0.32 7.95 0.01 0.03 2.3 1.7 43.4 0.1 0.2

LDDT 2230060330 9.91 8.72 166.13 0.11 0.66 54.2 47.6 907.8 0.6 3.6

2BHDDV 2230071330 4.23 3.70 73.96 0.05 0.30 23.1 20.2 404.2 0.3 1.6

LHDDV 2230072330 24.25 21.42 393.54 0.24 1.56 132.5 117.1 2,150.5 1.3 8.5

MHDDV 2230073330 46.49 38.36 733.16 0.57 1.97 254.1 209.6 4,006.3 3.1 10.8

HHDDV 2230074330 133.47 114.12 2,014.77 1.58 3.96 729.4 623.6 11,009.7 8.6 21.7

BUSES 2230075330 10.15 8.68 150.03 0.08 0.25 55.5 47.4 819.8 0.4 1.3
2008 Maricopa Co. PM10 Emission Inventory 117 June 2011 

Table 5.2–3. Annual and average daily onroad mobile source emissions by facility type and vehicle class in 

Maricopa County (continued).

Facility

Type

Vehicle

Class SCC

Annual emissions (tons/year) Average daily emissions (lbs/day)

PM10 PM2.5 NOx SO2 NH3 PM10 PM2.5 NOx SO2 NH3

Off-Network

LDGV 2201001000 69.48 63.97 4,520.99 6.27 0.00 379.6 349.6 24,704.9 34.3 0.0

LDGT1 2201020000 20.26 18.65 1,566.03 1.46 0.00 110.7 101.9 8,557.5 8.0 0.0

LDGT2 2201040000 10.44 9.61 806.74 0.75 0.00 57.0 52.5 4,408.4 4.1 0.0

HDGV 2201070000 3.96 3.64 250.31 0.22 0.00 21.6 19.9 1,367.8 1.2 0.0

MC 2201080000 0.08 0.07 2.30 0.02 0.00 0.4 0.4 12.6 0.1 0.0

LDDV 2230001000 6.38 6.19 18.86 0.01 0.00 34.9 33.8 103.1 0.0 0.0

LDDT 2230060000 1.48 1.43 28.15 0.01 0.00 8.1 7.8 153.8 0.0 0.0

2BHDDV 2230071000 0.53 0.51 12.26 0.00 0.00 2.9 2.8 67.0 0.0 0.0

LHDDV 2230072000 3.31 3.22 66.42 0.02 0.00 18.1 17.6 363.0 0.1 0.0

MHDDV 2230073000 2.34 2.27 155.73 0.03 0.00 12.8 12.4 851.0 0.2 0.0

HHDDV 2230074000 33.61 32.61 2,787.80 0.46 0.00 183.7 178.2 15,233.9 2.5 0.0

BUSES 2230075000 0.24 0.24 3.99 0.01 0.00 1.3 1.3 21.8 0.0 0.0

5.3 Fugitive dust emissions

While exhaust, tire wear, and brake wear emissions were calculated using the EPA MOVES2010a model, fugitive dust emissions from paved and unpaved roads were calculated using the 

equations found in sections 13.2.1 and 13.2.2 of the EPA Compilation of Air Pollutant Emission 

Factors, AP-42 (EPA, 2006). The new AP-42 equation published by EPA in January 2011 has 

been applied to estimate the PM10 and PM2.5 emissions from paved roads. The contact person for 

the fugitive dust emission estimates is Cathy Arthur (602-254-6300).

5.3.1 Paved road fugitive dust emissions

In the AP-42 equation, paved road emissions are a function of silt loading values and the average 

weight of vehicles traveling on paved road surfaces. Paved roads have been classified as freeways, high-traffic arterials, and low-traffic arterials to reflect different silt loading assumptions. 

An arterial carrying a traffic volume of less than 10,000 vehicles per average weekday is classified as low-traffic; all other roads that are not freeways are classified as high-traffic arterials. 

The silt loading levels, in grams per square meter, are 0.02 for freeways, 0.067 for high-traffic 

arterials, and 0.23 for low-traffic arterials. The silt loadings were derived from paved road 

samples collected in Maricopa County by an EPA contractor (US EPA, 1993). The average 

vehicle weights were derived from July 1, 2010 vehicle registrations for Maricopa County provided by the Arizona Department of Transportation. The fugitive dust emission factors for 

paved roads were derived by applying the following AP-42 equation:

E = k × sL0.91 × W1.02 × (1 − P⁄4N)

where: E = annual average particulate emission factor (g/mile),

k = particle size multiplier for particle size range (1.0 g/mile for PM10 and 0.25 g/mile 

for PM2.5),

sL = road surface silt loading (0.02 g/m2 for freeways, 0.067 g/m2 for high-traffic 

arterials, and 0.23 g/m2 for low-traffic arterials),

W = average weight of the vehicles traveling on the roads (3.53 tons on freeways and 

2.65 tons on arterials),
2008 Maricopa Co. PM10 Emission Inventory 118 June 2011 

P = annual number of “wet” days with at least 0.254 mm (0.01 in) of precipitation (39 

days3

N = annual number of days (366 days in 2008).

in 2008), and

The annual average PM10 and PM2.5 emission factors for paved roads derived from the AP-42 

equation are presented in Table 5.3–1.

The 2008 VMTs by silt loading category were used to estimate paved road fugitive dust emissions. Daily VMTs by silt loading category for the PM10 NAA and Maricopa County are shown 

in Table 5.3–2. The VMTs were derived by applying geographic information systems (GIS) to a 

2008 traffic assignment output by the MAG travel demand model, TransCAD. The 2008 weekday traffic volumes output by TransCAD were normalized to 2008 HPMS VMTs for the PM10

NAA and Maricopa County to produce the VMTs by silt loading category shown in Table 5.3–2.

Table 5.3–1. 2008 fugitive dust emission factors for paved roads.

Silt Loading Category

Emission factors (g/mile)

PM10 PM2.5

Freeways 0.10 0.03

High Traffic Arterials 0.22 0.06

Low Traffic Arterials 0.69 0.17

Table 5.3–2. 2008 VMT by silt loading category for paved roads.

Daily VMT

Silt Loading Category PM10 NAA Maricopa County

Freeways 30,835,329 32,526,693

High Traffic Arterials 42,498,543 43,586,568

Low Traffic Arterials 13,819,127 15,143,740

Totals: 87,153,000 91,257,000

Applying the emission factors in Table 5.3–1 to the VMTs in Table 5.3–2 and converting to 

pounds per day produces the 2008 uncontrolled particulate emissions from paved roads for the 

PM10 NAA and Maricopa County, shown in Table 5.3–3. These uncontrolled emissions do not 

include the 2008 emission reductions attributed to the committed measures in the MAG 2007 

Five Percent Plan.

Table 5.3–3. 2008 uncontrolled fugitive dust emissions from paved roads.

Silt Loading Category

PM10 NAA(lbs/day) Maricopa County (lbs/day)

PM10 PM2.5 PM10 PM2.5

Freeways 6,798.0 2,039.4 7,170.8 2,151.3

High Traffic Arterials 20,612.3 5,621.5 21,140.0 5,765.5

Low Traffic Arterials 21,021.3 5,179.2 23,036.3 5,675.6

Totals: 48,431.6 12,840.1 51,347.1 13,592.4

The MAG 2007 Five Percent Plan contains a number of committed measures that reduce paved 

road fugitive dust emissions in the PM10 NAA. Five committed measures that reduce paved road 

particulate emissions were quantified in the MAG 2007 Five Percent Plan. Table 5.3–4 shows 

the emission reductions attributed to these committed measures based on their implementation 

 3 Precipitation data for 2008 were obtained from National Oceanic and Atmospheric Administration (NOAA) in the 

form of local climatological data at Phoenix Sky Harbor Airport.
2008 Maricopa Co. PM10 Emission Inventory 119 June 2011 

status in 2008. In addition, Table 5.3–4 includes emission reduction credit for 97 PM10-certified 

street sweepers purchased by December 31, 2007 with FY 2001–2006 MAG Congestion 

Mitigation and Air Quality Improvement (CMAQ) funds. Reductions for the sweepers that were 

purchased with FY 2001–2006 CMAQ funds were also applied to base case uncontrolled paved 

road emissions in the MAG 2007 Five Percent Plan.

The emission benefits in Table 5.3–4 were subtracted from the uncontrolled PM10 emissions in 

Table 5.3–3. The total 2008 PM10 emission reduction of 11,851.1 pounds per day in the PM10

NAA represents 24.5 percent of the uncontrolled PM10 emissions of 48,431.6 pounds per day. 

This percent reduction was applied to the uncontrolled PM2.5 emissions in the PM10 NAA; then 

the absolute reduction in PM2.5 emissions due to the control measures was applied to the uncontrolled PM2.5 emissions in Maricopa County. The controlled emissions in tons per year and 

pounds per day are shown in Table 5.3–5.

Table 5.3–4. 2008 benefits of measures that reduce paved road fugitive dust in the PM10 NAA4

Committed Measures in the MAG 2007 Five Percent Plan

.

PM10 emission reduction

Annual

(tons/year)

Average daily

(lbs/day)5

1. Public education and outreach program (Measure 1)6 7.7 42.2

2. Reduce trackout onto paved roads (Measures 14/15/17) 579.9 3,169.0

3. Sweep streets with PM10-certified sweepers (Measure 24) 166.9 911.9

4. Pave or stabilize existing unpaved shoulders (Measure 28) 233.3 1,274.6

5. Additional $5M in FY07 MAG TIP for paving roads/shoulders (Measure 43)7 8.2 44.8

97 PM10-certified sweepers purchased with FY 2001–2006 CMAQ funds: 1,172.8 6,408.6

Total 2008 PM10 emission reductions for paved roads: 2,168.8 11,851.1

Table 5.3–5. Annual controlled fugitive dust emissions from paved roads.

Geographic Area

Annual emissions

(tons/year)

Average daily emissions

(lbs/day)

PM10 PM2.5 PM10 PM2.5

PM10 NAA 6,694.2 1,774.8 36,580.5 9,698.1

Maricopa County 7,227.8 1,912.4 39,496.0 10,450.4

5.3.2 Unpaved road fugitive dust emissions

AP-42 emission factors were applied to unpaved road and alley VMTs to estimate fugitive dust 

emissions (US EPA, 2006). The unpaved road and alley particulate emission factors were 

derived from the following AP-42 equation for publicly accessible unpaved roads, assuming a 

silt content of 11.9%, a soil moisture content of 0.5%, and an average speed of 25 miles per hour 

on unpaved roads and 10 miles per hour on unpaved alleys:

 4 The 2008 benefits of the committed measures in the Five Percent Plan have been reduced by 61 percent to reflect 

the new AP-42 equation for paved road dust released by EPA in January 2011. 5 366 days were used to convert tons per year to pounds per day in 2008.

6 Measure benefit reflects a 0.1% reduction in 2008 uncontrolled paved road emissions in the MAG 2007 Five 

Percent Plan.

7 Measure benefit includes only the projects that paved unpaved shoulders in 2008.
2008 Maricopa Co. PM10 Emission Inventory 120 June 2011 

E = �

k � s

12�

1

� S

30�

0.5

� M

0.5�

0.2 − C� �1 − P

N�

where: E = annual average particulate emission factor extrapolated for natural mitigation 

(lb/mile),

 k = particle size multiplier for particle size range (1.8 lb/mile for PM10 and 0.18 lb/mile 

for PM2.5),

 s = surface material silt content (11.9%),

 S = mean vehicle speed (25 mph for unpaved roads and 10 mph for unpaved alleys),

 M = surface material moisture content (0.5%),

 C = emission factor for 1980's vehicle fleet exhaust, brake wear and tire wear (0.00047 

lb/mile for PM10 and 0.00036 lb/mile for PM2.5),

 P = annual number of “wet” days with at least 0.254 mm (0.01 in) of precipitation (39 

days in 2008), and

 N = annual number of days (366 days in 2008).

The unpaved road emission factors resulting from the above equation are 1.4554 pounds per mile 

for PM10 and 0.1453 pounds per mile for PM2.5. The unpaved alley emission factors are 0.9203 

pounds per mile for PM10 and 0.0918 pounds per mile for PM2.5.

The 2008 daily VMTs on unpaved roads and alleys in the PM10 NAA and Maricopa County are 

shown in Table 5.3–6. The 2008 VMT for unpaved roads in the PM10 NAA was derived from 

the MAG 2009 Unpaved Road Inventory (MAG, 2010). The 2008 VMT for unpaved alleys was 

derived by multiplying a MAG GIS-derived estimate of 650 miles of dirt alleys by an annual 

average daily traffic estimate of 9.1 vehicles per day. 

The 2008 Maricopa County VMT was obtained by applying a ratio of 1.047 to the PM10 NAA 

VMT in Table 5.3–6. This ratio represents 2008 VMT on all roads in Maricopa County to 2008 

VMT on all roads in the PM10 NAA, as derived in Table 5.3–7. The VMTs in Table 5.3–7 

represent 2008 HPMS data submitted to the Federal Highway Administration by ADOT in 

August 2009.

Table 5.3–6. 2008 VMT on unpaved roads in the PM10 NAA and Maricopa County.

Geographic Area

2008 Annual Average Daily VMT

Unpaved Roads Unpaved Alleys

PM10 NAA 47,984 5,915

Maricopa County 50,239 6,193
2008 Maricopa Co. PM10 Emission Inventory 121 June 2011 

Table 5.3–7. 2008 VMT on all roads in the PM10 NAA and Maricopa County.

Geographic Area

2008 Annual Average Daily VMT

(in thousands)

Ratio to 2008 Annual Average

Daily VMT in the PM10 NAA

PM10 NAA 87,153 1.000

Maricopa County 91,257 1.047

Multiplying the unpaved road emission factors by the VMTs in Table 5.3–6 results in the uncontrolled emissions shown in Table 5.3–8. These uncontrolled emissions do not include the 2008 

emission reductions attributed to the committed measures in the MAG 2007 Five Percent Plan 

for PM10.

Table 5.3–8. Daily uncontrolled unpaved road and alley fugitive dust emissions.

Geographic Area

PM10 (lbs/day) PM2.5 (lbs/day)

Unpaved Roads Unpaved Alleys Unpaved Roads Unpaved Alleys

PM10 NAA 69,835.9 5,443.6 6,972.1 543.0

Maricopa County 73,117.8 5,699.4 7,299.7 568.5

The MAG 2007 Five Percent Plan contains a number of committed measures that reduce unpaved road and alley fugitive dust emissions in the PM10 NAA (MAG, 2007). Four committed 

measures that reduce unpaved road and alley PM10 emissions were quantified in the MAG 2007 

Five Percent Plan. The 2008 emission reductions attributed to these measures are shown in 

Table 5.3–9.

Table 5.3–9. 2008 benefits of measures that reduce unpaved road and alley fugitive dust in the PM10 NAA.

Committed Measures in the MAG 2007 Five Percent Plan

PM10 emission reductions

Annual

(tons/year)

Average daily

(lbs/day)8

1. Public education and outreach program (Measure 1)9 17.5 95.6

2. Pave or stabilize existing public dirt roads and alleys (Measure 26) 1,488.0 8,131.2

3. Limit speeds to 15 mph on high-traffic dirt roads (Measure 27) 390.4 2,133.4

4. Additional $5M in FY07 MAG TIP for paving roads/shoulders (Measure 43)10 169.5 926.2

Total 2008 PM10 emission reductions for unpaved roads: 2,065.4 11,286.4

The reductions in Table 5.3–9 were subtracted from the uncontrolled PM10 emissions in Table 

5.3–8. The total 2008 PM10 emission reduction of 11,286.4 pounds per day represents 15.0 percent of the total uncontrolled unpaved road and alley PM10 emissions of 75,279.5 pounds per day 

in the PM10 NAA. This percent reduction was applied to the uncontrolled PM2.5 emissions in the 

PM10 NAA; then the absolute reduction in PM2.5 emissions due to the control measures was 

applied to the uncontrolled PM2.5 emissions in Maricopa County. The controlled emissions in 

tons per year and pounds per day are shown in Table 5.3–10.

Table 5.3–10. Annual and average daily controlled fugitive dust emissions from unpaved roads.

Area

Annual emissions (tons/year) Average daily emissions (lbs/day)

PM10 PM2.5 PM10 PM2.5

PM10 NAA 11,710.70 1,169.00 63,993.1 6,387.8

Maricopa County 12,358.20 1,233.60 67,530.9 6,741.0

 8 366 days were used to convert tons per year to pounds per day in 2008.

9 Measure benefit reflects a 0.1% reduction in 2008 uncontrolled paved road emissions in the MAG 2007 Five 

Percent Plan.

10 Measure benefit includes only the projects that paved unpaved roads in 2008.
2008 Maricopa Co. PM10 Emission Inventory 122 June 2011 

5.4 Summary of particulate emissions from onroad mobile sources

Table 5.4–1 summarizes the annual emissions and the average daily emissions for PM10, PM2.5, 

NOx, SO2, and NH3 from all onroad mobile sources in Maricopa County in 2008. Similar data 

for the PM10 NAA are presented in Table 5.4–2.

Table 5.4–1. Annual and average daily emissions from all onroad mobile sources in Maricopa County.

Emission 

Category

Annual emissions (tons/year) Average daily emissions (lbs/day)

PM10 PM2.5 NOx SO2 NH3 PM10 PM2.5 NOx SO2 NH3

Exhaust, tire wear, 

and brake wear 3,295.74 2,417.89 75,033.94 314.45 1,294.12 18,009.2 13,212.4 410,021.3 1,718.2 7,072.1

Paved road

fugitive dust 7,227.77 1,912.42 — — — 39,496.0 10,450.4 — — —

Unpaved road and 

alley fugitive dust 12,358.20 1,233.60 — — — 67,530.9 6,741.0 — — —

Totals: 22,881.71 5,563.91 75,033.94 314.45 1,294.12 125,036.1 30,403.8 410,021.3 1,718.2 7,072.1

Table 5.4–2. Annual and average daily emissions from all onroad mobile sources in the PM10 NAA.

Emission 

Category

Annual emissions (tons/year) Average daily emissions (lbs/day)

PM10 PM2.5 NOx SO2 NH3 PM10 PM2.5 NOx SO2 NH3

Exhaust, tire wear, 

and brake wear 3,144.17 2,300.80 71,444.20 300.66 1,235.28 17,181.3 12,572.9 390,405.5 1,643.0 6,750.5

Paved road

fugitive dust 6,694.22 1,774.76 — — — 36,580.5 9,698.1 — — —

Unpaved road and 

alley fugitive dust 11,710.70 1,169.00 — — — 63,993.1 6,387.8 — — —

Totals: 21,549.09 5,244.56 71,444.20 300.66 1,235.28 117,754.9 28,658.8 390,405.5 1,643.0 6,750.5

5.5 Quality assurance process

5.5.1 VMT estimates

Normal quality assurance procedures, including automated and manual consistency checks, were 

conducted by MAG in developing the 2008 TransCAD traffic assignment network used to generate the VMT data. The VMT estimates using the MAG travel demand model have been 

validated against approximately 2,200 traffic counts collected in 2006–2008.

5.5.2 Emission estimates

The quality assurance process performed on the MOVES2010a analyses included accuracy, 

completeness, and reasonableness checks. For accuracy and completeness, all calculations were 

checked by an independent reviewer. Any errors found were corrected and the changes were 

then rechecked by the reviewer.

5.5.3 Draft particulate matter emissions inventory

The draft onroad mobile source portion of the 2008 periodic PM10 emissions inventory was 

reviewed using published EPA quality review guidelines for base year emission inventories 

(EPA, 1992b). The procedure review (Levels I, II, and III) included checks for completeness, 

consistency, and the correct use of appropriate procedures.
2008 Maricopa Co. PM10 Emission Inventory 123 June 2011 

5.6 References

MAG, 2000. Revised MAG 1999 Serious Area Particulate Plan for PM10 for the Maricopa 

County Nonattainment Area, 2000.

MAG, 2007. MAG 2007 Five Percent Plan for PM10 for the Maricopa County Nonattainment 

Area, December 2007.

MAG, 2009. MAG Eight-Hour Ozone Redesignation Request and Maintenance Plan for the 

Maricopa Nonattainment Area, February 2009.

MAG, 2010. VMT Estimation for the 2009 MAG Unpaved Road Inventory, Memorandum 

prepared by Cathy Arthur, MAG Air Quality Policy Manager, January 26, 2010.

US EPA, 1991. Emission Inventory Requirements for Ozone State Implementation Plans, EPA450/4-91-010, March 1991.

US EPA, 1992a. Procedures for Emission Inventory Preparation Volume IV: Mobile Sources, 

EPA-450/4-81-026d (Revised), 1992.

US EPA, 1992b. Quality Review Guidelines for 1990 Base Year Emission Inventories, EPA454/R-92-007, July 1992.

US EPA, 1993. Emission Factor Documentation for AP-42, Section 13.2.1, Paved Roads, 

 Prepared by MRI under EPA Contract No. 68-D0-0123, March 8, 1993.

US EPA, 2006. Compilation of Air Pollutant Emission Factors, AP-42, Fifth Edition, Vol. I: 

Stationary, Point and Area Sources. Section 13.2.1: Paved Roads and Section 13.2.2: 

Unpaved Roads. November 2006 (http://www.epa.gov/ttn/chief/ap42/ch13/index.html

US EPA, 2010a. Technical Guidance on the Use of MOVES2010 for Emission Inventory 

Preparation in State Implementation Plans and Transportation Conformity, EPA-420-B-10-

023, April 2010.

).

US EPA, 2010b. User’s Guide for the SMOKE-MOVES Integration Tool, EPA Contract EP-D07-102 (WA 3-03), July 2010.

US EPA, 2010c. Motor Vehicle Emission Simulator (MOVES) - User Guide for MOVES2010a, 

EPA-420-B-10-036, August 2010.
2008 Maricopa Co. PM10 Emission Inventory 124 June 2011 

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2008 Maricopa Co. PM10 Emission Inventory 125 June 2011 

6. Biogenic Sources

6.1 Introduction

Biogenic emissions have been estimated for the 2008 Periodic Emissions Inventory for particulate matter in Maricopa County (9,223 square miles) and the PM10 Nonattainment Area (NAA) 

(2,887 square miles). The Model of Emissions of Gases and Aerosols from Nature (MEGAN) 

has been used to estimate the biogenic emissions. MEGAN is a state-of-the-art biogenic emissions model developed by the National Center for Atmospheric Research (NCAR). Some important corrections and improvements were made in the latest version of MEGAN2.04 (Guenther, 

2007) compared to previous versions (Guenther, 2006, 2006a and 2006b). MEGAN2.04 was 

applied to compute biogenic emissions in Maricopa County and the PM10 NAA. Among the 

chemical species included in MEGAN, only nitric oxide (NO) is attributable to particulate matter 

formation. Therefore, only NOx emissions are included in the inventory. The MEGAN runs 

were executed by the Maricopa Association of Governments. The contact person for the 

MEGAN emission estimates is Feng Liu (602-254-6300).

6.2 Modeling domain

As a numerical model, the MEGAN inputs and outputs are given in user-defined two-dimensional grid cells. To develop biogenic emissions for the 2008 Periodic Emission Inventory for 

particulate matter, the 4-km and 12-km modeling domains developed for the MAG eight-hour 

ozone plans for the Maricopa Nonattainment Area (MAG, 2007 and 2009), were employed for 

the PM10 NAA and Maricopa County, respectively. The definitions of these two domains in the 

Universal Transverse Mercator (UTM) coordinate system are presented in Table 6.2–1. Since 

MEGAN estimates biogenic emissions for entire modeling domains rather than specific areas, 

additional input files, masking areas covered by the PM10 NAA and Maricopa County, were 

developed by applying Geographic Information Systems (GIS) to calculate emissions for those 

two target areas. In order to represent the target area, the masking file assigns 1.0 for the grid 

cells fully covered by the target area, a fractional value for grid cells partially covered by the 

target area, and 0.0 for grid cells outside the target area. As shown in Figure 6.3–1, biogenic 

emissions for the PM10 NAA and Maricopa County were extracted from MEGAN runs for the 

masked grid cells in the 4-km and 12-km modeling domains, respectively.

Table 6.2–1. Two modeling domains defined in the UTM coordinate system.

Grid Horizontal 

Resolution Grid Size Domain Range (km) Target Area

4-km 50 × 29 (297,3652) to (497,3768) PM10 NAA

12-km 111 × 84 (275, 3188) to (1,057,4196) Maricopa County

6.3 Input data

To calculate biogenic emissions using MEGAN, the following gridded input files for land cover 

and meteorological data were prepared:

1. EFMAP_LAI file: This file provides emission factors (EF) for 20 MEGAN species 

including NO, and monthly average leaf index (LAI) for 12 months for each grid cell.
2008 Maricopa Co. PM10 Emission Inventory 126 June 2011 

2. PFTF file: This input file gives percentage of four plant function types (PFT) including 

broadleaf trees (BT), needle leaf trees (NT), grass and crops (HB) and shrubs (SB) for 

each model domain grid location.

3. METCRO2D file: This file contains meteorological parameters including temperature, 

short wave radiation, wind speed, humidity and soil moisture for each grid.

Figure 6.3–1. Mask of the PM10 NAA in the 4-km modeling domain (top) and mask of Maricopa County in 

the 12-km modeling domain (bottom).

6.3.1 Land cover data

The land cover data, including the monthly LAI, PFT, and EF, are provided by the EFMAP_LAI 

and PFTF files. These input data were derived from the MEGAN land cover database available 

1

6

11

16

21

26

31

36

41

46

51

56

61

66

71

76

81

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101 106 111

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
2008 Maricopa Co. PM10 Emission Inventory 127 June 2011 

at a base resolution of 30 seconds latitude by 30 seconds longitude (~1×km2) in ArcGIS format 

(http://acd.ucar.edu/~guenther/MEGAN/MEGAN.htm). For the MEGAN runs, however, the 

default land cover data during the summer season (June to August) were replaced by local datasets, which were developed by a field study conducted by Dr. Guenther in June 2006 

(ENVIRON, 2006). The substitution was made because the default database systematically 

underestimated the LAIs in Maricopa County.

6.3.2 Weather data

The weather data used by MEGAN are temperature, downward short wave radiation, wind 

speed, humidity and soil moisture. The Measurement and Instrumentation Data Center (MIDC) 

collects irradiance and meteorological data from nation-wide stations, one of which is located in 

northern Phoenix (33.83° N, 112.17° W, denoted by red star in Figure 6.3–2), and is operated by 

the Phoenix Federal Correction Institution (PFCI). The archived hourly temperature, wind 

speed, humidity and radiation data from this site are available to the public. Monthly mean 

diurnal cycles of the weather parameters were calculated based on hourly data for the year 2008, 

and a netCDF file representing 24-hour data for each month was prepared for MEGAN inputs.

Figure 6.3–2. Boundaries of the PM10 NAA (red line), the 4-km eight-hour ozone modeling domain (pink 

line), Maricopa County (blue line), and the meteorological observation site (red star).

Biogenic NO is mainly emitted from wetted soil. The emission rate is dependent not only upon 

temperature and downward short wave radiation but also on soil moisture. Due to dry conditions 

year round in Maricopa County, the NO flux from the surface is very low compared to other 

states with higher precipitation. Only moisture delivery by Arizona monsoons leads to precipitation during the summer. This precipitation, in turn, increases soil moisture and humidity. 

According to weather records at the Phoenix Sky Harbor International Airport, the precipitation 
2008 Maricopa Co. PM10 Emission Inventory 128 June 2011 

60

65

70

75

80

85

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

Hour of the day

Temperature (F) -100

0

100

200

300

400

500

600

700

800

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

Hour of the day

Downward short wave radiation (W/m2)

in the Phoenix area was 0.0 and 2.15 inches in June and July 2008, respectively. Therefore, 

maximum monthly NO emissions occurred in July 2008. In general, however, NO emissions in 

the Maricopa County area are temperature and radiation dominated during the year. Figure 6.3–

3 shows annual mean diurnal cycles of temperature and radiation. The peak temperature around 

4:00–5:00 pm lags three hours behind the peak radiation. The delay is due to the fact that 

heating of the air occurs not from the sun’s rays, but from heating of the earth and infrared 

radiation leaving the ground in the form of heat. As a result, maximum hourly emission rates 

take place in the afternoon because the emission rates are positively related to both temperature 

and short wave radiation (Guenther, 2006).

Figure 6.3–3. Annual mean diurnal cycles of measured temperature (top panel) and downward short wave 

radiation (bottom panel) in 2008.

6.4 Emissions estimation

MEGAN runs for the two modeling domains provide hourly emission outputs for the year 2008. 

Daily mean emissions for each month in 2008 were derived by using the hourly outputs for each 

month. In addition, monthly total emissions were obtained by multiplying the daily mean emissions for each month by the number of days in the month. The daily mean emissions for the 12 

months of 2008 are shown in Table 6.4–1.
2008 Maricopa Co. PM10 Emission Inventory 129 June 2011 

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

180.0

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Month, 2008

Total NOx emissions (tonnes/month)

NA_NOx

MC_NOx

Table 6.4–1. Daily mean biogenic emissions of NOx in the PM10 NAA and Maricopa County, by month.

PM10 NAA Maricopa County

Month kg/day lbs/day kg/day lbs/day

January 127.2 280.4 355.2 783.1

February 168.0 370.4 480.9 1,060.2

March 413.3 911.2 1,131.0 2,493.4

April 601.7 1,326.5 1,658.8 3,657.0

May 721.0 1,589.5 1,923.1 4,239.7

June 1,818.8 4,009.8 4,729.4 10,426.5

July 1,878.7 4,141.8 4,930.0 10,868.8

August 1,702.0 3,752.3 4,485.1 9,888.0

September 1,331.9 2,936.3 3,784.7 8,343.8

October 651.1 1,435.4 1,839.9 4,056.3

November 328.5 724.2 910.8 2,008.0

December 138.6 305.6 388.0 855.4

Monthly mean emissions for Maricopa County and the PM10 NAA are illustrated in Figure 6.4–

1. Monthly emission values are presented in Table 6.4–2. It can be seen that the monthly NOx

emissions reached the highest values in July. This is because biogenic emissions of nitric oxide 

(NO) are mainly from wetted soil. Thus, the NO emission rate depends not only on temperature 

and radiation, but also on soil moisture, which is related to precipitation. As discussed in Section 

6.3, there were 2.15 inches of precipitation in July, but no precipitation in June, 2008. There is 

also one more day in July than June; therefore, the total NOx monthly emissions in July are 

higher than in June.

Figure 6.4–1. Monthly emissions of NOx in Maricopa County (pink solid line, abbreviated as “MC”) and the 

PM10 NAA (blue solid line, abbreviated as “NA”).
2008 Maricopa Co. PM10 Emission Inventory 130 June 2011 

Table 6.4–2. Monthly biogenic emissions of NOx in the PM10 NAA and Maricopa County.

PM10 NAA Maricopa County

Month Metric tons/mo Tons/mo Metric tons/mo Tons/mo

January 3.94 4.35 11.01 12.14

February 4.87 5.37 13.95 15.37

March 12.81 14.12 35.06 38.65

April 18.05 19.90 49.76 54.85

May 22.35 24.64 59.62 65.72

June 54.56 60.15 141.88 156.40

July 58.24 64.20 152.83 168.46

August 52.76 58.16 139.04 153.27

September 39.96 44.05 113.54 125.16

October 20.18 22.26 57.04 62.87

November 9.86 10.86 27.32 30.12

December 4.30 4.74 12.03 13.26

Totals: 301.88 332.77 813.08 896.27

6.5 Summary of biogenic source emissions

Daily mean and annual total biogenic NOx emissions for Maricopa County and the PM10 NAA in 

2008 are summarized in Table 6.5–1. Due to the incorporation of land cover data that are more 

characteristic of plants located in the desert southwest, as well as improvements to the MEGAN 

model, the 2008 data shown in Table 6.5–1 represent a substantial improvement over previous 

biogenic emission estimates for Maricopa County and the PM10 NAA.

Table 6.5–1. Daily mean and annual total NOx emissions from biogenic sources.

Geographic Area

Daily mean Annual total

kg/day lbs/day Metric tons/yr Tons/yr

Maricopa County 2,218.1 4,890.0 813.08 896.27

PM10 NAA 823.4 1,815.3 301.88 332.77

6.6 References

ENVIRON International Corp., 2006. Final Report, Maricopa Association of Governments 2006 

Biogenics Study.

Guenther, A., T. Karl, P. Harley, C. Wiedinmyer, P. I. Palmer, and C. Geron, 2006. Estimates of 

global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and 

Aerosols from Nature), Atmos. Chem. Phys., 6, 1-30.

Guenther, A., 2006a. User’s Guide to Processing Driving Variables for Model of Emissions of 

Gases and Aerosols from Nature (MEGAN).

Guenther, A., 2006b. User’s Guide to the Model of Emissions of Gases and Aerosols from 

Nature (MEGAN) Version MEGAN-VBA-2.0.

Guenther, 2007. Corrigendum to "Estimates of global terrestrial isoprene emissions using 

MEGAN (Model of Emissions of Gases and Aerosols from Nature)" Atmos. Chem. Phys., 6, 

3181–3210, 2006, Atmos. Chem. Phys., 7, p. 4327.

MAG, 2007. Eight-Hour Ozone Plan for the Maricopa Nonattainment Area. Maricopa 

Association of Governments, Phoenix AZ.

MAG, 2009. MAG Eight-Hour Ozone Redesignation Request and Maintenance Plan for the 

Maricopa Nonattainment Area. Maricopa Association of Governments, Phoenix AZ. 
Appendix 1. Public Comment Period Documentation

A1-1

Public Information Officer

Maricopa County Air Quality

1001 N. Central Avenue

Suite 900

Phoenix, Arizona 85004

(602) 506-6713, desk

(602) 526-7307, cell

Maricopa County Air Quality Department

NEWS RELEASE

April 26, 2010

Contact: Holly Ward: 602-506-6713/desk * 602-526-7307/cell

FOR IMMEDIATE RELEASE 

Emissions Inventory Public Review Draft Released 

Document details sources of air pollution emissions within Maricopa 

County; public workshop to be held May 14

The Maricopa County Air Quality Department announced today the release of its 

draft 2008 Periodic Emissions Inventory for PM10 for the Maricopa County PM10

Nonattainment Area. The document is now available for an informal 30-day public 

review period. The PM10 emissions inventory includes emissions estimates for PM10 

and PM2.5 as well as three particulate matter precursors: nitrogen oxides (NOx), sulfur 

oxides (SOx) and ammonia (NH3).

The inventory provides emission estimates from point, area, nonroad mobile, onroad 

mobile and biogenic sources. The report is divided into six chapters, as follows:

Chapter 1: Introduction

Chapter 2: (Stationary) point sources (large manufacturing facilities, power 

plants) 

Chapter 3: Area (non-point) sources (widespread, similar sources, such as fuel 

combustion, fires, etc.)

Chapter 4: Nonroad mobile sources (aircraft, locomotives, lawn movers, tractors, 

etc.)

Chapter 5: Onroad mobile sources (cars, trucks, other vehicles)

Chapter 6: Biogenic sources (crops, indigenous vegetation, landscaping, etc.)

The latter two chapters were prepared by the Maricopa Association of Governments 

(MAG).

The document is available in electronic format (PDF files) on the department’s 

website at:

http://www.maricopa.gov/aq/divisions/planning_analysis/emissions_inventory/Defau

lt.aspx

The Air Quality Department will hold a public workshop to discuss the draft 2008 

Periodic Emissions Inventory for PM10. The workshop will be held at 9 AM at the 

department’s offices at 1001 N. Central Ave., Suite 560, on Friday, May 14, 2010. 

(continued on next page)
NEWS RELEASE: Maricopa County Air Quality Department

Emissions Inventory Public Review Draft Released April 26, 2010

The department is also accepting written comments on the draft inventory through 

Wednesday, May 26, 2010, 5:00 PM. Comments may be submitted to:

Maricopa County Air Quality Department

Emissions Inventory Unit

1001 N. Central Avenue, Suite 595

Phoenix, AZ 85004

E-mail: EmisInv@mail.maricopa.gov

Questions may be addressed to Bob Downing at bdowning@mail.maricopa.gov. 

####

About Maricopa County Air Quality Department

The Maricopa County Air Quality Department is a regulatory agency whose goal is to ensure 

federal clean air standards are achieved and maintained for the residents and visitors of 

Maricopa County. The department is governed by the Maricopa County Board of Supervisors 

and follows air quality standards set forth by the federal Clean Air Act.
Appendix 2. Instructions for Reporting 2008 Annual Air Pollution Emissions

INSTRUCTIONS

FOR REPORTING 2008

ANNUAL AIR POLLUTION EMISSIONS

January 2009

Emissions Inventory Unit

1001 North Central Avenue, Suite 595

Phoenix, Arizona 85004

(602) 506-6790

(602) 506-6179 (Fax)

Copies of this document, related forms 

and other reference materials are available online at our web site:

http://www.maricopa.gov/aq/divisions/planning_analysis/emissions_inventory/Default.aspx

A2-1
Maricopa County Emissions Inventory Unit ii Instructions for Reporting 2008 Emissions

TABLE OF CONTENTS

WHAT’S NEW FOR 2008?.............................................................................................................. 1

I. INTRODUCTION............................................................................................................................. 2

Steps to Complete Your 2008 Maricopa County Emissions Inventory

II. REPORTING REQUIREMENTS................................................................................................... 3

- Pollutants to be Reported

- Emission Calculation Method Hierarchy

III. CONFIDENTIALITY OF DATA SUBMITTED............................................................................ 5

- Arizona State Statue and Maricopa County Rule

IV. HELPFUL HINTS AND INFORMATION..................................................................................... 6

- What is a Process?

- Processes and Materials That Do Not Have to be Reported

- Grouping Materials and/or Equipment Under One Process ID

- Assigning Identification Numbers (IDs)

- Industry-Specific Instructions

- Commonly Used Conversion Factors

- Additional Resources and Assistance

V. INSTRUCTIONS AND EXAMPLES FOR EMISSIONS REPORTING FORMS

Business Form..................................................................................................................................... 8

Stack Form ......................................................................................................................................... 9

Control Device Form ....................................................................................................................... 10

General Process Form....................................................................................................................... 11

Evaporative Process Form ................................................................................................................ 15

Off-Site Recycling/Disposal Form.................................................................................................... 19

Documentation of Emission Factor Calculations.............................................................................. 20

Data Certification Form (for NON-Title V sources) ........................................................................ 21

How to Calculate an Emission Fee (for Title V sources ONLY)...................................................... 22

Data Certification/Fee Calculation Form (for Title V sources ONLY) ............................................ 23
Maricopa County Emissions Inventory Unit 1 Instructions for Reporting 2008 Emissions

WHAT'S NEW FOR 2008?

Reporting forms:

• Some preprinted information on your report may be different from last year’s version. Please 

review the enclosed forms carefully, and verify all preprinted information. 

• Many of our reporting forms have changed in past years. If you use your own forms, or a 

computerized reproduction of our forms, the forms used MUST conform to the current information 

requirements and FORMAT as supplied on our preprinted forms. “Homemade” reporting forms that 

vary significantly from the preprinted forms sent to you will not be accepted. 

• Please VERIFY that your reporting forms match the preprinted forms.

Miscellaneous:

• If this is the first emissions inventory for your permit and your business did not operate in 2008, 

you must still submit a completed Business Form and a signed Data Certification Form stating 

that there were no operations at your facility during 2008.

• In accordance with Maricopa County Air Pollution Control Rule 280 (Fees), the 2008 annual emission 

fee for Title V sources only is $38.25/ton. NOTE: Only Title V sources (those whose air quality 

permit numbers have a “V” prefix) are subject to this annual emissions fee.
Maricopa County Emissions Inventory Unit 2 Instructions for Reporting 2008 Emissions

I. INTRODUCTION

An annual emissions inventory is a document submitted by a business that: (1) lists all processes emitting 

reportable air pollutants and (2) provides details about each of those processes. Submitting the emissions 

inventory report is required as a condition of your Maricopa County Air Quality Permit. A separate 

emissions report is required for each business location with its own air quality permit.

Follow these steps to complete your 2008 Maricopa County emissions inventory:

STEP 1: Determine which forms are needed for your business. There are eight different forms available, 

but not all are required for every type of business. For most permitted sources, the packet you received from 

us contains the necessary preprinted forms based on your site’s most recent emissions inventory.

1. Business Form: Contains general contact information about the permitted site. This form is required 

for all businesses.

2. Stack Form: Only required if your business location annually emits over 10 tons of a single pollutant

(CO, VOC, NOx, PM10, or SOx). A “stack” is defined as a stack, pipe, vent or opening through which a 

significant percentage of emissions (from one or more processes) are released into the atmosphere. See 

the “Stack Form Instructions” on page 9 for specific requirements.

3. Control Device Form: Required only if there is one or more emission control devices used at the 

business location.

4. General Process Form and

5. Evaporative Process Form }Either or both will be required for all businesses. :

6. Off-Site Recycling/Disposal Form: Required if you want to claim off-site recycling or disposal.

7. Emission Factor Calculations: Required as attachment for each process for which you calculated 

your own emission factors.

8. Data Certification Form or Data Certification/Fee Calculation Form: Only sources with a Title V

(permit number would start with “V”) permit are required to pay a fee for their emissions and need to 

use the Data Certification/Fee Calculation Form. All other sources use the Data Certification Form. 

STEP 2: Complete the applicable forms. Verify all preprinted information, and make corrections where 

necessary. When making corrections, strike out the preprinted data and write in corrections beside it. Please 

make all changes readily noticeable. Detailed information on how to complete the most common forms is 

included in this document. The packet you received also contains information about other resources 

(workshops, one-on-one assistance, etc.) available to help you in completing the necessary forms.

STEP 3: Make a copy of your completed emissions inventory report. Make sure to KEEP COPIES of all 

forms submitted and copies of all records and calculations used in completing the forms. Air pollution 

control regulations require that you keep all documentation for at least FIVE YEARS at the location where 

pollution is being emitted.

STEP 4: Make sure the Data Certification Form (or Data Certification/Fee Calculation Form for Title V 

sources) is signed by a company representative. Include your air quality permit number on all correspondence and applicable checks submitted with your report. Return the original, signed copy of your 

annual emission report, with payment for any applicable emission fees to:

MCAQD One Stop Shop 

Emissions Inventory Intake

501 N. 44th St. Suite 200

Phoenix AZ 85008-6538
Maricopa County Emissions Inventory Unit 3 Instructions for Reporting 2008 Emissions

II. REPORTING REQUIREMENTS

POLLUTANTS TO BE REPORTED:

Your emissions inventory must include your business’s emissions of the following air pollutants:

CO = Carbon monoxide

NOx = Nitrogen oxides

PM10 = Particulate matter less than 10 microns

SOx = Sulfur oxides

VOC = Volatile organic compounds *

HAP&NON = Hazardous Air Pollutant (HAP) that is also NOT a volatile organic compound (VOC)**

NHx = Ammonia and ammonium compounds

Pb = Lead

* A volatile organic compound (VOC) is defined as any compound of carbon that participates in atmospheric photochemical reactions. This definition excludes: carbon monoxide, carbon dioxide, acetone, 

carbonic acid, metallic carbides or carbonates, and ammonium carbonate, as well as certain other organic 

compounds. (See Maricopa County Air Pollution Control Rule 100, Sections 200.69 and 200.110 for a full 

definition.)

EPA has re-designated the chemical t-butyl acetate (CAS Number 540-88-5) as a VOC for record-keeping 

requirements and emissions reporting, but not for emission limitations or content requirements. County Rule 

100, Section 200.69b states:

“The following compound(s) are VOC for purposes of all recordkeeping, emissions reporting, photochemical 

dispersion modeling and inventory requirements which apply to VOC and shall be uniquely identified in 

emission reports, but are not VOC for purposes of VOC emissions limitations or VOC content requirements:

t-butyl acetate (540-88-5).”

Therefore, if your facility uses t-butyl acetate, it is necessary to report t-butyl acetate as a separate material 

on the evaporative process form, not as part of a grouped material (e.g., solvents, thinners, activators, etc.). 

T-butyl acetate will continue to be identified as a VOC on your emission report and count towards any 

applicable emission fees.

** HAP&NON: Usage of certain materials that are: (1) a Hazardous Air Pollutant (HAP) and (2) not also a 

VOC (that is, not also an ozone precursor) should also be reported if:

(a) your site is subject to a Federal MACT (Maximum Achievable Control Technology) standard or

(b) your air quality permit contains specific quantitative limits for HAP emissions.

The most common materials categorized as “HAP&NON” include:

• methylene chloride (dichloromethane)

• perchloroethylene

• 111-trichloroethane (111-TCA or methyl chloroform)

• hydrochloric acid

• hydrofluoric acid

NOTE: HAPs that are also considered volatile organic compounds are reported as VOC.
Maricopa County Emissions Inventory Unit 4 Instructions for Reporting 2008 Emissions

EMISSION CALCULATION METHOD HIERARCHY

When preparing emission information for your report, the most accurate method for calculating actual

emissions must be used. The hierarchy listed below outlines the preferred methods for calculating emission 

estimates (taken from County Rule 280, Section 305.1). 

:

(1) Whenever available, emissions estimates should be calculated from continuous emissions 

monitors certified under 40 CFR Part 75, Subpart C, or data quality assured pursuant to 

Appendix F of 40 CFR, Part 60.

(2) When sufficient data obtained using the methods described in paragraph 1 is not available,

emissions estimates should be calculated from source performance tests conducted pursuant to 

Rule 270 in Maricopa County’s Air Pollution Control Rules and Regulations.

(3) When sufficient data obtained using the methods described in paragraphs 1 or 2 is not available, 

emissions estimates should be calculated from material balance using engineering knowledge of 

the process.

(4) When sufficient data obtained using the methods described in paragraphs 1 through 3 is not 

available, emissions estimates shall be calculated using emissions factors from EPA Publication 

No. AP-42 "Compilation of Air Pollutant Emission Factors," Volume I: Stationary Point and 

Area Sources.

(5) When sufficient data obtained using the methods described in paragraphs 1 through 4 is not 

available, emissions estimates should be calculated by equivalent methods supported by back-up 

documentation that will substantiate the chosen method.
Maricopa County Emissions Inventory Unit 5 Instructions for Reporting 2008 Emissions

III. CONFIDENTIALITY OF DATA SUBMITTED

Information submitted in your annual emissions reports must be made available to the public unless it meets 

certain criteria of Arizona State Statutes and Maricopa County Rules. Applicable excerpts concerning 

confidentiality of data are reproduced below.

ARS § 49-487 D. ...the following information shall be available to the public:...

2. The chemical constituents, concentrations and amounts of any emission of any air contaminant. ...

MARICOPA COUNTY AIR POLLUTION CONTROL RULES AND REGULATIONS, Rule 100:

§ 200.107 TRADE SECRETS - Information to which all of the following apply:

a. A person has taken reasonable measures to protect from disclosure and the person intends to continue to 

take such measures.

b. The information is not, and has not been, reasonably obtainable without the person’s consent by other 

persons, other than governmental bodies, by use of legitimate means, other than discovery based on a 

showing of special need in a judicial or quasi-judicial proceeding.

c. No statute, including ARS §49-487, specifically requires disclosure of the information to the public.

d. The person has satisfactorily shown that disclosure of the information is likely to cause substantial harm to 

the business’s competitive position.

§ 402 CONFIDENTIALITY OF INFORMATION:

402.2 Any records, reports or information obtained from any person under these rules shall be available to the 

public ... unless a person:

a. Precisely identifies the information in the permit(s), records, or reports which is considered confidential.

b. Provides sufficient supporting information to allow the Control Officer to evaluate whether such information 

satisfies the requirements related to trade secrets as defined in Section 200.107 of this rule.

For emissions inventory information to be deemed confidential, the following steps must be followed:

• Specific data which you request be held confidential must be identified by marking an “X” in the 

corresponding gray confidentiality box(es) on the relevant report forms.

• Provide a written explanation which gives factual information satisfactorily describing why releasing this 

information could cause substantial harm to the business’s competitive position.

• Use the gray-shaded boxes on the reporting forms to indicate which data are to be held confidential. Do 

NOT stamp “Confidential”, highlight data, or otherwise mark the page.

No data can be held confidential without proper justification.
Maricopa County Emissions Inventory Unit 6 Instructions for Reporting 2008 Emissions

IV. HELPFUL HINTS AND INFORMATION

Be sure to verify all preprinted information on forms. If any information is incorrect or blank, please provide 

correct information. Making a change on the Business Form will NOT transfer the permit ownership or 

location. You must contact the Department's One Stop Shop at (602) 506-6464 to accomplish this.

WHAT IS A PROCESS? A process is a business activity at your location that emits one or more of the 

pollutants listed on page 3, and has only one material type as input and one operating schedule. For each 

applicable process at your business, you must assign a unique Process ID number to differentiate each 

process.

PROCESSES AND MATERIALS THAT DO NOT HAVE TO BE REPORTED:

• Welding.

• Acetone usage.

• Fuel use for forklifts or other vehicles. (NOTE: Fuel use in non-vehicle engines is reportable.)

• Soil remediation activities. (Note: Other periodic reporting requirements may exist; consult your permit.)

• Storage emissions from fuels or organic chemicals in any tank with a capacity of 250 gallons or less.

• Storage emissions of diesel and Jet A fuel in underground tanks of any size.

• Storage emissions of diesel and Jet A fuel in aboveground tanks, with throughput < 4,000,000 gal/yr.

• Routine pesticide usage, housekeeping cleaners, and routine maintenance painting at your facility.

Please group all similar equipment and materials together before applying the following limitations:

• Internal combustion engines (e.g., emergency generators) or external combustion equipment (e.g., boilers 

and heaters) that operated less than 100 hrs. and burned less than 200 gals. diesel or gas, or less than 

100,000 cubic feet of natural gas.

• Materials with usage of less than 15 gallons or 100 pounds per year.

GROUPING MATERIALS AND/OR EQUIPMENT UNDER ONE PROCESS ID:

You can group together under one process ID:

• All internal combustion engines less than 600 hp if they burn the same fuel and have similar operating 

schedules.

• All external combustion equipment (boilers, heaters) with a capacity of less than 10,000,000 Btu per 

hour if they burn the same fuel and have similar operating schedules.

• All similar evaporative materials with similar emission factors that have similar operating schedules and 

process descriptions. For example, group low-VOC red paint, green paint and white paint together as 

one material: “Paint: Low-VOC.” Do not group dissimilar materials together, such as thinners and 

paints. Attach documentation (see example, p. 20) showing how the grouped emission factor was 

determined. 

• All underground tanks with the same fuel and same type of vapor recovery system.

ASSIGNING IDENTIFICATION NUMBERS (IDs)

Unique IDs are required for the following report elements: Stacks, Control Devices and Processes. For 

processes, that means a process ID number may be used only once on each General Process form and for 

each material reported on the Evaporative Process Forms.

:

These numbers are usually assigned by the person who prepares the original report. If you are adding a new 

item to a preprinted report, assign a number not already in use. Once an ID number is assigned, continue 

using the same number for that item each year. If that item is no longer reportable, mark it with ‘DELETE’ 

and return the preprinted form with a brief explanation. Do not use that ID number again.
Maricopa County Emissions Inventory Unit 7 Instructions for Reporting 2008 Emissions

INDUSTRY-SPECIFIC INSTRUCTIONS: Additional help sheets, detailed examples, and special 

instructions are available for a number of specific processes or industries listed below. To get copies of any 

of these documents, please visit our web site at:

http://www.maricopa.gov/aq/divisions/planning_analysis/emissions_inventory/Default.aspx

or call (602) 506-6790.

• Bakeries • Natural Gas Boilers/Heaters • Using EPA's TANKS 4.09d Program

• Concrete Batch Plants • Polyester Resin • Vehicle Refinishing

• Fuel Storage and Handling • Printing Plants • Vehicle Travel on Unpaved Roads

• Incinerators and Crematories • Roofing Asphalt • Woodworking

• Lg. Aboveground Storage Tanks • Sand and Gravel Plants

COMMONLY USED CONVERSION FACTORS:

1 gram/liter = 0.00834 lbs/gal 1 foot = 0.0001894 mile

1 liter = 0.2642 gallon (US) 1 square foot = 0.000022957 acre

1 therm = 0.0000952 MMCF 1 pound = 0.0005 ton

NOTE: MM = 1,000,000 Example: MMCF = 1,000,000 cubic feet

M = 1,000 Example: MGAL = 1,000 gallons

ADDITIONAL RESOURCES AND ASSISTANCE:

The Maricopa County Emissions Inventory web site at:

http://www.maricopa.gov/aq/divisions/planning_analysis/emissions_inventory/Default.aspx

contains additional reference materials, such as:

• blank copies of most emissions reporting forms.

• an updated list of emission factors for a large number of industrial processes, including SCC codes.

• a list of Tier Codes for industrial processes.

• detailed help sheets for a number of specific industries or processes.

To receive any of the above materials by fax or mail, or for additional information or assistance in how to 

calculate and report your emissions, please call us at (602) 506-6790.
Maricopa County Emissions Inventory Unit 8 Instructions for Reporting 2008 Emissions

V. INSTRUCTIONS AND EXAMPLES FOR COMPLETING EMISSIONS REPORTING FORMS

Business Form Instructions

Verify all preprinted information, and make corrections where necessary. When making corrections, strike 

out the preprinted data and write in corrections beside it. Please make all changes readily noticeable.

NOTE: Indicating a change in ownership or business location on the Business Form will not serve to 

transfer the permit ownership or location. You must contact the MCAQD One Stop Shop at (602) 506-6464

to accomplish this.

Data fields:

6 Number of employees: This should be the annual average number of full-time equivalent (FTE) 

employee positions at this business location.

9 NAICS Code: This 5- or 6-digit North American Industrial Classification System (NAICS) code has 

been introduced to replace the 4-digit Standard Industrial Classification (SIC) codes. Please list the 

primary and secondary NAICS codes for your business, if known. (Consult our website, at:

http://www.maricopa.gov/aq/divisions/planning_analysis/emissions_inventory/Default.aspx, for a link to 

a full list of NAICS codes.) 

10 Preparer of the Inventory (primary contact for technical questions concerning this report): This should be 

the person who knows the most about the data in the report. If this person has an e-mail address used for 

business purposes, please provide it.
Maricopa County Emissions Inventory Unit 9 Instructions for Reporting 2008 Emissions

Stack Form Instructions

A “stack” is defined as a stationary stack, pipe, vent or opening through which a significant percentage of 

emissions (from one or more processes) are released into the atmosphere (with or without a control device).

NOTE: Stack information is required only if your business location annually emits over 10 tons of any one 

individual pollutant. If so, you must complete a Stack Form for:

• each stack connected to a control device.

• any stack that discharges annually more than 5 tons of combined pollutant emissions (such as a paint 

booth exhaust).

EXAMPLE Stack Form Information:

1 2 3 4 5a OR 5b 6a OR 6b & 6c 7

Stack 

ID

Stack 

Type 

Code*

Stack 

Height**

Exit Gas 

Temperature

Velocity

feet/sec

Flow Rate

acfm

Diameter

inside inch

Length / Width

inside inch

Stack Name/Description. Include lat/long 

coordinates of stack (in decimal degrees)

1 W 30 ft 90 o

F 20,000 36 paint booth Lat: N33. 5276 

 Long: W1 1 2. 2626 

2 V 14 ft 200 o

F 19,186 40 thermal oxidizer, Bldg. 2

Lat:N33. 5259 Long:W1 1 2. 261 1 

* Stack Type Codes: V = Vertical unobstructed H = Horizontal unobstructed

D = Downward unobstructed G = Gooseneck

W = Obstructed vertical (e.g. weather cap)

** Stack height is calculated relative to the surrounding terrain. For instance, the stack height of a 10-foot 

stack on top of a 20-foot tall building is 30 feet.

Data fields:

1 Stack ID: (See “Assigning Identification Numbers” on page 6.) A number (up to three digits, numeric 

only) which identifies a specific stack. It is suggested you start with 1, then 2, etc.

4 Exit Gas Temperature: Should represent average operating conditions, in degrees Fahrenheit.

DO NOT report “ambient”.

5a Exit Gas Velocity: OR 5b Gas Flow Rate:

Provide EITHER the exit velocity (in feet per second) OR the flow rate of gas (in actual cubic feet per 

minute) exiting the stack during normal operations. Preprinted information provides both.

6a Inside Stack Diameter: For round stacks, provide Inside Stack Diameter in inches.

OR

6b & 6c Inside Stack Length and Width: For square or rectangular stacks, provide inside Length and inside

Width in inches. 

7 Stack Name/Description and Lat/Long Coordinates: Provide a brief text description of the stack along 

with the latitude and longitude coordinates of the stack (in decimal degrees).
Maricopa County Emissions Inventory Unit 10 Instructions for Reporting 2008 Emissions

Control Device Form Instructions

EXAMPLE Control Device Form Information

1 2 3 4 5 6

Control 

ID

Installation/ 

Reconstruction* 

Date

Size or Rated Capacity** Control 

Type Code

Control Device 

Name/Description

Stack ID

1 05/09/98 25,000.0 cfm 021 Thermal oxidizer 2

4 03/10/97 cfm 153 Watering with water trucks

Data fields:

1 Control ID: (See “Assigning Identification Numbers” on page 6.) A unique number (up to three digits) 

that you assign to identify a specific control device.

2 Installation/Reconstruction Date: The completion date (given in mm/dd/yy format) of installation or the 

most recent reconstruction of the identified control device. This is not a date on which routine repair or 

maintenance was done. “Reconstruction” means any component of the control device was replaced and 

the cost (fixed capital) of the new component(s) was more than half of what it would have cost to 

purchase or construct a new control device.

3 Size or Rated Capacity: Report the air or water flow rate in cubic feet per minute. Some devices (e.g., 

water trucks for dust control) will not include a value in this field.

4 Control Type Code: A 3-digit code designating the type of control device. A complete list of all EPA 

control device codes can be found on the Web at: http://www.maricopa.gov/aq/divisions/

planning_analysis/emissions inventory/Default.aspx or call (602) 506-6790 for assistance. 

6 Stack ID: Not all businesses require a Stack ID. This is required if the Stack Form is used for your site 

(see page 9) and the control device is vented through that identified stack. This is the ID number shown 

in column 1 of the Stack Form. The Stack ID can be entered on this form after the Stack Form has been 

filled out.
Maricopa County Emissions Inventory Unit 11 Instructions for Reporting 2008 Emissions

General Process Form Instructions

The General Process Form is used to record data on all emissions-producing processes except evaporative 

processes. A “general process” is normally characterized by the burning or handling of a material. One 

form reports all the pollutants for one process. For example, several pollutants are produced by burning fuel, 

and PM10 is emitted by processing rock products, processing materials such as wood or cotton, and driving 

on unpaved areas.

Data fields: (See sample forms on pages 13 and 14.)

1 Process ID: A number (up to three digits) that is preprinted or you assign. (See “Assigning Identification 

Numbers” on page 6.) This Process ID number can not be used for any other process at this location.

2 Process Type/Description: Brief details on the type of activity that is occurring. 

3 Stack ID(s): The stack ID number(s) shown in column 1 of the Stack Form that identify the stack(s) 

which vent pollution created by this process. Not all businesses are required to report stacks. This is only 

required if the Stack Form is required for your site (see page 9) and the process has a stack.

4 Process Tier Code and If these codes are not preprinted on your form, please consult the 

5 SCC Code: section “Other Resources” on our web site, or call (602) 506-6790.

6 Seasonal Throughput Percent: Enter the percent of total annual operating time that occurred per season, 

rounded to the nearest percent. For example, “Dec-Feb 30% ” means 30% of total annual activity 

occurred in January, February and December 2008. The total for all four seasons must equal 100%.

7 Normal Operating Schedule and These reflect the normal daily, weekly, and annual operating 

8 Typical Hours of Operation: parameters of this process during 2008.

9 Emissions Based on: Provide the name of the material used, fuel used, product produced, or whatever 

was measured for the purpose of calculating emissions, such as “natural gas”, “hours of operation,” 

“vehicle miles traveled,” or “acres.”

10 Used, Produced or Existing: Indicate whether calculated emissions are based on a material type or fuel

used (an input, such as “paint” or “natural gas”), or an output (such as “sawdust produced” or “finished 

product”). Use “Existing” if the parameter reported on line 9 is not directly used or produced in the 

process (such as “vehicle miles traveled” or “acres”).

11 Annual Amount: The annual amount (a number) of material that was used, fuel combusted, product 

produced, hours of operation, vehicle miles traveled, or acres.

12 Fuel Sulfur Content (in percent): For processes that involve the combustion of oil or diesel fuels, report 

the sulfur content of the fuel as a decimal value. Example: 0.05 % (= 500 ppm) 

13 Unit of Measure: Units of the material used, fuel used or product produced shown on line 9. 

For example: gallons, pounds, tons, therms, acres, vehicle miles traveled, units produced.

14 Unit Conversion Factor: You must provide this if you use an emission factor with an emission factor unit 

(see item 17 below) that is not the same as the unit of measure (from line 13). This is the standard

number you would multiply your amount (line 11) by to convert it to the units of the emission factor. See 

page 7 for a list of commonly used conversion factors.
Maricopa County Emissions Inventory Unit 12 Instructions for Reporting 2008 Emissions

General Process Form Instructions (continued)

15 Pollutant: See page 3 for a list of pollutants that need to be reported.

16 Emission Factor (EF): The number to be multiplied by the annual amount (line 11) to determine how 

much of the pollutant was emitted. If you calculate your own emission factor or change the preprinted 

emission factor, you must provide details of your calculations in an attachment.

17 Emission Factor (EF) Units: Enter the appropriate Emission Factor Units in pounds (lb) per unit; e.g., 

lb/ton, lb/MMCF, lb/gal.

18 Controlled Emission Factor (EF)? YES or NO: Indicate “YES” if: 1) you have your own emission factor 

from testing and included the control device efficiency within the factor, or 2) the emission factor used is 

clearly identified as a controlled emission factor. A “YES” response requires the use of Formula A (see 

#25 below). Indicate “NO” if: 1) there is no emission control device, or 2) the emission factor represents 

emission rates before controls. A “NO” response requires the use of Formula B (see #25 below). 

19 Calculation Method: Enter the number code (listed at the bottom of the General Process Form) which 

best describes the method you used to obtain this emission factor. Code 5, “AP-42/FIRE Method or 

Emission Factor” means that the factor comes from EPA documents or software. NOTE: If you have

continuous emissions monitors (CEM) data or conducted a source test that was required and approved by 

the County for a specific process or piece of equipment, you must use the emission data from the CEM 

or the test results. Report “1” in this column for CEM data or “4” for performance test data.

20 through 24: Leave blank if there is no control device.

20 Capture % Efficiency: The percent of the pollutant that is captured and sent to the primary control 

device in this process. Be sure to list capture efficiency separately for each pollutant affected.

21 Primary Control Device ID: If this pollutant is being controlled in this process, enter the Control 

Device ID number which represents the first control device affecting the pollutant.

22 Secondary Control Device ID: If this pollutant is being controlled sequentially by 2 devices, enter 

the Control Device ID number which represents the second control device; otherwise leave this field 

blank.

23 Control Device(s) % Efficiency: Enter the total control efficiency of the control device(s). Be sure to 

list control device efficiency separately for each pollutant affected. If you report control device 

efficiency, you must also show capture efficiency in column 20.

24 Efficiency Reference Code: Enter the code (1 through 6) that best describes how you determined the 

control device efficiency. A list of possible codes is included at the bottom of the form.

25 Estimated Actual Emissions (in pounds/year): You may round the calculated emissions values to the 

nearest pound. Calculate as follows:

A. Emissions with no controls or controls are reflected in the emission factor:

Column 25 = line 11 × line 14 × column 16

B. Emissions after control:

Column 25 = line 11 × line 14 × column 16 × (1 – [column 20 × column 23])

Use the decimal equivalent for columns 20 and 23. Example: 96.123% = 0.96123
Maricopa County Emissions Inventory Unit 13 Instructions for Reporting 2008 Emissions

General Process Form 2008 EXAMPLE: Internal Combustion Permit number(s) V99999

Place an X in any gray cell to mark data requested to be held confidential. See page 5 for requirements for information to be deemed confidential.

1- Process ID 80 

2- Process Type/Description: 3 ENGINES FOR CRUSHING (EACH LESS THAN 600 HP)

3- Stack ID(s) (only if required on Stack Form) _______ ________ ________ ________ ________

4- Process TIER Code: 020599 FUEL COMB. INDUSTRIAL: INTERNAL COMBUSTION

5- SCC Code 20200102 (8 digit number) IND:DIESEL-RECIPROCATING

6- Seasonal Throughput Percent: Dec-Feb 25 % Mar-May 25 % Jun-Aug 25 % Sep-Nov 25 %

7- Normal Operating Schedule: Hours/Day 8 Days/Week 5 Hours/Year 2080 Weeks/Year 52 x

8- Typical Hours of Operation: (military time) Start 0700 End 1530

9- Emissions based on (name of material or other parameter, e.g. “rock”, “diesel”, “vehicle miles traveled”) DIESEL

10- Used (input) or Produced (output) or Existing (e.g. VMT, acres)

11- Annual Amount: (a number) 16,250 12- Fuel Sulfur Content (in percent) __0.05_______%

13- Unit of Measure: (for example: tons, gallons, million cu ft, acres, units produced, etc.) GALLONS

14- Unit Conversion Factor (if needed to convert Unit of Measure to correlate with emission factor units) 0.001

Emission Factor (EF) Information Control Device Information

15 16 17 18 19 20 21 22 23 24 25

Pollutant Emission

Factor (EF) 

(number)

Emission

Factor 

Unit (lb per)

Controlled 

EF?

Yes or No

Calculation 

Method 

Code*

Capture % 

Efficiency

Primary 

Control 

Device ID

Secondary 

Control 

Device ID

Control 

Device(s) % 

Efficiency

Efficiency

Reference 

Code**

Estimated Actual 

Emissions

CO 130 M GALS N 5 2,113 lbs 

NOx 604 M GALS N 5 9,815 lbs 

PM-10 42.5 M GALS N 5 691 lbs 

SOx 39.7 M GALS N 5 645 lbs 

VOC 49.3 M GALS N 5 801 lbs 

* Calculation Method Codes:

1 = Continuous Emissions Monitoring Measurements

2 = Best Guess / Engineering Judgment 

3 = Material Balance

4 = Source Test Measurements (Stack Test)

5 = AP-42 / FIRE Method or Emission Factor 

6 = State or Local Agency Emission Factor

7 = Manufacturer Specifications

8 = Site-Specific Emission Factor

9 = Vendor Emission Factor

10 = Trade Group Emission Factor

** Control Efficiency Reference Codes:

1 = Tested efficiency / EPA reference method

2 = Tested efficiency / other source test method

3 = Design value from manufacturer

4 = Best guess / engineering estimate

5 = Calculated based on material balance

6 = Estimated, based on a published value
Maricopa County Emissions Inventory Unit 14 Instructions for Reporting 2008 Emissions

General Process Form 2008 EXAMPLE: Unpaved Road Travel Permit number(s) V99999

Place an X in any gray cell to mark data requested to be held confidential. See page 5 for requirements for information to be deemed confidential.

1- Process ID 28 

2- Process Type/Description: UNPAVED ROAD TRAVEL: HEAVY-DUTY TRUCKS @ 15 MPH 

3- Stack ID(s) (only if required on Stack Form) _______ ________ ________ ________ ________

4- Process TIER Code: 140799 MISCELLANEOUS: FUGITIVE DUST 

5- SCC Code 30502504 (8 digit number) SAND/GRAVEL: HAULING 

6- Seasonal Throughput Percent: Dec-Feb 25 % Mar-May 25 % Jun-Aug 25 % Sep-Nov 25 %

7- Normal Operating Schedule: Hours/Day 8 Days/Week 5 Hours/Year 2080 Weeks/Year 52 x 

8- Typical Hours of Operation: (military time) Start 0700 End 1530

9- Emissions based on (name of material or other parameter, e.g. “rock”, “diesel”, “vehicle miles traveled”) VEHICLE MILES TRAVELED (VMT)

10- Used (input) or Produced (output) or Existing (e.g. VMT, acres)

11- Annual Amount: (a number) 7,500 12- Fuel Sulfur Content (in percent) ______________%

13- Unit of Measure: (for example: tons, gallons, million cu ft, acres, units produced, etc.) VMT 

14- Unit Conversion Factor (if needed to convert Unit of Measure to correlate with emission factor units) 

Emission Factor (EF) Information Control Device Information

15 16 17 18 19 20 21 22 23 24 25

Pollutant Emission

Factor (EF) 

(number)

Emission

Factor 

Unit (lb per)

Controlled 

EF?

Yes or No

Calculation 

Method 

Code*

Capture % 

Efficiency

Primary 

Control 

Device ID

Secondary 

Control 

Device ID

Control 

Device(s) % 

Efficiency

Efficiency

Reference 

Code**

Estimated Actual 

Emissions

PM-10 3.2 VMT N 6 100 4 70 6 7200 lbs 

lbs 

lbs 

lbs 

lbs 

lbs 

NOTE: Emissions in col. 25 are calculated as follows: (line 11 × col. 16) × (1 – [col. 20 × col. 23])

* Calculation Method Codes:

1 = Continuous Emissions Monitoring Measurements

2 = Best Guess / Engineering Judgment 

3 = Material Balance

4 = Source Test Measurements (Stack Test)

5 = AP-42 / FIRE Method or Emission Factor

6 = State or Local Agency Emission Factor

7 = Manufacturer Specifications

8 = Site-Specific Emission Factor

9 = Vendor Emission Factor

10 = Trade Group Emission Factor

** Control Efficiency Reference Codes

1 = Tested efficiency / EPA reference method

2 = Tested efficiency / other source test method

3 = Design value from manufacturer

4 = Best guess / engineering estimate

5 = Calculated based on material balance

6 = Estimated, based on a published value
Maricopa County Emissions Inventory Unit 15 Instructions for Reporting 2008 Emissions 

Evaporative Process Form Instructions 

The Evaporative Process Form is used to report all emissions produced by evaporation. Examples include: 

cleaning with solvents, painting and other coatings, printing, using resin, evaporation of fuels from storage 

tanks, ammonia use, etc. All other processes should be shown on the General Process Form.

One Evaporative Process Form may be used to report numerous materials, with each material given a 

separate process ID number, as long as the information on lines 1–5 apply to all items on that form. Use a 

separate form for each group of materials that has a different Process Type/Description (shown on line 1), 

different Tier Code (line 2) or different operating schedule (lines 3, 4, or 5). 

Data fields: (See sample forms on pages 17 and 18.)

1 Process Type/Description: Brief details of the activity in which the listed materials were used.

2 Process Tier Code: If this 6-digit code is not preprinted on your form, please refer to the Tier Code list 

at: http://www.maricopa.gov/aq/divisions/planning_analysis/emissions_inventory/Default.aspx

or call (602) 506-6790.

3 Seasonal Throughput Percent: Enter the percent of total annual operating time that occurred per season 

(rounded to the nearest percent). For example, “Dec-Feb 30% ” means 30% of the total annual activity 

occurred during January, February and December 2008. The total for all four seasons must equal 100%.

4 Normal Operating Schedule and These represent the usual number of hours, time of day and weeks

5 Typical Hours of Operation: per year when this process occurred during the calendar year.

6 Process ID: A number (up to three digits) that represents this specific material (process). Each process 

on one form must have the same tier code and operating schedule as that shown in the top portion of the 

form. This Process ID number can not be used for any other process at this business location. See page 

6 of these instructions for more explanation of ID numbers and for exclusions and guidance on grouping 

materials.

7 Stack ID(s): The stack ID number(s) shown in column 1 of the Stack Form that identify the stack(s) 

which vent pollution created by this process. Not all businesses are required to report stacks. This is only 

required if the Stack Form is required for your site (see page 9) and the process has a stack.

8 Material Type: Provide the name of the material used in this process. Give the chemical name for pure 

chemicals or a name that reflects its use (paint, ink, etc.), rather than just a brand name or code number. 

Examples of materials include: paint, thinner, degreasing solvent (plus its common name), ink, fountain 

solution, ammonia, alcohol, ETO (ethylene oxide), gasoline (in a storage tank).

9 Annual Material Usage/Input: Amount of this material used during the year. In most cases, the amount 

purchased is suitable. Write in “lbs” or “gal” (pounds or gallons).

10 Pollutant: The only pollutants reported on this form are VOC, HAP&NON and NHX (see definitions on 

page 3). When one process (or material) has more than one of these pollutants, list each pollutant on a 

separate line, using the same process ID number.
Maricopa County Emissions Inventory Unit 16 Instructions for Reporting 2008 Emissions 

Evaporative Process Form (continued)

11 Emission Factor (EF): An emission factor is a number used to calculate the pounds of pollutant emitted 

based on the quantity of material used in a process. Emission factors can be obtained from your supplier 

(usually provided on a Material Safety Data Sheet or environmental data sheet), and must correspond 

with the material units reported in column 9. If the material unit is “gal,” then the emission factor must 

be in pounds of pollutant per gallon. If the material unit is “lb,” then the emission factor must be in 

pounds of pollutant per pound of material. 

Verify (and correct, where necessary) all preprinted emission factors, as the composition of materials 

used may have changed since your last report. A “lb/gal” emission factor is almost always less than 8 and 

never greater than 14. A “lb/lb” emission factor is never larger than 1.0.

12 Pounds of pollutant sent off-site: Required only if you wish to take credit for reduced emissions because 

waste of this material is sent off-site for recycling or disposal. Only waste generated during the report 

year may be claimed. The Off-Site Recycling/Disposal Form must be completed if you wish to claim a 

credit. The number of pounds reported in column 12 must equal the number of pounds reported on the 

Off-Site Recycling/Disposal Form(s) for the same Process ID number. 

13 and 14: Leave these fields blank if there is no control device present.

13 Capture % Efficiency: The percent of the pollutant from this process that is captured and sent to the 

control device.

14 Control ID: If this pollutant is being controlled in this process, enter the Control Device ID number 

from column 1 of the Control Device Form.

Control % Efficiency: Enter the percent of this pollutant that is controlled by this control device.

Code: Select the Control Efficiency Reference Code from the list at the bottom of the form.

15 Estimated Emissions (lbs/yr): Estimated pounds of the pollutant emitted during the year, after off-site 

recycling/disposal and controls if applicable. Credit will not be given for off-site recycling/disposal 

unless it is shown on the Off-Site Recycling/Disposal Form. Round to the nearest pound. If the 

answer is 0, give a decimal answer to the first significant digit. Column 15 is calculated as follows:

Emissions without off-site recycling/disposal or controls:

Column 15 = column 9 × column 11

Emissions with off-site recycling/disposal:

Column 15 = (column 9 × column 11) – column 12

Emissions with off-site recycling/disposal and controls:

Column 15 = ([column 9 × column 11] – column 12) × (1 – [column 13 × column 14])

Use the decimal equivalent for columns 13 and 14. Example: 96.123% = 0.96123
Maricopa County Emissions Inventory Unit 17 Instructions for Reporting 2008 Emissions

EXAMPLE: Coating and Painting

Evaporative Process Form 2008 Permit number(s) V99999

Place an X in any gray cell to mark data requested to be held confidential. See page 5 for requirements for information to be deemed confidential.

1- Process Type/Description: Coating metal parts

2- Process TIER Code: 080415 SOLVENT USE: SURFACE COATING - MISC METAL PARTS

3- Seasonal Throughput Percent: Dec-Feb 25 % Mar-May 25 % Jun-Aug 25 % Sep-Nov 25 %

4- Normal Operating Schedule: Hours/Day 8 Days/Week 5 Hours/Year 2080 Weeks/Year 52__ 

5- Typical Hours of Operation (military time) Start 0800 End 1700 

6 7 8 9 10 11 12 13 14 15

Process 

ID

Stack 

ID(s)

Material Type Annual

Usage

Input

lb 

or

gal

VOC, 

HAP&NON

or

NHx

Emission

Factor

EF

Units

(lbs per)

Pounds of 

pollutant* 

sent

off site

Capture

Efficiency

%

Control

ID

Control

Efficiency

%

Control 

Efficiency

Code**

Estimated 

Emissions

(lbs/yr)

800 1 Lacquer

6455-06

95 gl VOC 4.7 gal % % 447

801 1 lacq thinner 120 gl VOC 7.1 gal % % 852

802 1 Paint red 

4039-03

940 gl VOC 4.2 gal % % 3,948

803 1 paint thinner 707 gl VOC 7.0 gal % % 4,949

804 1 powder paint

8730-11

20,200 lb VOC 0.001 lb % % 20

% %

Note: Do NOT change preprinted Process ID numbers. See page 6 of these instructions for information on how to delete materials that are no longer used, or to assign Process 

ID numbers for new materials.

* If you have off-site recycling/disposal of any of the materials listed above, you must complete an Off-site Recycling/Disposal Form to receive 

credit for reduced emissions.

NOTE: Emissions in col. 15 are calculated as follows: ([col. 9 × col. 11] – col. 12) × (1 – [col. 13 × col. 14])

** Control Efficiency Reference Codes

1 = Tested efficiency / EPA reference method 2 = Tested efficiency / other source test method 3 = Design value from manufacturer

4 = Best guess / engineering estimate 5 = Calculated based on material balance 6 = Estimated, based on a published value.
Maricopa County Emissions Inventory Unit 18 Instructions for Reporting 2008 Emissions

EXAMPLE: Cleaning solvent (with recycling)

Evaporative Process Form 2008 Permit number(s) V99999

Place an X in any gray cell to mark data requested to be held confidential. See page 5 for requirements for information to be deemed confidential.

1- Process Type/Description: CLEANING METAL PARTS

2- Process TIER Code: 080103 SOLVENT USE: DEGREASING - COLD CLEANING

3- Seasonal Throughput Percent: Dec-Feb 25 % Mar-May 25 % Jun-Aug 25 % Sep-Nov 25 %

4- Normal Operating Schedule: Hours/Day 8 Days/Week 5 Hours/Year 2080 Weeks/Year 52__ 

5- Typical Hours of Operation (military time) Start 1300 End 1700 

6 7 8 9 10 11 12 13 14 15

Process 

ID

Stack 

ID(s)

Material Type Annual Usage

Input

lb 

or

gal

VOC, 

HAP&NON

or

NHx

Emission

Factor

EF

Units

(lbs per)

Pounds of 

pollutant* 

sent

off site

Capture

Efficiency

%

Control

ID

Control

Efficienc

y

%

Control 

Efficiency

Code**

Estimated 

Emissions

(lbs/yr)

3 2 SANITIZER 716 lb VOC 1.0 lb 95 % 1 80 % 3 172

6 GUN CLEANER 180 gl VOC 7.2 gl 569 % % 727

7 XYZ STRIPPER 1300 gl VOC 3.3 gl 1,884 % % 2,406

8 CLEANING 

SOLVENTS

358 gl VOC 6.4 gl 1,006 % % 1,285

9 MEGASOLVE 2258 gl VOC 6.8 gl 6,741 % % 8,613

% %

Note: Do NOT change preprinted Process ID numbers. See page 6 of these instructions for information on how to delete materials that are no longer used, or to assign Process 

ID numbers for new materials.

* If you have off-site recycling/disposal of any of the materials listed above, you must complete an Off-site Recycling/Disposal Form to receive 

credit for reduced emissions.

NOTE: This example shows the case where 2,400 of the original 4,096 gallons of materials #6 through 9 were captured 

for off-site recycling, and the pollutant content of the waste material was estimated to be 75% of the 

original. The pounds of pollutant sent off-site shown in column 12 is calculated on the example Off-Site 

Recycling/Disposal Form on the next page.
Maricopa County Emissions Inventory Unit 19 Instructions for Reporting 2008 Emissions 

EXAMPLE

Off-Site Recycling/Disposal Form 2008 Permit number(s) V99999

NOTE: If you need blank copies of this form, call the Emissions Inventory Unit at 

(602) 506-6790 or consult our web page at 

http://www.maricopa.gov/aq/divisions/planning_analysis/emissions_inventory/Default.aspx

Provide one off-site recycling/disposal form for each waste stream at your business location. A waste stream is the waste from one 

or more processes mixed together to make one waste product before it is taken off site for recycling, disposal or combustion.

1) Assign a unique two-digit ID number to identify the waste stream that will be described below. 01 

(Start with ID# 01 for first waste stream. Make copies of a blank Off-Site Recycling/Disposal form and use 02 for second, 

etc.)

2) What was the quantity of this waste stream in 2008? 

Indicate whether this quantity is reported in pounds or gallons. Keep waste disposal company manifests as proof that this

amount of waste was taken off-site.

3) What was the average pollutant content of the waste stream? NOTE: Report in the same units (pounds or gallons) as used 

in line 2.

VOC 4.25 lbs/unit HAP&NON lbs/ unit NHx lbs/ unit

NOTE: Waste normally has less pollutant content than the new product. Some of the 

pollutant evaporates during the use of the product, and there is usually dirt, water or 

other contaminants in the waste stream. The estimated pollutant content of the waste is 

usually between 50% and 95% of the new product. This example estimates an average VOC 

content (on line 3) to be 75% of the original VOC content of 5.67 lbs/gal., to account 

for evaporation and contaminants. See page 20 to calculate a weighted average.

4) Calculate the total annual pollutant content of the waste in this waste stream.

(volume of waste, from Line 2) × (pollutant content, from Line 3) = Total pollutants in waste stream, in lbs/yr.

VOC 10,200 lbs/yr HAP&NON lbs/yr NHx lbs/yr

5) List the process ID numbers of the processes contributing to this waste stream. Also estimate the pounds of pollutant 

that each process contributed to this waste stream. 

NOTE: In this example, the amount each process material contributed to total pollutants 

in the waste stream (Line 4) is based on the percentage, by weight, of each material 

that contributed to the waste stream (e.g., Process ID #6 contributed 5.6%, therefore 

5.6% × 10,200 lbs/yr = 569 lbs. See example on page 20).

NOTE: Column totals in the table below must equal the total for each pollutant type reported on line 4. The quantities 

you report below for each pollutant and process must also be reported in column 12 on the Evaporative Process Form.

 Process ID Annual VOC (lbs)

Annual

HAP&NON (lbs) Annual NHx (lbs)

 6 Contributed about 569 lbs lbs lbs

 7 Contributed about 1,884 lbs lbs lbs

 8 Contributed about 1,006 lbs lbs lbs

 9 Contributed about 6,741 lbs lbs lbs

Check one:

pounds

2,400 gallons
Maricopa County Emissions Inventory Unit 20 Instructions for Reporting 2008 Emissions 

EXAMPLE: Documentation of Emission Factor Calculations

Identify the process ID number(s) and pollutant(s). Show calculations made to obtain the emission factors used 

for the process(es). Include references to data sources used, including the document name, date published, page 

numbers, etc.

Emission Factor Calculation

Process ID 201 Permit number V99999 

Emission factors derived from source test performed 12/2/00 by XYZ Engineering 

Company (copy of summary tables also attached).

Outlet (after controls):

CO = 0.43 lb/hr × 1 hr/60 min × 1 min/77.9 cu. ft × 1,000,000 cu. ft/MMCF

= 92.0 lb/MMCF

NOx = 0.09 lb/hr × 1 hr/60 min × 1 min/77.9 cu. ft × 1,000,000 cu. ft/MMCF

= 19.3 lb/MMCF

Weighted average sample calculation

NOTE: The example below shows how the weighted average of the materials going into the 

waste stream is calculated. A weighted-average emission factor has been calculated 

by listing usage amounts and emission factors for each material, summing each 

column, and then dividing the total emissions by the total gallons used.

 In this example: 23,231 lbs ÷ 4,096 gal = 5.67 lb/gal average VOC content. This 

emission factor is then used to calculate the average pollutant content in the Offsite Recycling / Disposal Form example.

 This process can also be used to find the weighted average emission factor for 

similar materials if you are reporting them together as a single line item on the 

Evaporative Process form. Refer to the explanation of “grouping” on page 6.

Process 

ID # Material Type

2008

Usage Units

VOC

(lbs/unit)

VOC Emissions

(= Usage × VOC 

content)

Percent contributed 

to waste stream

6 gun cleaner 180 gal 7.2 1,296 lbs. 5.6 %

7 xyz stripper 1,300 gal 3.3 4,290 lbs. 18.5 %

8 cleaning solvent 358 gal 6.4 2,291 lbs. 9.9 %

9 MEGASOLVE 2,258 gal 6.8 15,354 lbs. 66.1 %

Totals: 

4,096

gal 23,231 lbs. 100.0 %

Average

VOC content:

23,231 lbs.

4,096 gals = 5.67lb/gal
Maricopa County Emissions Inventory Unit 21 Instructions for Reporting 2008 Emissions 

EXAMPLE (for all sources except Title V sources)

Data Certification Form 2008 Permit number 999999

For EACH pollutant listed, total up all emissions recorded on your General Process and Evaporative Process Forms. Enter these 

numbers in column 1, “Totals from Process Forms.” Report any emissions from accidental releases in column 2.

Add the figures in each row across, and enter the result in column 3, “Total Emissions”.

NOTE: “Accidental Releases” reported in column 2 should include all excess emissions 

reported to the Department under Rule 140, Section 500. 

Summary of 2008 Annual Emissions:

(1)

Totals from

Process Forms

(2)

+ Accidental

Releases

(3)

= TOTAL

2008 Emissions

CO 2,113 0 2,113

NHx 0 0 0

Lead 0 0 0

HAP&NON 0 0 0

VOC 24,220 0 24,220

NOx 9,815 0 9,815

SOx 645 0 645

PM10 7,891 0 7,891

NOTE: Review specific requirements for data confidentiality on page 5. We cannot hold 

any data confidential without the required documentation.

TO COMPLETE YOUR EMISSIONS INVENTORY REPORT:

- Complete the Confidentiality Statement below.

- Sign and date this form below where indicated.

- Send the original copy of your completed forms to: Maricopa County Air Quality Department, One Stop Shop, 

Emissions Inventory Intake, 501 N. 44th Street, Suite 200, Phoenix, AZ 85008-6538. Keep a copy of all forms for your records.

CONFIDENTIALITY STATEMENT:

This annual emissions report contains requests to keep some data confidential. YES NO

If you check “YES”, you must submit documentation and meet certain requirements before your data can be deemed confidential.

See enclosed instructions for further details.

NOTE: The Data Certification form must be signed by a responsible company official.

CERTIFICATION STATEMENT:

I declare under penalty of perjury that the data (e.g. inputs, emission factors, controls, and annual emissions) presented herein 

represents the best available information and is true, accurate and complete to the best of my knowledge.

___________________________________________________________________________________________________________

Signature of owner/business officer Date of signature Telephone number

___________________________________________________________________________________________________________

Type or print full name of owner/business officer Type or print full title
Maricopa County Emissions Inventory Unit 22 Instructions for Reporting 2008 Emissions 

How to calculate an emission fee (for Title V sources only):

1. For each pollutant listed on the “Data Certification/Fee Calculation” form, total up all emissions 

recorded on your General Process and Evaporative Process Forms. Enter these numbers in column 1, 

“Totals from Process Forms.” 

NOTE: While most processes that generate PM10 should be reported on line 5 of the Data Certification/Fee 

Calculation form, “[f]ugitive emissions of PM10 from activities other than crushing, belt transfers, screening, 

or stacking” (County Rule 280, § 305.2d) are NOT subject to annual emission fees. The most common 

occurrences of these PM10-producing activities that are NON-billable are listed below:

SCC codes and description of PM10-producing processes that are NOT subject to emission fees

SCC Major Category Subcategory Facility / Process Type Process Description

30200814 Industrial Processes Food and Agriculture Feed Manufacture Storage

30400737 Industrial Processes Secondary Metal Production Steel Foundries Raw Material Silo

30500120 Industrial Processes Mineral Products Asphalt Roofing Manufacture Storage Bins: Ferric Chloride

30500121 Industrial Processes Mineral Products Asphalt Roofing Manufacture Storage Bins: Mineral Stabilizer

30500134 Industrial Processes Mineral Products Asphalt Roofing Manufacture Blown Saturant Storage

30500135 Industrial Processes Mineral Products Asphalt Roofing Manufacture Blown Coating Storage

30500141 Industrial Processes Mineral Products Asphalt Roofing Manufacture Granules Storage

30500143 Industrial Processes Mineral Products Asphalt Roofing Manufacture Mineral Dust Storage

30500203 Industrial Processes Mineral Products Asphalt Concrete Storage Piles

30500212 Industrial Processes Mineral Products Asphalt Concrete Heated Asphalt Storage Tanks

30500213 Industrial Processes Mineral Products Asphalt Concrete Storage Silo

30500290 Industrial Processes Mineral Products Asphalt Concrete Haul Roads: General

30500303 Industrial Processes Mineral Products Brick Manufacture Storage of Raw Materials

30500608 Industrial Processes Mineral Products Cement Manufacturing (Dry Process) Raw Material Piles

30500708 Industrial Processes Mineral Products Cement Manufacturing (Wet Process) Raw Material Piles

30501710 Industrial Processes Mineral Products Mineral Wool Storage of Oils and Binders

30502007 Industrial Processes Mineral Products Stone Quarrying - Processing Open Storage

30502011 Industrial Processes Mineral Products Stone Quarrying - Processing Hauling

30502504 Industrial Processes Mineral Products Construction Sand and Gravel Hauling

30502507 Industrial Processes Mineral Products Construction Sand and Gravel Storage Piles

30502760 Industrial Processes Mineral Products Industrial Sand and Gravel Sand Handling, Transfer, & Storage

30531090 Industrial Processes Mineral Products Coal Mining, Cleaning, Material Handling Haul Roads: General

30532007 Industrial Processes Mineral Products Stone Quarrying - Processing Open Storage

30704002 Industrial Processes Pulp and Paper & Wood Pdts. Bulk Handling and Storage - Wood/Bark Stockpiles

31100199 Industrial Processes Building Construction Construction: Building Contractors Other Not Classified

31100299 Industrial Processes Building Construction Demolitions/Special Trade Contracts Other Construction/Demolition

50100401 Waste Disposal Solid Waste Disposal Landfill Dump Unpaved Road Traffic

50100402 Waste Disposal Solid Waste Disposal Landfill Dump Fugitive Emissions

50100403 Waste Disposal Solid Waste Disposal Landfill Dump Area Method

50100404 Waste Disposal Solid Waste Disposal Landfill Dump Trench Method

50100405 Waste Disposal Solid Waste Disposal Landfill Dump Ramp Method

2. Report any accidental releases in column 2. Add columns 1 and 2 together for each pollutant, and enter 

the sum in column 3. Sum lines 1 through 5 together, and enter the total on line 6. 

3. Divide your facility's total billable emissions (on line 6) by 2000 to convert pounds into tons. Round to 

the nearest ton. Enter this value on line 7. Multiply this number by $38.25, and enter the result on line 

8. This is your 2008 emission fee. 
Maricopa County Emissions Inventory Unit 23 Instructions for Reporting 2008 Emissions 

EXAMPLE (for Title V sources only)

Data Certification/Fee Calculation Form 2008 Permit number V99999

For EACH pollutant listed, total up all emissions recorded on your General Process and Evaporative Process Forms. Enter these 

numbers in column 1, “Totals from Process Forms.” Report any emissions from accidental releases in column 2.

Add the figures in each row across, and enter the result in column 3, “Total Emissions”.

Carefully follow the instructions on lines 6 through 8 to calculate any emission fee owed.

NOTE: “Accidental Releases” reported in column 2 should include all excess emissions 

reported to the Department under Rule 140, Section 500. 

NOTE: Review specific requirements for data confidentiality on page 5. We cannot hold 

any data confidential without the required documentation.

TO COMPLETE YOUR EMISSIONS INVENTORY REPORT:

- Include a check (made payable to Maricopa County Air Quality Department) for the amount calculated on line 8 above.

- Complete the Confidentiality Statement below.

- Sign and date this form below where indicated.

- Send the original copy of your completed forms, along with any emission fee due to: Maricopa County Air Quality Department, 

One Stop Shop, Emissions Inventory Intake, 501 N. 44th Street, Suite 200, Phoenix, AZ 85008-6538. Keep a copy of all forms 

for your records.

CONFIDENTIALITY STATEMENT:

This annual emissions report contains requests to keep some data confidential. YES NO

If you check “YES”, you must submit documentation and meet certain requirements before your data can be deemed confidential.

See enclosed instructions for further details.

NOTE: The Data Certification form must be signed by a responsible company official.

CERTIFICATION STATEMENT:

I declare under penalty of perjury that the data (e.g. inputs, emission factors, controls, and annual emissions) presented herein 

represents the best available information and is true, accurate and complete to the best of my knowledge.

___________________________________________________________________________________________________________

Signature of owner/business officer Date of signature Telephone number

___________________________________________________________________________________________________________

Type or print full name of owner/business officer Type or print full title

Summary of 2008 Annual Emissions:

(1)

Totals from

Process Forms

(2)

+ Accidental

Releases

(3)

= TOTAL

2008 Emissions

CO 2,113 0 2,113

NHx 0 0 0

Lead 0 0 0

PM10 (non-billable; see page 22) 7,200 0 7,200

Emissions fees are based on your emissions of the following pollutants ONLY:

1 HAP&NON 0 0 0

2 VOC 24,220 0 24,220

3 NOx 9,815 0 9,815

4 SOx 645 0 645

5 PM10 (billable; see page 22) 691 0 691

6 Add “TOTAL” column from lines 1 through 5 ONLY: 35,371 lbs.

7 Divide the total on line 6 by 2000 (pounds per ton) to get tons, and round the number to the 

nearest ton. (Drop any decimal of .499 or less. Increase to the next whole number any 

decimal of .500 or more.) Enter the resulting WHOLE NUMBER here. 18 TONS

8

Multiply line 7 (a WHOLE number) by $ 38.25.

This is your 2008 ANNUAL EMISSION FEE. $ 688.50
2008 Maricopa Co. PM10 Emission Inventory A3–1 June 2011

Appendix 3. Rule Effectiveness (RE) Studies

3.1 Introduction

Rule effectiveness (RE) studies are designed to assess the success of regulatory rules at controlling their targeted emissions. It is acknowledged that facilities and source categories subject to 

control techniques and devices mandated by rules do not always achieve 100% compliance with 

those requirements. Given this reality, the US EPA recommends the use of rule effectiveness 

studies to improve the quality of emission estimates presented in emission inventories.

Once an RE rate has been calculated, its value is applied to relevant sources at an individual 

process level, thus adjusting (i.e., increasing) emission estimates to reflect a lower degree of 

control efficiency. The formulas below illustrate how inclusion of rule effectiveness can 

significantly affect the resulting emission estimates:

Emissions before the application of rule effectiveness:

Uncontrolled Emissions × [1 – (Control Efficiency)] = Emissions with Control

100 tons × [ 1 – (0.90) ] = 10.0 tons

Emissions including the application of rule effectiveness:

Uncontrolled Emissions × [1 – (Control Efficiency × RE)] = Emissions with Control

100 tons × [ 1 – (0.90 × 0.83) ] = 25.3 tons

In general, the RE rate is applied to all processes where a control device or control technique is 

in use. There are however some limitations to this blanket rule, as expressed in US EPA’s most 

recent guidance:

...not all emission estimates involving use of a control device or technique need to 

be adjusted to account for RE...For example, a state or local agency may conclude that a control device that operates in conjunction with a continuous emissions monitor, or is equipped with an automatic shutdown device, may provide a 

sufficient level of assurance that intended emission reductions will be achieved, 

and therefore an adjustment for rule effectiveness is not necessary. Another 

example would be in instances where a direct determination of emissions, such as 

via a mass balance calculation, can be made. (US EPA, 2005)

Another complication in any attempt to apply a blanket RE percentage rate occurs where control 

device efficiencies are extremely high. Some categories of control devices routinely operate at 

efficiencies of 99% or greater (e.g., baghouses, thermal oxidizers). For these activities, even 

small adjustments through the application of RE can cause a dramatic increase in reported 

emissions. As an example, a process with a control device of 99.9% efficiency may report 

controlled emissions of 10 tons. If an RE rate of 85% were applied to this process, the adjusted 

emissions would total 1,508.5 tons (an increase of nearly 15,000%). In these types of instances, 

the department evaluated the affected processes on a case-by-case basis to determine the 

appropriateness of applying an RE adjustment.
2008 Maricopa Co. PM10 Emission Inventory A3–2 June 2011

3.2 Calculating Rule Effectiveness Rates for Rules 310, 310.01, and 316

Rule effectiveness studies adjust the emissions from subject facilities and source categories to 

account for times of non-compliance and control device equipment failure. Of particular importance to the Maricopa County Air Quality Department (MCAQD) are those rules that control 

particulate matter release, since parts of the county have been designated as nonattainment areas 

in regard to US EPA PM10 standards. Consequently, the rule effectiveness studies presented here 

deal with the control of criteria pollutant PM10.

Source-specific rule effectiveness studies were undertaken as part of this project to adjust the 

emissions from subject facilities and source categories to account for times of non-compliance 

and control device equipment failure by incorporating applicable compliance history data to 

ascribe a percentage rate (RE rate) at which the subject rule(s) attains the intended emissions 

reductions. These source-specific studies use data from inspections conducted from July 2008 

through June 2009 to determine the rate of compliance of subject facilities and source categories 

with Rule 310 (Fugitive Dust from Dust-Generating Operations), Rule 310.01 (Fugitive Dust 

from Non-Traditional Sources of Fugitive Dust), and Rule 316 (Nonmetallic Mineral Processing)

with final RE rates listed in Table A3–1 below. Rule effectiveness rates were calculated separately for agricultural activities (best management practices), Title V, and non-Title V permitted 

facilities, which are each described in detail in Section 3.3.

Table A3–1. Rule effectiveness rates, listed by rule analyzed.

Rule Rule Effectiveness (RE) Rate

Rule 310 89.94%

Rule 310.01 95.21%

Rule 316 65.44%

The resulting RE rates shown above have been applied to relevant point and area source inventory categories and are reflected in the emission estimates presented in applicable sections of 

Chapters 2 and 3.

The US EPA has provided a number of guidance documents that detail the use and formulation 

of rule effectiveness studies (US EPA, 2005; 1994; 1992). The most recent of these documents 

states, “First and foremost, an agency responsible for emissions inventory preparation should 

attempt to obtain facility specific data from as many sources as possible, and use the collected 

information to make a refined source or source category RE determination” (US EPA, 2005). 

Given this directive, MCAQD developed a rule effectiveness study methodology that utilizes all 

available compliance data to produce a RE rate that best reflects the field effectiveness of the 

rule. By using the entire population of data for the prescribed time period, (July 2008 – June 

2009) the statistical validity of the RE rate greatly improves. This approach differs from previous rule effectiveness studies conducted by the department that were based upon a small sample 

pool of targeted inspections (MCAQD, 2007).

The source-specific RE rates presented here are developed from statistical examination of 

recorded inspection data. This is the rate at which inspection staff is observing facility and 

source category compliance in the field. While this provides the most direct measure of rule 

effectiveness, it can still be an incomplete picture of overall rule effectiveness. In the case of the 

source-specific studies for those sources directly affected by a county air quality rule (Rules 310, 

310.01, and 316) the compliance rate is used as the RE rate. These sources tend to have a 

focused, homogeneous set of processes. This, combined with the fact that these studies not only 
2008 Maricopa Co. PM10 Emission Inventory A3–3 June 2011

contain the entire population of affected sources but are also very large sample sizes, gives 

confidence that inconsistencies of individual inspections are already addressed in practice. To 

further focus the study of these sources each unique permit was classified as “in violation” if any 

inspection during the allotted time period resulted in an emission based violation or as “in compliance” if no violations were issued or an administrative based violation was issued.

A total of six distinct rule effectiveness rates were calculated for use in this emissions inventory: 

four source-specific rule effectiveness determinations (Rule 310, Rule 310.01, Rule 316 and 

agricultural activities) along with two multi-rule determinations (Title V and non-Title V permitted facilities). The following three sections describe in further detail the data and methods 

used in the development of the Rule 310, Rule 310.01, and Rule 316 RE factors. 

3.2.1 Calculating Rule Effectiveness for Sources Subject to Rule 310

Sources subject to the department Rule 310 (Fugitive Dust from Dust-Generating Operations) are 

most often those construction sites where the disturbance of earth is occurring. The RE rate for 

Rule 310 sources is developed from the observed compliance rate of permitted sites.

The compliance rate for Rule 310 sources uses inspection data of issued dust permits between 

July 2008 and June 2009. Only inspections that result in a finding of compliance or noncompliance (i.e., “in violation”) are considered in the compliance rate. Inspections conducted 

solely to confirm the closing of a permit, or inspections where a compliance determination could 

not be made, were not included in the development of the compliance rate. Using these criteria, 

a total of 12,325 inspections were conducted on 5,467 issued permits, out of a possible pool of 

7,918 issued permits. Dust Control Permits are only valid for 12 months, and expire on the 

anniversary of their issue date; for instance a permit issued on July 22, 2007 would have a July 

22, 2008 expiration date. This permit would therefore only have “operated” 22 days in the 

inspection period on which this compliance data is based. Some issued permits also experience 

limited operations, perhaps only a month or two, but in most cases these permits are left open by 

the permit holder for the entire 12 months. Given these realities, it is not unexpected that 2,451

out of the pool of 7,918 permits received no compliance determination inspection during the 12-

month period of July 2008–June 2009. Conversely, over 59% of all issued permits that received 

a compliance determination inspection were inspected two or more times, with some sites receiving as many as 13 inspections during the 12-month time period of this study.

Of the inspected sources listed above, individual compliance rates are determined on a permit by 

permit basis. Any permit that received at least one emissions-related violation during any 

inspection conducted between July 2008 and June 2009 received a compliance rate of 0%. 

Permitted sites that had no recorded emissions-related violations during the study period received 

a compliance rate of 100%. Of the permits with violations noted, 550 (80%) were emissionsrelated (track-out, visible emissions, recordkeeping, silt content, etc.), with the remaining 137

(20%) violating permits being procedural (inadequate dust control plan, late fees, etc.). The 

permit-specific compliance rates were summed and averaged to produce an overall grouped 

compliance rate of 89.94%.
2008 Maricopa Co. PM10 Emission Inventory A3–4 June 2011

3.2.2 Calculating Rule Effectiveness for Sources Subject to Rule 310.01

The majority of sources subject to Rule 310.01 (Fugitive Dust from Non-Traditional Sources of 

Fugitive Dust) are vacant lots. It is estimated that there are presently more than 100,000 vacant 

lots in Maricopa County. Rule 310.01 sources generally do not require a permit, unlike Rule 310 

and Rule 316 sources. The RE rate for Rule 310.01 sources is calculated based upon vacant lot 

inspection compliance rates.

During the study period (July 2008 – June 2009), the department inspectors performed a total of 

12,370 inspections of vacant lots in Maricopa County. The primary purpose of a Rule 310.01 

inspection is to verify whether or not the vacant lot in question has a stabilized surface. If the 

surface is determined to be stable (through a variety of tests), the lot is deemed to be in compliance. Conversely, if the lot’s surface is deemed to be unstable, then a violation of Rule 310.01 

has occurred. As with Rule 310, a compliance rate is determined individually for each vacant 

lot, and then summed and averaged to produce a group compliance rate. The overall compliance 

rate for Rule 310.01 sites is 95.21%. All 592 violations noted by inspectors were emissionsrelated violations, as all the violations are for unstable soil conditions.

3.2.3 Calculating Rule Effectiveness for Sources Subject to Rule 316

Facilities subject to Rule 316 (Nonmetallic Mineral Processing) include those involved in the 

mining of sand and gravel and the production of concrete products. All such “Rule 316 sites” are 

required to have either a Title V or non-Title V permit issued by the department. At present, all 

facilities that are subject to Rule 316 have only non-Title V permits. (One class of sources that 

has long been an exception to this is portable sources that may operate in more than one county 

during the life of the permit; thus these sources are issued permits by the Arizona Department of 

Environmental Quality.) The RE rate for Rule 316 sites was determined in a similar fashion as 

for Rules 310 and 310.01; i.e., calculated on the basis of the actual observed compliance rates of 

permitted sites.

Inspection data for the period July 2008 through June 2009 reveal that inspections were conducted for 136 issued permits for Rule 316 facilities. All of these facilities were inspected at 

least once during this study period, with a compliance determination made for each facility. 

Overall, 525 inspections that resulted in a compliance determination were performed during the 

study period. As with Rules 310 and 310.01, a compliance rate is computed for each facility,

and then summed and averaged for the group, resulting in an overall compliance rate of 65.44%. 

Of the violating permits noted, 47 (54%) were emissions-related, with the remaining 40 (46%)

primarily procedural in nature.

3.3 Calculating Rule Effectiveness Rates for Agricultural Activities, Title V Facilities, and 

Non-Title V Facilities

The observed compliance rate in some cases, such as multi-source Title V and non-Title V 

facilities, can be better described as a rate at which inspection staff issue violations. Inspection 

staff has a range of experience and training which influences their proficiency in issuing appropriate violations. There may be instances when a rule violation goes unnoticed by staff, or 
2008 Maricopa Co. PM10 Emission Inventory A3–5 June 2011

conversely a violation may be issued in error. Even when a compliance rate has a high statistical 

measure of accuracy, it can fail to reflect a number of programmatic measures that affect overall 

rule effectiveness; measures like the strength of rule language, departmental enforcement and 

penalty actions, inspector training programs, educational and public outreach efforts, etc. This 

reality is reflected in earlier US EPA guidance:

A percentage effectiveness rating is not enough to describe the compliance effectiveness of a rule for a source category. An SSCD [Stationary Source Compliance 

Division] study should attempt to link the rating to a regulatory agency’s overall 

effort. The study should address the factors that affect the percentage effectiveness rating such as the compliance rate of the sources in a category, inspection 

frequency and thoroughness, the language of the rule (i.e., whether or not it has 

loopholes), and the reporting and recordkeeping by the regulatory agency. 

Evaluating these factors will provide a more complete evaluation of the effectiveness of a rule. (US EPA, 1994)

In order to incorporate all the salient factors described above, a matrix was created to produce a 

final RE rate. US EPA’s latest guidance (2005) provides a listing of factors that can impact rule 

effectiveness rates (e.g., inspector training, frequency of inspections, media outreach, enforcement policies, recordkeeping requirements, etc.), grouped into major categories such as most 

important factors, important factors and other factors. The department used these suggested 

factors as the basis for developing the RE matrices contained in Tables A3–3 through A3–5.

In brief, the compliance rate developed from inspection data accounts for 70% of the overall RE 

rate, while all other factors account for the remaining 30%. (An exception to these values 

applies in the case of agricultural activities.) Each factor is scored individually, based upon the 

department’s success in implementing that factor. As an example, the score for the factor 

“Compliance History” is the compliance rate developed from the study period inspection data, 

while the score for “Enforcement Penalties” is based upon the department’s timely response to, 

and settlement of, observed violations associated with the subject rule or source category. The 

complete matrices for each applicable rule or source category for which rule effectiveness was 

addressed, are contained in Tables A3–3 through A3–5.

The following sections describe in further detail the data and methods used in the development 

of the remaining RE factors for agricultural activities, Title V, and non-Title V permitted 

facilities; results are summarized in Table A3–2 below. 

Table A3–2. Compliance and rule effectiveness rates, by source category analyzed.

Source Category Compliance Rate Rule Effectiveness (RE) Rate

Agricultural Activities Unknown 55.33%

Title V Facilities 89.14% * 90.94%

Non-Title V Facilities 81.00% * 84.27%

* Compliance rates for both Title V and Non-Title V facilities are based upon 2008-2009 inspection data, and 

reflect compliance self-monitoring recordkeeping practice, in addition to violation data.
2008 Maricopa Co. PM10 Emission Inventory A3–6 June 2011

3.3.1 Calculating Rule Effectiveness for Agricultural Activities

Agricultural activities in most parts of Maricopa County are subject to the Best Management 

Practices program administered by the Arizona Department of Environmental Quality (ADEQ). 

This program is largely a self-monitoring program, in which participants indicate which management practices were chosen to be used during various operations (e.g., harvesting, tilling). No 

compliance rate estimates for this program were noted during the study period. ADEQ does 

indicate that after a site has been visited, 100% of the sources return to compliance. Since compliance with this program is verified only on a complaint-driven basis, the weight given to compliance history was lowered, from 70% to 25%, in the matrix shown in Table A3–3, indicating 

an overall RE rate of 55.30% for agricultural activities. 

3.3.2 Calculating Rule Effectiveness for Title V and Non-Title V Processes

For the remaining emission processes (not regulated by Rules 310, 310.01 and/or 316) that

include a control device or technique that limits particulate matter or ozone formation, separate 

multi-rule RE rates have been calculated for permitted Title V and non-Title V facilities. Factorbased matrices have been utilized to develop RE rates for Title V and non-Title V facilities. 

Compliance rates for these sources are based upon two full years of data (2008 through 2009), as 

compliance information for these sources tends to be more detailed (as reflected in the matrix). 

The compliance rate for these facilities also includes data on self-monitoring recordkeeping 

practices in addition to inspection data. The combination of monitoring data and inspection data 

comprise the ‘compliance rate’ section of the RE calculation matrix, and still account for 70% of 

the overall RE rate. The combined compliance rate for Title V facilities is 89.14% and 81.00% 

for non-Title V facilities, resulting in RE rates of 90.94% and 84.27% for Title V and non-Title 

V facilities, respectively, as shown in Tables A3–4 and A3–5 below.

3.4 References

MCAQD, 2007. 2005 Periodic Emissions Inventory for PM10 for the Maricopa County, Arizona, 

Nonattainment Area.

US EPA, 1992. Guidelines for Estimating and Applying Rule Effectiveness for Ozone/CO State 

Implementation Plan Base Year Inventories. EPA Rep. 452/R-92-010, November 1992.

US EPA, 1994. Rule Effectiveness Guidance: Integration of Inventory, Compliance and 

Assessment Applications. EPA Rep. 452/R-94-001, January 1994.

US EPA, 2005. Emissions Inventory Guidance for Implementation of Ozone and Particulate 

Matter National Ambient Air Quality Standards (NAAQS) and Regional Haze Regulations. 

EPA Rep. 454/R-05-001, November 2005.
2008 Maricopa Co. PM10 Emission Inventory A3–7 June 2011

Table A3–3. Rule Effectiveness Matrix for Agricultural Activities

A. Most important factor (1 criterion, assigned weighting of 25% of total):

Factor Range

Midpt. 

value Description Weight

Value 

assigned to 

MCAQD

Score

(= weight × 

value)

Compliance 

History

86% 100% 93%

Over 90% of facilities inspected in the source 

category are in compliance 25% 93% 23.25%

70% 85% 78%

Over 75% of facilities inspected in the source 

category are in compliance

< 70% 35%

Over 60% of facilities inspected in the source 

category are in compliance

Type of 

Inspection

86% 100% 93%

Inspections are thorough and detailed, and include 

close examination of control equipment, and a 

detailed records review

70% 85% 78%

Inspections consist of a records review, and 

sometimes inspection of control equipment;

< 70% 35%

Inspections generally consist of a records review 

only; 10% 35% 3.5%

B. Other important factors (6 criteria, each assigned weighting of 10% of total):

Compliance 

Certifications

86% 100% 93%

Source is subject to some type of compliance 

certification;

70% 85% 78%

Source is subject to some type of compliance 

certification;

< 70% 35%

Source is not subject to any type of compliance 

certification; 10% 35% 3.5%

Inspection 

Frequency/ 

Percentage

86% 100% 93%

Percent of facilities inspected in the sector in a 

given year is 25% or greater;

70% 85% 78%

Percent of facilities inspected in the sector in a 

given year is 15% or greater;

< 70% 35%

Percent of facilities inspected in the sector in a 

given year is less than 15% 10% 35% 3.5%

Unannounced 

Inspections 

86% 100% 93% Unannounced inspections are sometimes done;

70% 85% 78%

Unannounced inspections are done, but 

infrequently;

< 70% 35% Unannounced inspections are never done; 10% 35% 3.5%

Enforcement 

Penalties

86% 100% 93%

Agency takes prompt enforcement action, 

including monetary fines, against violators;

70% 85% 78%

Agency usually takes enforcement action, 

including monetary fines, against violators;

< 70% 35%

Agency usually does not take enforcement action

against violators; 10% 35% 3.5%

Compliance 

Assistance

86% 100% 93%

A compliance assistance program exists and is 

adequately staffed, and includes such things as 

workshops, mailings, web-based tutorials, etc. 10% 93% 9.3%

70% 85% 78%

A compliance assistance program exists and is 

minimally staffed. The program occasionally 

makes workshops, mailings, web-based tutorials, 

etc., available.

< 70% 35% A compliance assistance program does not exist
2008 Maricopa Co. PM10 Emission Inventory A3–8 June 2011

C. Other factors (3 criteria, each assigned weighting of 5% of total):

Factor Range

Midpt. 

value Description Weight

Value 

assigned to 

MCAQD

Score

(= weight × 

value)

Monitoring 

Requirements

86% 100% 93%

Monitoring requirements exist and must be 

reported to regulatory agency at least once a year;

70% 85% 78%

Monitoring requirements exist but records don’t 

have to be filed with regulatory agency;

< 70% 35% Monitoring requirements do not exist; 5% 35% 1.75%

Follow-up 

Inspections

86% 100% 93%

Follow-up inspections are done when violations 

are noted most (>75%) of the time;

70% 85% 78%

Follow-up inspections are done when violations 

are noted some of the time;

< 70% 35% Follow-up inspections are not routinely done; 5% 35% 1.75%

Media 

Publicity

86% 100% 93%

Media publicity of enforcement actions is routinely 

conducted.

70% 85% 78%

Media publicity of enforcement actions is 

sometimes done.

< 70% 35%

Media publicity of enforcement actions is rarely 

done. 5% 35% 1.75%

Overall rule effectiveness score for agricultural activities: 55.30%
2008 Maricopa Co. PM10 Emission Inventory A3–9 June 2011

Table A3–4. Rule Effectiveness Matrix for Title V Facilities

A. Most important factors (2 criteria, each assigned weighting of 35% of total):

Factor Range

Midpt. 

value Description Weight

Value 

assigned to 

MCAQD

Score

(= weight × 

value)

Monitoring

94% 100% 97%

Source specific monitoring used for compliance 

purposes, and monitoring records filed with 

regulatory agency at least every 4 months.

87% 93% 90%

Source specific monitoring used as an indicator of 

compliance, and monitoring records filed with 

regulatory agency every 6 to 9 months. 35% 90% 31.5%

81% 86% 84%

Source specific monitoring used as an indicator of 

compliance, and monitoring records filed with 

regulatory agency each year.

70% 80% 75%

General guidance exists for source specific 

enhanced monitoring, and monitoring records 

required but aren’t submitted to regulatory agency.

< 70% 35% No requirements for any type of monitoring.

Compliance 

History

94% 100% 97%

The facility has been in compliance for the past 

eight quarters.

35%

10 of 19 

facilities 17.9%

87% 93% 90%

The facility is believed to have been in compliance 

for the past eight quarters, although inspection 

frequency is such that this can’t be positively 

confirmed.

81% 86% 84%

On schedule; the facility is meeting its compliance 

schedule.

70% 80% 75%

In Violation; facility is in violation of emissions 

and/or procedural requirements.

8 of 19 

facilities 12.4%

< 70% 35%

High Priority Violator (HPV): the facility is in 

significant violation of one or more applicable 

requirement of the CAA.

1 of 19 

facilities 0.6%

Sum: 30.9%

B. Other important factors (4 criteria, each assigned weighting of 3% of total):

Type of 

Inspection

94% 100% 97%

Inspections involve compliance test methods with 

a high degree of accuracy, such as stack testing or 

other types of precise emissions measurement. 3% 97% 2.9%

87% 93% 90%

Inspections involve detailed review of process 

parameters & inspection of control equipment.

81% 86% 84%

Inspections involve review of process and 

inspection of control equipment.

70% 80% 75%

Inspections generally consist of only a records 

review.

< 70% 35%

Inspections most likely consist of visual inspection 

(e.g., opacity), or drive by.

Operation & 

Maintenance

94% 100% 97%

Control equipment operators follow and sign daily 

O&M instructions. 

87% 93% 90%

Control equipment operators follow daily O&M 

instructions. 3% 90% 2.7%

81% 86% 84%

Control equipment operators follow daily or 

weekly O&M instructions.

70% 80% 75%

O&M requirements exist, but on no specific 

schedule.

< 70% 35% No specific O&M requirements.
2008 Maricopa Co. PM10 Emission Inventory A3–10 June 2011

Factor Range

Midpt. 

value Description Weight

Value 

assigned to 

MCAQD

Score

(= weight × 

value)

Unannounced 

Inspections 

94% 100% 97% Routinely conducted. 3% 97% 2.9%

87% 93% 90% Sometimes done.

81% 86% 84% Done, but infrequently.

70% 80% 75% Rarely done.

< 70% 35% Never done.

Enforcement 

Penalties

94% 100% 97%

Agency has the authority to impose punitive 

measures, including monetary fines, towards 

violators such as in delegated Title V Operating 

Permit programs. 3% 97% 2.91%

87% 93% 90%

Agency has the authority to impose punitive 

measures, including monetary fines, towards 

violators such as in delegated Title V Operating 

Permit programs.

81% 86% 84%

Agency has the authority to impose punitive 

measures, including monetary fines, towards 

violators such as in delegated Title V Operating 

Permit programs.

70% 80% 75%

Agency has the authority to impose punitive 

measures, including monetary fines, towards 

violators such as in delegated Title V Operating 

Permit programs.

< 70% 35%

Agency does not have sufficient authority to 

impose punitive measures towards violators.

C. Other factors (9 criteria, each assigned weighting of 2% of total):

Compliance 

Certifications

94% 100% 97%

Source subject to Title V or other type of compliance certification. 2% 97% 1.94%

87% 93% 90%

Source subject to Title V or other type of compliance certification.

81% 86% 84%

Source not subject to any type of compliance certification.

70% 80% 75%

Source not subject to any type of compliance certification.

< 70% 35%

Source not subject to any type of compliance certification.

Inspection 

Frequency

94% 100% 97%

Source(s) are inspected once every 2 years or more 

frequently. 2% 97% 1.94%

87% 93% 90%

Source(s) are inspected once every 3 years or more 

frequently.

81% 86% 84%

Source(s) are inspected once every 5 years or more 

frequently.

70% 80% 75% Inspection of source(s) infrequent; > every 5 years.

< 70% 35% Inspections rarely, if ever, performed.

EPA HPV 

Enforcement

94% 100% 97%

Agency has sufficient resources to implement 

EPA’s 12/22/98 HPV policy. 2% 97% 1.94%

87% 93% 90%

Agency’s resources allow it to implement EPA’s 

12/22/98 HPV policy in most instances.

81% 86% 84%

Agency’s resources allow it to implement EPA’s 

12/22/98 HPV policy in most instances.

70% 80% 75%

Agency’s resources allow it to implement EPA’s 

12/22/98 HPV policy more often than not.

< 70% 35%

Resource constraints prohibit agency from 

implementing EPA’s 12/22/98 HPV policy in most 

instances.
2008 Maricopa Co. PM10 Emission Inventory A3–11 June 2011

Factor Range

Midpt. 

value Description Weight

Value 

assigned to 

MCAQD

Score

(= weight × 

value)

Operator 

Training

94% 100% 97%

Control equipment operators complete a formal 

training program on use of the equipment, and 

such program is kept up to date and has been 

reviewed by the regulatory agency.

87% 93% 90%

Control equipment operators complete formal 

training program, and such program is kept up to 

date and available for review by the regulatory 

agency upon request.

81% 86% 84%

Control equipment operators complete some

amount of formal training. 2% 84% 1.68%

70% 0.8 75%

Control equipment operators receive only on the 

job training.

< 70% 35%

Control equipment operators receive no specific 

training.

Media 

Publicity

94% 100% 97% Media publicity of enforcement actions. 2% 97% 1.94%

87% 93% 90% Media publicity of enforcement actions.

81% 86% 84% Media publicity of enforcement actions.

70% 80% 75% Media publicity of enforcement actions.

< 70% 35% No media publicity of enforcement actions.

Regulatory 

Workshops

94% 100% 97%

Regulatory workshops are available annually, 

and/or the implementing agency mails regulatory 

information packages each year. 2% 97% 1.94%

87% 93% 90%

Regulatory workshops are available every 1-2 

years, and/or the implementing agency mails 

regulatory information packages every 1-2 years.

81% 86% 84%

Regulatory workshops are available every 2-3 

years, and/or the implementing agency mails 

regulatory information packages once every 2-3 

years.

70% 80% 75%

Regulatory workshop not routinely available, but 

implementing agency mails regulatory information 

packages out about once every 2-3 years.

< 70% 35%

Regulatory workshops not routinely available. 

Implementing agency mails regulatory information 

packages infrequently, if ever.

Inspector 

Training

94% 100% 97%

Inspectors must undergo 2 weeks of 

comprehensive basic training, and 1 to 2 weeks of 

source specific training, and such training is 

updated each year.

87% 93% 90%

Inspectors must undergo 1 to 2 weeks of basic 

training and 1 week of source specific training and 

such training is updated every 1-2 years. 2% 90% 1.80%

81% 86% 84%

Inspectors must undergo 1 to 2 weeks of basic 

training and 3 to 5 days of source specific training, 

and such training is updated every 1-2 years.

70% 80% 75%

Inspectors must undergo 1 to 2 weeks of basic 

training and 1 to 3 days of source specific training, 

and such training is updated every 1-2 years. 

< 70% 35%

Inspectors must undergo less than 5 days of basic 

training less than 3 days of source specific 

training, and such training is updated only every 2 

years or less frequently.
2008 Maricopa Co. PM10 Emission Inventory A3–12 June 2011

Factor Range

Midpt. 

value Description Weight

Value 

assigned to 

MCAQD

Score

(= weight × 

value)

Testing 

Guidelines

94% 100% 97%

Specific guidelines and schedule for testing and 

test methods exist. 2% 97% 1.94%

87% 93% 90%

Specific guidelines on testing and test methods 

exist, but no schedule for testing.

81% 86% 84%

Specific guidelines on testing and test methods 

exist, but no schedule for testing.

70% 80% 75%

Specific guidelines on testing and test methods, 

but no schedule for testing.

< 70% 35%

Only general guidance on testing, or no mention of 

testing requirements.

Follow-up 

Inspections

94% 100% 97%

Follow-up inspections always or almost always 

conducted (90 % of the time or more). 2% 97% 1.94%

87% 93% 90%

Follow-up inspections usually conducted

(approximately 75% of the time).

81% 86% 84%

Follow-up inspections sometimes conducted

(approximately 50% of the time).

70% 80% 75%

Follow-up inspections infrequently conducted

(approximately 25% of the time).

< 70% 35%

Follow-up inspections rarely or never conducted

(10% of the time or less)

Overall rule effectiveness score for Title V facilities: 90.94%
2008 Maricopa Co. PM10 Emission Inventory A3–13 June 2011

Table A3–5. Rule Effectiveness Matrix for Non-Title V Facilities

A. Most important factors (2 criteria, each assigned weighting of 35% of total):

Factor Range

Midpt. 

value Description Weight

Value 

assigned to 

MCAQD

Score

(= weight 

× value)

Monitoring

94% 100% 97%

Source specific monitoring used for compliance 

purposes, and monitoring records filed with 

regulatory agency at least every 4 months.

87% 93% 90%

Source specific monitoring used as an indicator of 

compliance, and monitoring records filed with 

regulatory agency every 6 to 9 months.

81% 86% 84%

Source specific monitoring used as an indicator of 

compliance, and monitoring records filed with 

regulatory agency each year.

70% 80% 75%

General guidance exists for source specific 

enhanced monitoring, and monitoring records required but aren’t submitted to regulatory agency. 35% 75% 26.3%

< 70% 35% No requirements for any type of monitoring.

Compliance 

History

94% 100% 97%

The facility has been in compliance for the past 

eight quarters. 35% 156 of 298 facilities 17.8%

87% 93% 90%

The facility is believed to have been in compliance 

for the past eight quarters, although inspection 

frequency is such that this can’t be positively 

confirmed.

10 of 298 

facilities 1.1%

81% 86% 84%

On schedule; the facility is meeting its compliance 

schedule.

70% 80% 75%

In Violation; facility is in violation of emissions 

and/or procedural requirements.

130 of 298

facilities 11.5%

< 70% 35%

High Priority Violator (HPV): the facility is in 

significant violation of one or more applicable 

requirement of the CAA.

2 of 298 

facilities 0.1%

Sum: 30.4%

B. Other important factors (4 criteria, each assigned weighting of 3% of total):

Type of 

Inspection

94% 100% 97%

Inspections involve compliance test methods with 

a high degree of accuracy, such as stack testing or 

other types of precise emissions measurement.

87% 93% 90%

Inspections involve detailed review of process 

parameters & inspection of control equipment. 3% 90% 2.7%

81% 86% 84%

Inspections involve review of process and 

inspection of control equipment.

70% 80% 75%

Inspections generally consist of only a records 

review.

< 70% 35%

Inspections most likely consist of visual inspection 

(e.g., opacity), or drive by.

Operation & 

Maintenance

94% 100% 97%

Control equipment operators follow and sign daily 

O&M instructions. 

87% 93% 90%

Control equipment operators follow daily O&M 

instructions. 3% 90% 2.7%

81% 86% 84%

Control equipment operators follow daily or 

weekly O&M instructions.

70% 80% 75%

O&M requirements exist, but on no specific 

schedule.

< 70% 35% No specific O&M requirements.
2008 Maricopa Co. PM10 Emission Inventory A3–14 June 2011

Factor Range

Midpt. 

value Description Weight

Value 

assigned to 

MCAQD

Score

(= weight 

× value)

Unannounced 

Inspections 

94% 100% 97% Routinely conducted. 3% 97% 2.91%

87% 93% 90% Sometimes done.

81% 86% 84% Done, but infrequently.

70% 80% 75% Rarely done.

< 70% 35% Never done.

Enforcement 

Penalties

94% 100% 97%

Agency has the authority to impose punitive 

measures, including monetary fines, towards 

violators such as in delegated Title V Operating 

Permit programs. 3% 97% 2.91%

87% 93% 90%

Agency has the authority to impose punitive 

measures, including monetary fines, towards 

violators such as in delegated Title V Operating 

Permit programs.

81% 86% 84%

Agency has the authority to impose punitive 

measures, including monetary fines, towards 

violators such as in delegated Title V Operating 

Permit programs.

70% 80% 75%

Agency has the authority to impose punitive 

measures, including monetary fines, towards 

violators such as in delegated Title V Operating 

Permit programs.

< 70% 35%

Agency does not have sufficient authority to 

impose punitive measures towards violators.

C. Other factors (9 criteria, each assigned weighting of 2% of total):

Compliance 

Certifications

94% 100% 97%

Source subject to Title V or other type of 

compliance certification.

87% 93% 90%

Source subject to Title V or other type of 

compliance certification.

81% 86% 84%

Source not subject to any type of compliance 

certification.

70% 80% 75%

Source not subject to any type of compliance 

certification. 2% 75% 1.5%

< 70% 35%

Source not subject to any type of compliance 

certification.

Inspection 

Frequency

94% 100% 97%

Source(s) are inspected once every 2 years or more 

frequently. 2% 97% 1.94%

87% 93% 90%

Source(s) inspected every 3 years or more 

frequently.

81% 86% 84%

Source(s) inspected every 5 years or more 

frequently.

70% 80% 75% Inspection of source(s) infrequent; > every 5 years.

< 70% 35% Inspections rarely, if ever, performed.

EPA HPV 

Enforcement

94% 100% 97%

Agency has sufficient resources to implement 

EPA’s 12/22/98 HPV policy. 2% 97% 1.94%

87% 93% 90%

Agency’s resources allow it to implement EPA’s 

12/22/98 HPV policy in most instances.

81% 86% 84%

Agency’s resources allow it to implement EPA’s 

12/22/98 HPV policy in most instances.

70% 80% 75%

Agency’s resources allow it to implement EPA’s 

12/22/98 HPV policy more often than not.

< 70% 35%

Resource constraints prohibit agency from 

implementing EPA’s 12/22/98 HPV policy in most 

instances.
2008 Maricopa Co. PM10 Emission Inventory A3–15 June 2011

Factor Range

Midpt. 

value Description Weight

Value 

assigned to 

MCAQD

Score(= 

weight × 

value)

Operator 

Training

94% 100% 97%

Control equipment operators complete a formal 

training program on use of the equipment; the

program is kept up to date and has been reviewed 

by the regulatory agency.

87% 93% 90%

Control equipment operators complete formal 

training program, and such program is kept up to 

date and available for review by the regulatory 

agency upon request.

81% 86% 84%

Control equipment operators complete some 

amount of formal training.

70% 0.8 75%

Control equipment operators receive only on the 

job training. 2% 75% 1.5%

< 70% 35%

Control equipment operators receive no specific 

training.

Media 

Publicity

94% 100% 97% Media publicity of enforcement actions. 2% 97% 1.94%

87% 93% 90% Media publicity of enforcement actions.

81% 86% 84% Media publicity of enforcement actions.

70% 80% 75% Media publicity of enforcement actions.

< 70% 35% No media publicity of enforcement actions.

Regulatory 

Workshops

94% 100% 97%

Regulatory workshops are available annually, 

and/or the implementing agency mails regulatory 

information packages each year. 2% 97% 1.94%

87% 93% 90%

Regulatory workshops are available every 1-2 

years, and/or the implementing agency mails 

regulatory information packages every 1-2 years.

81% 86% 84%

Regulatory workshops are available every 2-3 

years, and/or the implementing agency mails 

regulatory information packages once every 2-3 

years.

70% 80% 75%

Regulatory workshop not routinely available, but 

implementing agency mails regulatory information 

packages out about once every 2-3 years.

< 70% 35%

Regulatory workshops not routinely available. The 

implementing agency mails regulatory information 

packages infrequently, if ever.

Inspector 

Training

94% 100% 97%

Inspectors must undergo 2 weeks of comprehensive basic training, and 1 to 2 weeks of source 

specific training, and such training is updated each 

year.

87% 93% 90%

Inspectors must undergo 1 to 2 weeks of basic 

training and 1 week of source specific training and 

such training is updated every 1-2 years. 2% 90% 1.80%

81% 86% 84%

Inspectors must undergo 1 to 2 weeks of basic 

training and 3 to 5 days of source specific training, 

and such training is updated every 1-2 years.

70% 80% 75%

Inspectors must undergo 1 to 2 weeks of basic 

training and 1 to 3 days of source specific training, 

and such training is updated every 1-2 years. 

< 70% 35%

Inspectors must undergo less than 5 days of basic 

training less than 3 days of source specific 

training, and such training is updated only every 2 

years or less frequently.
2008 Maricopa Co. PM10 Emission Inventory A3–16 June 2011

Factor Range

Midpt. 

value Description Weight

Value 

assigned to 

MCAQD

Score(= 

weight × 

value)

Testing 

Guidelines

94% 100% 97%

Specific guidelines and schedule for testing and 

test methods exist. 2% 97% 1.94%

87% 93% 90%

Specific guidelines on testing and test methods 

exist, but no schedule for testing.

81% 86% 84%

Specific guidelines on testing and test methods 

exist, but no schedule for testing.

70% 80% 75%

Specific guidelines on testing and test methods, 

but no schedule for testing.

< 70% 35%

Only general guidance on testing, or no mention of 

testing requirements.

Follow-up 

Inspections

94% 100% 97%

Follow-up inspections always or almost always 

conducted (90 % of the time or more). 2% 97% 1.94%

87% 93% 90%

Follow-up inspections usually conducted

(approximately 75% of the time).

81% 86% 84%

Follow-up inspections sometimes conducted

(approximately 50% of the time).

70% 80% 75%

Follow-up inspections infrequently conducted

(approximately 25% of the time).

< 70% 35%

Follow-up inspections rarely or never conducted

(10% of the time or less)

Overall rule effectiveness score for non-Title V facilities: 84.27%
 Appendix 4. Windblown Dust Emission Estimation Methodology 

2008 Maricopa Co. PM10 Emission Inventory A4–1 June 2011

Introduction 

The production of windblown dust occurs through an intricate process where the force of wind 

initiates the movement of soil particles. As stated below, 

This process has the distinct phases of particle entrainment, transport and 

deposition. It is a complex process because it is affected by many factors which 

include atmospheric conditions (e.g., wind, precipitation and temperature), soil 

properties (e.g., soil texture, composition and aggregation), land-surface 

characteristics (e.g., topography, moisture, aerodynamic roughness length, 

vegetation and non-erodible elements) and land-use practice (e.g., farming, 

grazing and mining). During a wind-erosion event, these factors interact with 

each other and, as erosion progresses, the properties of the eroded surface can be 

significantly modified. (Shao, 2008a) 

The development of an annual inventory of PM10 emissions from windblown dust focuses on 

quantifying the first phase of windblown dust production: particle entrainment. The phases of 

transport and deposition are typically explored during modeling exercises of specific windblown 

dust events and are not discussed here. 

An assortment of dust emission schemes have been developed that attempt to quantify the 

entrainment of windblown dust (e.g., “Open Area Wind Erosion” chapter in WRAP Fugitive Dust 

Handbook, WGA, 2006). These schemes differ greatly depending on the geographic scale 

(local, regional or global) and theoretical constructs of the scheme (e.g., assessment of threshold 

wind speeds, the importance of soil properties and land uses, etc.). Published empirical data on 

windblown dust emissions varies widely as well, with dust emission rates for a given wind speed 

varying from 10-1 to 105 μg m

-2

s

-1 (Shao, 2008b). This suggests that the specific conditions and 

properties of subject soils greatly modify dust emission rates, and that the accuracy of a dust 

emission scheme is heavily dependent on the quality of the input data describing each of these 

controlling factors (e.g., surface roughness lengths, soil texture, moisture content, vegetation, 

etc.). Often, there is no reliable data available to account for a controlling factor (e.g., soil 

moisture or surface roughness lengths), forcing dust schemes to use surrogates or broad 

assumptions in an attempt to incorporate the effects of a controlling factor. Additionally, even 

when quality data on a relevant factor exists (e.g., soil texture), the role of that factor as it 

interacts with other factors is uncertain (Alfaro et al., 2004) or could change as atmospheric or 

soil conditions are altered throughout the year. 

The inherent uncertainties involved with any windblown dust emission scheme require that the 

available input data for the region of interest be scrutinized to help inform the selection of an 

appropriate scheme. In choosing a dust emission scheme for this inventory, the focus was placed 

upon a theoretical model that best describes local, observed windblown dust events combined 

with empirical data from wind tunnel studies performed in the deserts of the southwest U.S. 

Supply-Limited Windblown Dust Emission Scheme 

The deserts of the southwest U.S., including Maricopa County, are characterized as supplylimited environments (Gillette and Chen, 2001; Zender and Kwon, 2005), where the potential for 

generating windblown dust is controlled primarily by the amount of surface material available 

for entrainment. In contrast, traditional dust emission schemes consider soils to be transport-
2008 Maricopa Co. PM10 Emission Inventory A4–2 June 2011

limited, where windblown dust emissions are controlled solely by the force of wind (Bagnold, 

1941; Greeley and Iverson, 1985). Traditional dust emission schemes perform best in areas 

where contiguous desert land with little vegetation exists (e.g., Sahara Desert). The Sonoran 

Desert, of which Maricopa County is a part of, contains a wide variety of vegetation, which can 

be quite dense in some areas, severely limiting the amount of exposed soil to be entrained by 

wind. Since the bulk of wind erosion research is rooted in the physics of transport-limited soils, 

most dust emission schemes (Gillette and Passi, 1988; Shao et al., 1993; Marticorena and 

Bergametti, 1995; Alfaro and Gomes, 2001) do not address many of the physical realities of 

supply-limited soils. 

A major theoretical tenet of transport-limited schemes is that little or no dust emissions occur 

until wind speeds reach the threshold required for saltation to occur; the process by which the 

dynamic bombardment of sand particles blasts and breaks down aggregated soils to then be 

suspended as dust emissions. However, the supply-limited soils of the desert southwest have 

been shown to emit substantial quantities of dust, even the majority of dust emissions, in the 

absence of saltation (Macpherson et al., 2008). While the southwest deserts can experience high 

magnitude wind events where saltation dominates dust production (e.g., haboob), the majority of 

windblown dust emissions occur during lower intensity, higher frequency events (e.g., synoptic 

scale fronts, dust devils) (Koch and Renno, 2005; Macpherson et al., 2008). These events often 

do not reach the threshold wind speeds required for saltation to occur, yet monitoring data 

consistently record elevated ambient PM10 concentrations at these wind speeds (see further 

discussion in section on Threshold Friction Velocity). This suggests that significant quantities of 

dust emissions are generated primarily through direct aerodynamic entrainment of available 

surface material, before saltation occurs. Despite concerns that direct aerodynamic entrainment 

is limited due to the strong interactive cohesive forces between dust particles (Iverson and White, 

1982), several studies have shown the importance of direct aerodynamic entrainment in the 

production of windblown dust (Loosmore and Hunt, 2000; Roney and White 2004; Kjelgaard et 

al., 2004; Macpherson et al., 2008; Harris and Davidson 2009). Consequently, the dust scheme 

chosen for the supply-limited environment of Maricopa County includes the process of direct 

aerodynamic entrainment as a major contributor to the production of windblown dust. 

Another key limitation of transport-limited schemes concerns surface disturbance of soils. 

Disturbance levels of soils have been shown to be a key factor in controlling the intensity of dust 

emissions during a wind event (Tegen and Fung, 1995; Belnap and Gilliette, 1998; Gillette and 

Chen, 2001; Zender and Newman, 2003; Baddock et al., 2011). However, many transportlimited schemes do not have a direct mechanism to incorporate the effects of disturbed soil on 

dust production. Since dust emissions in a transport-limited scheme are dependent solely on 

saltation, a disturbed soil is often theoretically assumed to emit at the same rate as a stable soil 

since the texture, or particle size distribution of the soil is uniform in both disturbed and stable 

conditions (Alfaro et al., 2004). A common adjustment made to account for disturbance in 

traditional dust schemes is to assume that disturbed soils have lower threshold friction velocities 

than stable soils (WGA, 2006). This effect has been shown in relation to saltation (Gillette, 

1980), but does not necessarily reflect the threshold friction velocities required for dust 

emissions, since supply-limited soils can show dust emissions in the absence of saltation on both 

disturbed and stable soils (Macpherson et al., 2008). 

Instead of directly addressing surface disturbance, incorporation of the surface roughness length 

of the soil (which can provide an approximation for the non-erodible elements of the soil) is 

usually assumed to be the principal limiter of dust production, beyond friction velocities, in 

transport-limited schemes (Marticorena et al., 1997; Alfaro et al., 2004). Surface roughness 
2008 Maricopa Co. PM10 Emission Inventory A4–3 June 2011

lengths (the theoretical height at which the mean wind speed is assumed to be zero) are either 

calculated through direct measurement of wind speeds at varying heights or approximated 

through equations that estimate the roughness elements (e.g., rocks, vegetation, structures) 

associated with land cover or land uses. This produces wide variations in the estimation of 

surface roughness lengths for similar surfaces (MacKinnon et al., 2004). Surface roughness 

values have also been shown to change dynamically with effects from factors such as 

atmospheric conditions, past wind events, levels of disturbance and vegetation growth (Greeley 

et al., 1997). Attempts have been made recently to improve the database of available surface 

roughness lengths through satellite data, but incorporation of these data has not readily occurred 

and is largely focused on global scale dust emissions (Prigent et al., 2005). Because of the 

transient nature of surface roughness lengths and differing methodologies used to measure these 

lengths, a reliable local database does not exist that can incorporate their effects, especially when 

dealing with a large time period like an annual inventory (Marticorena et al., 2006). 

While surface roughness lengths can eliminate rough surfaces as sources of dust production (i.e., 

many dust schemes assume no windblown dust emissions occur from surfaces with roughness 

lengths greater than 0.1 cm; Gillette, 1999) it cannot explain the difference in emissions seen 

between disturbed and stable soils at similar roughness lengths. In fact, the Owen Effect (Owen, 

1964) demonstrates that surface roughness actually increases during saltation events. This 

positive feedback loop has the effect of simultaneously increasing friction velocities and saltation 

effects, which in turn increase vertical flux emissions (Gillette et al., 1998). Additionally, with 

supply-limited soils in particular, disturbed soils have been shown to produce orders of 

magnitude higher dust emissions than similar stable soils, despite having similar surface 

roughness lengths (Nickling and Gillies, 1989; Macpherson et al., 2008). This is because 

disturbance of the soil, through breaking of surface crusts and reorientation of surface grains, has 

the foremost effect of creating larger reservoirs of surface material available to be entrained as 

compared to stable soils. Since actual surface roughness lengths of subject soils are largely 

unknown and vary over time; and because surface roughness does not directly address the effects 

of disturbed soils, another variable is required to approximate disturbance levels. In this scheme, 

disturbance of soils is determined through use of site-specific inspection data of specific land 

uses gathered by Maricopa County Air Quality Department (MCAQD) personnel (further detail 

available in section on Threshold Friction Velocity). 

In addition to the conceptual dust scheme associated with supply-limited soils, empirical wind 

tunnel data gathered in local supply-limited environments is utilized in the development of 

vertical dust fluxes. Three data sets of wind tunnel tests performed in the southwest U.S. (areas 

around Barstow, California; Las Vegas, Nevada and southern Arizona) present empirical data on 

windblown dust emission rates (Nickling and Gillies, 1989; Wacaser et al., 2006; Macpherson et 

al., 2008). These data confirm the initiation of dust emissions at wind speeds lower than 

thresholds required for saltation and that disturbed soils produce higher dust emissions than 

stable soils. These outcomes are expected in supply-limited environments and support the use of 

a dust scheme modeled around the characteristics of supply-limited environments. Specifically, 

the wind tunnel tests performed in southern Arizona (Nickling and Gillies, 1989) form the basis 

of the vertical fluxes (dust emission rates) used to quantify PM10 emissions from windblown dust 

in Maricopa County and the PM10 nonattainment area (see section on Vertical Emission Fluxes 

for further discussion). 

As highlighted in the introduction, there are many factors that control the production of 

windblown dust beyond wind speed velocities and disturbance levels that cannot be directly 

accounted for in this dust scheme (e.g., soil texture, soil moisture, topography, land use, etc.). 
2008 Maricopa Co. PM10 Emission Inventory A4–4 June 2011

Data for these factors can be limited, nonexistent or unreliable. It is also unknown what degree 

of importance each of these factors have when they combine in the processes that contribute to 

the production of windblown dust. In order to account for the role of these missing variables, 

windblown dust emissions developed here were standardized to match observed PM10 monitor 

concentrations when high winds were present. This sensitivity analysis puts the windblown dust 

emission estimates in context with other emissions sources and provides a reality check on dust 

emissions developed using only wind speed velocities and vertical flux equations. The analysis 

of PM10 concentrations under elevated wind speeds estimated that approximately 10% of annual 

PM10 emissions are linked to high wind speeds (see Standardized Windblown Dust Emissions 

section for more information). As such, windblown dust emissions have been limited to no more 

than 10% of the total annual inventory for Maricopa County and the PM10 nonattainment area. 

Threshold Friction Velocity 

An essential factor to any windblown dust scheme involves determining the threshold friction 

velocity (represented as u*

t); the minimum wind speed at which windblown dust emissions are 

initiated at ground level. In reality, the threshold friction velocity will change based upon the 

individual properties of the subject soil during any given wind event. However, for the purposes 

of development of a windblown dust inventory, it is necessary to identify a minimum wind speed 

at which dust production can theoretically begin. The threshold friction velocity for this 

inventory was identified using the theoretical principles of aerodynamic entrainment observed on 

supply-limited soils (Macpherson et al., 2008) and empirical data from regional wind tunnel 

tests, local meteorological data, and local PM10 monitoring data. 

Many dust schemes set separate threshold velocities depending upon a measured or assumed set 

of soil properties. In the absence of, or augmentation to, local wind tunnel studies, soil texture 

and soil roughness lengths are common variables used to determine threshold friction velocities. 

In traditional transport-limited schemes, the physics of saltation dictate that loose, sandy soils 

will have lower threshold friction velocities than undisturbed clay- or silt-dominated soils 

(Gillette, 1999). However, the role of soil texture is unclear in the published literature, with 

recent studies finding that soil texture plays only a secondary role in dust production (Chatenet et 

al., 1996; Alfaro et al., 2004). 

Wind tunnel studies done in the supply-limited deserts of the southwestern U.S. also show little 

connection between soil texture and threshold friction velocities. Wind tunnel studies in Las 

Vegas, Nevada (Wacaser et al., 2006) on nine different soil types (including both stable and 

disturbed soil conditions) found that all soil types emitted dust at the lowest available wind speed 

of the wind tunnel, approximately 11 mph, suggesting that soil texture plays no distinguishable 

role in setting threshold friction velocities. Studies in the deserts around Barstow, California 

found that dust emissions were initiated for three different soil textures (stable and disturbed) at 

ground-level wind speeds (u*) between 16 to 26 cm/s. Depending on surface roughness values, 

these ground-level wind speeds translate into 10-meter wind speeds of approximately 10–15 

mph. Wind tunnel studies performed in southern Arizona on mostly disturbed, sandy or sandy 

loam soils found saltation velocities to be between 13 to 30 mph. Roney and White (2004) found 

that direct aerodynamic entrainment threshold friction velocities are approximately 50 to 75% 

less than saltation thresholds, suggesting that the dust emission thresholds for southern Arizona 

could be as low as 7 mph. The measured wind tunnel data, combined with the conceptual 

ambiguity surrounding the role of soil texture, provide limited empirical rationale to set threshold 

friction velocities according to soil texture alone. 
2008 Maricopa Co. PM10 Emission Inventory A4–5 June 2011

Large changes in surface roughness lengths have been clearly shown to affect threshold friction 

velocities of soils (Marticorena et al., 1997). However, there is no reliable data available to 

estimate surface roughness lengths throughout Maricopa County, especially on lands where 

frequent human activity is expected (e.g., agriculture, construction sites, urban vacant lots) 

(Marticorena et al., 2006). As mentioned earlier, these values are not static and change with 

atmospheric and anthropogenic activities. Surfaces that are known to have uniformly high 

surface roughness lengths (e.g., built-out urban areas and mountain ranges) have already been 

eliminated from the underlying land uses that are selected as possible sources of windblown dust. 

The land uses that remain (e.g., open and vacant areas, agriculture, construction sites) can have 

varying surface roughness lengths depending on the level of human and natural activity 

occurring on the soils. As such, tying threshold friction velocities to assumed surface roughness 

lengths is not a viable option. 

Examination of local PM10 concentration and meteorological monitoring data in Maricopa 

County show that when wind speeds reach approximately 12 mph (measured as a 5-minute 

average), average PM10 concentrations are consistently higher than concentrations at lower wind 

speeds. Also, as wind speeds exceed 12 mph, average PM10 concentrations uniformly increase 

with increasing wind speeds. These monitoring stations are surrounded by a wide variety of land 

uses and differing surface roughness lengths, yet they all consistently display similar 

relationships between wind speeds and PM10 concentrations. Figure A4–1 displays the annual 

average relationship between wind speed and PM10 concentrations from four distinct monitoring 

locations which represent a variety of land uses, soil types and geographic conditions within 

Maricopa County. Although not shown in Figure A4-1, the remaining four monitoring stations 

that collected 5-minute PM10 concentration data in 2008 (Central Phoenix, Durango Complex, 

Greenwood and South Phoenix) show similar relationships between PM10 concentrations and 

wind speeds. This data, combined with the information developed from the wind tunnel studies 

performed in the southwest U.S., suggest that 12 mph is a valid approximation of the threshold 

friction velocity required for the initiation of windblown dust in Maricopa County. 

 
2008 Maricopa Co. PM10 Emission Inventory A4–6 June 2011

Figure A4–1. 2008 average 5-minute PM10 concentration by wind speed at sample Maricopa County 

monitoring stations.

Vertical Emission Fluxes 

The rate at which windblown dust emissions are created and suspended in air is described as a 

vertical flux. Shao (2008a) describes three processes that contribute to the verical flux: (1) 

Aerodynamic Entrainment where dust particles are directly lifted off the surface; (2) Saltation 

Bombardment as sand grains or aggregates strike the surface and eject dust particles and (3) 

Aggregate Disintegration where dust particles attached to sand grains disintegrate under strong 

winds. A vertical flux rate can be developed through an equation that represents these processes, 

or empirically with the use of wind tunnel studies. 

The vertical flux rate developed for this inventory uses wind tunnel studies performed in 

southern Arizona (Nickling and Gillies, 1989). These studies were performed under a variety of 

land uses (e.g., native desert, riverbeds, construction sites, agricultural land, mine tailings and 

dune flats) in soil textures that consisted of either sand or sandy loams. The studies were 

performed on thirteen sites that are described as disturbed by human activity, or having a strong 

20

40

60

80

100

120

140

160

180

200

0 2 4 6 8 10 12 14 16 18 20

2008 Average 5-Minute PM10

Concentration

Wind Speed (mph)

Buckeye Monitor

20

40

60

80

100

120

140

160

180

200

0 2 4 6 8 10 12 14 16 18 20

2008 Average 5-Minute PM10

Concentration

Wind Speed (mph)

Higley Monitor

20

40

60

80

100

120

140

160

180

200

0 2 4 6 8 10 12 14 16 18 20

2008 Average 5-Minute PM10

Concentration

Wind Speed (mph)

West 43rd Avenue Monitor

20

40

60

80

100

120

140

160

180

200

0 2 4 6 8 10 12 14 16 18 20

2008 Average 5-minute PM10

Concentration

Wind Speed (mph)

West Phoenix Monitor
2008 Maricopa Co. PM10 Emission Inventory A4–7 June 2011

potential to be disturbed because of the surface condition of the soil. The authors of the study 

provide vertical flux rates grouped by land use and by percent clay content. However, these 

grouping are not useful for this inventory given that recent research (Alfaro et al., 2004) and 

other wind tunnel studies (Wacaser et al., 2006) have shown that soil texture is not of primary 

importance in determining vertical fluxes. Fluxes based upon land use groupings provide limited 

information on soil condition and ignore other essential soil characteristics. Additionally, the 

wind tunnel studies performed in Barstow, California and Las Vegas, Nevada (Wacaser et al., 

2006; Macpherson et al., 2008) show that soil disturbance is the largest factor affecting the 

vertical flux rate of a soil. 

For the above reasons, applicable data from the southern Arizona studies (Nickling and Gillies, 

1989) were grouped together to form an overall vertical flux for disturbed soils. Data from seven 

of the thirteen test sites was grouped together to form the disturbed soil vertical flux. These 

seven sites include the land uses of construction activities, abandoned agriculture, dry river beds 

and scrub desert. Six sites were excluded because the land uses or soil properties do not exist in 

Maricopa County (mine tailings, sand dunes) or because they were conducted on active 

agricultural fields. Dust emissions from active agricultural fields are calculated using a formula 

developed by the U.S. Department of Agriculture (see Active Agriculture section). Inactive 

agricultural land uses that are either fallow, abandoned or some other use (e.g., dairies) are 

represented by the vertical fluxes developed through the southern Arizona wind tunnel tests, as 

these land uses do not have active crop cover. 

To create the disturbed soil vertical flux, a simple scatter plot of the data (frcition velocity 

against PM10 emissions) was made of the selected southern Arizona wind tunnel data. A power 

relationship is then developed from the data to produce the best fitting curve of the vertical flux. 

The assembled data performs reasonably well (R2 of 0.646) in developing a statistically 

signifigant vertical flux (4.36 x 10-15u*4.3961 g cm

-2 

s

-1) for disturbed soils, given the limited 

number of test sites and the lack of other variables describing the soil properties. There is 

significant scatter in the data seen at higher friction velocities. This phenomenon has been 

documented in other studies, and again highlights the fact that there are many other factors 

besides friction velocity that determine the vertical flux rates of soils (Houser and Nickling, 

2001). Despite this short coming, friction velocity remains the primary variable with which to 

describe the magnitude of dust emissions; largely because it is one of the easiest variables to 

verify with quantitative data. The vertical flux developed through the southern Arizona wind 

tunnel data is in the same order of magnitude, and compares well with, other fluxes measured in 

similar wind tunnel tests in Barstow, California and Las Vegas, Nevada (Wacaser et al., 2006; 

Macpherson et al., 2008). Figure A4–2 graphs the data points from the wind tunnel studies used 

to develop the vertical flux for disturbed soil. 
2008 Maricopa Co. PM10 Emission Inventory A4–8 June 2011

Figure A4–2. Vertical flux for disturbed soil. 

Since the southern Arizona wind tunnel tests provided limited information on vertical fluxes 

from stable soils, a stable soil vertical flux could not be developed directly from the wind tunnel 

data. As a surrogate, the ratio of stable to disturbed vertical fluxes found in the wind tunnel 

studies performed in Barstow, California (Macpherson et al., 2008) was used to develop the 

vertical flux for stable land uses. The Barstow area study contained multiple tests done on stable 

and disturbed soils at the same test sites. This allows for a direct comparison of the windblown 

dust emission rates between stable and disturbed soils. Data from all of the Barstow wind tunnel 

tests were used except for the tests done on salt-crusted soils (dry lake beds), as this type of soil 

is rare in Maricopa County. The results of the Barstow studies indicate that the stable soil 

vertical flux was found to produce emissions at a rate of about 12 to 20% of the disturbed soil 

vertical flux.1

Determination of the amount of disturbed land in each land use category is accomplished through 

use of rule effectiveness rates developed by MCAQD (see Appendix 3 for details on rule 

effectiveness), since direct measurement of soil disturbance is not feasible (i.e., soil conditions 

are constantly changing) in an area as large as Maricopa County. Activities on land uses subject 

to windblown dust are regulated by MCAQD rules that require specific activity-related control 

measures that stabilize the soil. Compliance and inspection records provide an estimate of how 

often these measures are being implemented and the frequency of observed violations of the 

measures. By implied extension, this is also an estimate of how often a regulated land use soil is 

stabilized. Examination of compliance records for the period of July 2008 through June 2009 

produced rule effectiveness rates of 90% for developing land uses (Rule 310), 65% for sand and 

                                                           

1

 For disturbed surfaces a flux of 2.35 x 10-12u*2.5604 g cm-2 s-1 was calculated using the Barstow wind tunnel data; 

likewise for stable surfaces, a flux of 2.96 x 10-12u*1.9744 g cm-2 s-1 was calculated. The ratio of these Barstow fluxes 

applied to the southern Arizona disturbed soil vertical flux (at the mean of each wind speed bin) allows for 

calculation of a vertical flux that can represent emissions from stable southern Arizona soils. 

y = 4.36×10-15u*4.3961

R2 = 0.646

0.0E+00

1.0E-07

2.0E-07

3.0E-07

4.0E-07

5.0E-07

6.0E-07

7.0E-07

10 15 20 25 30 35 40 45 50 55 60 65

PM10 Emissions (g cm-2 s-1)

Friction Velocity, u* (cm/s)

Vertical Flux for Disturbed Soil
2008 Maricopa Co. PM10 Emission Inventory A4–9 June 2011

gravel processing and mining land uses (Rule 316), and 95% for vacant land uses (Rule 310.01). 

For the purposes of calculating windblown dust, these rule effectiveness percentages are used as 

surrogates for the percentage of a land use category that is assumed to be disturbed. Thus, the 

Rule 310 effectiveness rate of 90% serves as a surrogate for developing land uses (i.e., 90% of 

the land is stable, 10% is disturbed), the Rule 316 rate of 65% serves as a surrogate for sand and 

gravel processing and mining activities, and the Rule 310.01 rate of 95% serves as a surrogate 

for all open and vacant lands, landfills, automotive test tracks and inactive agricultural land uses. 

The rule effectiveness rate developed for agricultural operations (55%) applies only to active 

agricultural land uses and is incorporated in the equation used to estimate windblown dust from 

active agricultural fields (see section on Active Agricultural Emissions). 

In order to utilize the disturbed soil and stable soil vertical fluxes for generating PM10 emission 

estimates, PM10 emission factors based upon these vertical fluxes are created. Initially, the units 

of the fluxes were converted (from g cm-2 s-1 to tons acre-1 5-minute-1) to match available 

meteorological data on wind speeds and comparable units of mass with other sections of this 

inventory. Selection of a 5-minute average for the wind speed value was chosen because it is the 

shortest duration of wind speed available that is constantly measured. Windblown dust 

production has been shown to be more closely correlated with gusts than with averaged wind 

speeds (Cakmur et al., 2004; Engelstaedter and Washington, 2007). However, gusts (usually 1-

second maximums) are not constantly measured which does not allow for their use in calculation 

of emissions in an annual inventory. Thus, the 5-minute average wind speed is selected as the 

input wind speed in both vertical fluxes (see Wind Speed Data section for more information). 

These 5-minute average wind speeds are aggregated into five 10-meter wind speed bins (12-15 

mph, 15-20 mph, 20-25 mph, 25-30 mph, and 30-35 mph) in order to develop a disturbed soil 

and stable soil emission factor per each wind speed bin. The midpoint of each wind speed bin 

(13.5 mph, 17.5 mph, 22.5 mph, 27.5 mph, and 32.5 mph) is converted via the Prandtl equation2

to a u* value (surface wind speed) for use in the disturbed soil vertical flux equation, resulting in 

a disturbed soil emission factor for each wind speed bin. After the disturbed soil emission 

factors are calculated, the ratio between disturbed and stable soil emissions observed at the 

Barstow tests is used to develop a stable soil emission factor for each wind speed bin. Table A4–

1 shows the resulting stable soil and disturbed soil emission factors for each wind speed bin (by 

land use category) and the ratio of stable to disturbed soil emissions observed in the Barstow area 

wind tunnel studies. 

 

                                                           

2 The fluid dynamics Prandtl equation: ܷ ൌ ௨כ

௞

݈݊ ௭

௭೚

, allows for the calculation of u* at various 10-meter wind 

speeds by solving for u*: (כݑ ൌ ܷ ௞

௟௡ ೥

೥೚

 ), where U is wind speed at 10 meters, k is Von Karman’s constant (0.4), z is 

10 meters, and zo is measured surface roughness value. An average value of 0.025cm (as measured during southern 

Arizona wind tunnel tests) was assumed for zo Once u* is calculated for each wind speed bin, that value is then 

inserted into the vertical flux rate to develop the emission factors seen in Table A4-1.
2008 Maricopa Co. PM10 Emission Inventory A4–10 June 2011

Table A4–1. PM10 emission factors for stable and disturbed land uses by wind speed bin. 

 

% of 

Land 

Use 

Category

PM10 Emission Factor 

 (tons/acre-5-minute) 

by 10-Meter Wind Speed Bin (mph) 

Land Use Category 12-15 15-20 20-25 25-30 30-35 

Agriculture (Active) NA – Calculated Under Different Methodology 

Agriculture (Inactive) – Stable 95% 1.10×10-5 2.93×10-5 7.68×10-5 1.64×10-4 3.10×10-4

Agriculture (Inactive) – Disturbed 5% 5.44×10-5 1.69×10-4 5.14×10-4 1.24×10-3 2.57×10-3

Developing Land – Stable 90% 1.10×10-5 2.93×10-5 7.68×10-5 1.64×10-4 3.10×10-4

Developing Land – Disturbed 10% 5.44×10-5 1.69×10-4 5.14×10-4 1.24×10-3 2.57×10-3

Open Space, River Beds, Vacant, Landfill, 

Test Tracks – Stable 95% 1.10×10-5 2.93×10-5 7.68×10-5 1.64×10-4 3.10×10-4

Open Space, River Beds, Vacant, Landfill, 

Test Tracks –Disturbed 5% 5.44×10-5 1.69×10-4 5.14×10-4 1.24×10-3 2.57×10-3

Sand & Gravel, Mining – Stable 65% 1.10×10-5 2.93×10-5 7.68×10-5 1.64×10-4 3.10×10-4

Sand & Gravel, Mining – Disturbed 35% 5.44×10-5 1.69×10-4 5.14×10-4 1.24×10-3 2.57×10-3

Disturbed Soil Vertical Flux: Ratio of Barstow Stable to Disturbed Soil Emissions 

4.36 × 10-15u*4.3961 g cm-2 s-1 20.16% 17.33% 14.94% 13.29% 12.06% 

Land Use Data 

The Maricopa Association of Governments (MAG) maintains GIS data on land use coverage in 

Maricopa County. The GIS data compiled by MAG represents land use coverage for the year 

2009. A detailed explanation on how MAG assembles and maintains its GIS database is 

included as Attachment I of this Appendix. In addition to data provided by MAG, the Arizona 

Cotton Research and Protection Council (ACRPC) provided supplemental GIS information on 

agricultural field crops in portions of Area A in Maricopa County. Where appropriate, data from 

the ACRPC was used to update the agricultural land use category maintained by MAG. A total 

of nine individual land use categories were identified as having potential to emit windblown 

dust. These categories were selected due to an abundant presence of exposed soils and the 

possibility of periodic or frequent disturbance. Other land uses not selected may on occasion 

emit windblown dust, but the presence of structures or vegetated/paved surfaces associated with 

these land uses limits their ability to emit windblown dust on a consistent basis. Land uses on 

steeply sloped rocky terrain were also excluded as sources of windblown dust, as the large 

surface roughness lengths prohibits the production of windblown dust from this type of 

topography. Table A4–2 lists a description of, and the acreage associated with, the nine land use 

categories considered as sources of windblown dust. Figure A4–3 shows the extent and 

distribution of the land use categories determined to have the potential to emit windblown dust. 

Table A4–2. Land use categories associated with the production of windblown dust.

MAG Land Use Category 

Maricopa 

County 

Acreage 

PM10

NAA 

Acreage Description 

Active Open Space 59,145 54,835 Natural desert community parks (e.g., White Tanks)

Agriculture 282,793 116,934 Active fields/orchards, dairies & inactive/abandoned

Auto Test Tracks 19,594 6,888 Unpaved automobile proving grounds

Developing 66,341 60,335 Vacant lands converting to built uses

Landfill 2,705 2,705 Community refuse disposal sites

Mining 3,329 2,004 Rock quarries/pits

Passive Open Space/Wash 1,861,493 341066 State/National parks, bombing range, dry rivers/washes

Sand & Gravel 11,112 10,350 Sand & Gravel processing facilities

Vacant 1,930,606 395,902 Developable/unprotected open spaces
2008 Maricopa Co. PM10 Emission Inventory A4–11 June 2011

Figure A4–3. Distribution of land use categories capable of producing windblown dust emissions. 

Meteorological Data

Thirty-four meteorological stations were used for source data to compile calendar year 2008 

wind speed and precipitation for this inventory of windblown dust. This includes eleven stations 

operated by the Arizona Meteorological Network (AZMET), twenty-two stations operated by the 

Maricopa County Air Quality Department (MCAQD), and one station operated by the Pinal 

County Air Quality Control District (PCAQCD). Stations operated by the National Weather 

Service (NWS) in and around Maricopa County were not chosen for inclusion in this analysis 

due to differences in wind speed data collection methods that preclude “apples-to-apples” 

comparisons with data from the meteorological stations included in this work.3

 Figure A4–4 

displays the location of the included meteorological stations. 

 

                                                           

3

 National Weather Service (NWS) stations report wind speeds in 2-minute averages at the time of posting, while 

AZMET, MCAQD and PCAQCD all report wind speed in hourly averages at the end of each hour or in 5-minute 

averages. 

Active Open Space

Agriculture

Automotive Proving Ground

Developing Employment Generating

Developing Residential

Landfill

Mining

Passive/Restricted Open Space

Sand and Gravel

Vacant

Wash

PM-10 Nonattainment Area
2008 Maricopa Co. PM10 Emission Inventory A4–12 June 2011

Figure A4–4. Location of meteorological stations. 

Wind Speed Data 

For this analysis, 5-minute average wind speeds form the basis of the wind data used in calculating windblown dust emissions. As mentioned earlier, windblown dust emissions have greater 

correlation with gusts than with averaged wind speeds (Cakmur et al., 2004; Engelstaedter and 

Washington, 2007). Data recorded as a 5-minute average provides finer time resolution (versus 

hourly average wind speeds) that can better capture the effects of gusts while still allowing for 

emission estimates to be developed. This approach also allows for any 5-minute time period 

over the threshold friction velocity (12 mph) to be counted and assigned into wind speed bins: 

12–15 mph, 15–20 mph, 20–25 mph, 25–30 mph and 30–35 mph. Creating wind speed bins 

allows for the efficient calculation of emissions while still reflecting the change in magnitude of 

emissions as wind speeds rise. Outlined below are the steps necessary to prepare the wind speed 

data for inclusion in windblown dust emission calculations. 

As an initial step, wind speed data from the selected meteorological stations were uniformly 

adjusted to speeds at 10 meters (to account for the difference in anemometer heights) through use 

of a standard wind profile power-law equation: 

ܷ௭ ൌ ܷ௥ሺܼ/ܼ௥ሻ௣

where Uz is wind speed (in mph) at 10 meters, Ur is wind speed (in mph) at referenced 

anemometer height, Z is 10 meters, Zr is the height (in meters) of the reference anemometer, and 

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@ A@

A@

A@

A@

A@

A@

A@

A@

A@ A@

A@

A@

A@

A@

A@

Meteorological Stations

A@ AZMET

A@ MCAQD

A@ PCAQCD

PM-10 Nonattainment Area
2008 Maricopa Co. PM10 Emission Inventory A4–13 June 2011

p is the power-law exponent. Determination of p was made by comparing wind speeds at 

neighboring stations with different anemometer heights (e.g., AZMET’s Buckeye station at 3 

meters compared with MCAQD’s Buckeye station at 10 meters) through a simple adaptation of 

the power-law equation: 

ൌ ݌

lnሺܷሻ െ lnሺܷ௥ሻ

lnሺܼሻ െ lnሺܼ௥ሻ

The stations used in comparison were all assumed to have similar surface roughness lengths to 

each other as the stations were between 1–3 miles apart. Comparison of hourly average wind 

speeds yielded an average value for p of 0.06 for urban stations and 0.12 for rural stations (only 

those hours when atmospheric conditions are well mixed were used, as applying the approach 

described above for hours with calm winds tends to over-inflate the value of p). 

In addition to correcting for height, adjustments to wind speed were performed to gap-fill 

missing data and interpolate 5-minute average values as necessary. All of the meteorological 

stations report hourly average wind speeds at the end of each hour. In addition, thirteen of the 

MCAQD stations also report 5-minute average wind speeds, with data completion rates of 75% 

or better. The data from these stations were: (1) counted and assigned to one of five wind speed 

bins of 12-15 mph, 15–20 mph, 20–25 mph, 25–30 mph, and 30–35 mph; and (2) “grown” to 

compensate for missing data, based upon the data completion rate of each station. Thus, a 

station that reported 124 5-minute periods assigned to a bin with a data completion rate of 

90.63%, would result in a “grown” bin value of 137 (124 periods divided by 90.63%). Table 

A4–3 presents the recorded and grown 5-minute values by wind speed bin for the year 2008, for 

each of the thirteen MCAQD meteorological stations that were considered. 

Table A4–3. Number of recorded and grown 5-minute average wind speeds for 2008, by wind speed bin and 

meteorological station. 

Recorded 5-Minute Averages Grown 5-Minute Averages 

MCAQD Station 

12-15 

mph 

15–20 

mph 

20–25 

mph 

25–30 

mph 

30–35 

mph 

% Data 

complete 

12-15 

mph 

15–20 

mph 

20–25 

mph 

25–30 

mph 

30–35 

mph 

Buckeye 3030 1679 296 54 12 99.62% 3042 1685 297 54 12 

Coyote Lakes 1846 840 77 1 0 98.71% 1870 851 78 1 0 

Durango Complex 1776 618 33 10 1 96.39% 1843 641 34 10 1 

Dysart 1782 784 92 6 0 78.16% 2280 1003 118 8 0 

Falcon Field 2088 758 95 2 1 76.77% 2720 987 124 3 1 

Greenwood 795 124 11 1 0 90.63% 877 137 12 1 0 

Higley 1896 766 50 8 1 91.02% 2083 842 55 9 1 

North Phoenix 376 80 8 2 0 77.59% 485 103 10 3 0 

South Phoenix 696 169 9 0 1 99.19% 702 170 9 0 1 

Tempe 54 5 0 0 0 86.38% 63 6 0 0 0 

West Chandler 1637 515 42 3 1 99.09% 1652 520 42 3 1 

West Forty-Third 2391 1042 83 13 6 98.44% 2429 1059 84 13 6 

West Phoenix 892 111 8 1 0 92.47% 965 120 9 1 0 

For the stations that do not record 5-minute average wind speeds4

, regression equations were 

developed (based upon those MCAQD stations that do report 5-minute average wind speeds) to 

interpolate counts of 5-minute average values. The equations were derived by regressing 5-

minute average counts in each wind speed bin (dependent [y]) against a count of an hourly 

average wind speeds greater than a pre-determined wind speed (independent [x]). Since the 

                                                           

4

 AZMET and PCAQCD stations report average wind speed only on an hourly basis, and another nine MCAQD 

stations that measure wind speed on a 5-minute average had data completion rates less than 75% for 2008. 
2008 Maricopa Co. PM10 Emission Inventory A4–14 June 2011

majority of wind speed counts exist in the lower wind speed bins (e.g., hourly average wind 

speeds over 25 mph were recorded only ten unique times in 2008), a count of hourly values 

greater than 15 mph was chosen as the independent variable (x). All of the regression equations 

proved to be statistically significant at the 95% confidence level. The results of the regression 

equations for each wind speed bin are shown in Table A4–4. The resulting 5-minute average 

wind speeds (by bin) for all meteorological stations in this study are shown in Table A4–5. 

Table A4–4. Regression equation, p-value, and R2 for interpolating 5-minute average wind speeds, by bin. 

5-minute average 

wind speed bin Regression equation 

p-value 

(probability) R2 

12-15 mph y = 827.00 + 19.80x 0.00007056 77.55% 

15–20 mph y = 150.05 + 11.92x 0.00000006 93.77% 

20–25 mph y = –8.34 + 1.39x 0.00000021 92.09% 

25–30 mph y = –4.20 + 0.31x 0.00009300 76.42% 

30–35 mph y = –0.99 + 0.07x 0.00047000 68.57% 

Table A4–5. Number of interpolated 5-minute average wind speeds, by station and wind speed bin. (Shaded 

cells denote interpolated values.) 

Station Name

Number of hourly 

average values 

> 15 mph

Number of 5-minute average values between:

12-15 

mph 

15–20 

mph 

20–25 

mph 

25–30 

mph 

30–35 

mph 

AZMET Aguila 284 6450 3535 386 84 19 

AZMET Buckeye 149 3777 1926 199 42 9 

AZMET Desert Ridge 70 2213 984 89 18 4 

AZMET Harquahala 274 6252 3416 373 81 18 

AZMET Maricopa 118 3163 1557 156 32 7 

AZMET Mesa 5 926 210 0 0 0 

AZMET Paloma 224 5262 2820 303 65 15 

AZMET Phoenix Encanto 1 847 162 0 0 0 

AZMET Phoenix Greenway 6 946 222 0 0 0 

AZMET Queen Creek 161 4015 2069 215 46 10 

AZMET Waddell 4 906 198 0 0 0 

MCAQD Blue Point 60 2015 865 75 14 3 

MCAQD Buckeye 146 3042 1685 297 54 12 

MCAQD Cave Creek 69 2193 973 88 17 4 

MCAQD Central Phoenix 43 1678 663 51 9 2 

MCAQD Coyote Lakes 54 1870 851 78 1 0 

MCAQD Durango Complex 50 1843 641 34 10 1 

MCAQD Dysart 64 2280 1003 118 8 0 

MCAQD Falcon Field 58 2720 987 124 3 1 

MCAQD Fountain Hills 1 847 162 0 0 0 

MCAQD Glendale 19 1203 377 18 2 0 

MCAQD Greenwood 1 877 137 12 1 0 

MCAQD Higley 42 2083 842 55 9 1 

MCAQD Mesa 42 1659 651 50 9 2 

MCAQD North Phoenix 4 485 103 10 3 0 

MCAQD Pinnacle Peak 51 1837 758 63 12 3 

MCAQD South Phoenix 6 702 170 9 0 1 

MCAQD South Scottsdale 3 886 186 0 0 0 

MCAQD Tempe 0 63 6 0 0 0 

MCAQD West Forty-Third 65 2429 1059 84 13 6 

MCAQD West Chandler 23 1652 520 42 3 1 

MCAQD West Indian School 19 1203 377 18 2 0 

MCAQD West Phoenix 5 965 120 9 1 0 

PCAQCD Apache Junction 134 3480 1747 178 37 8 
2008 Maricopa Co. PM10 Emission Inventory A4–15 June 2011

Because wind speeds vary dramatically between different meteorological stations in Maricopa 

County (especially in the transition between rural and urban stations), it is important to represent 

those variations in space upon the land uses subject to windblown dust. This is accomplished by 

assigning the wind speed counts in Table A4–5 in GIS (spatial joining) to the land uses nearest 

each meteorological station through a series of Thiessen polygons5 (Pulugurtha and James, 

2006). This process allows for variations in wind speed counts to be representatively distributed 

in space across land uses subject to windblown dust, as opposed to “smearing” averaged wind 

speed counts across all of Maricopa County and the PM10 nonattainment area. As an example, 

Figure A4–5 shows the resulting Thiessen polygons for the 15-20 mph wind speed bin. 

Figure A4–5. Thiessen polygon depiction displaying the number of values for the 15–20 mph wind speed bin.

Precipitation Data 

During days with precipitation, windblown dust emissions are severely, if not completely, 

limited. Precipitation also increases overall soil moisture which acts as a control on the 

production of windblown dust after precipitation has ceased. To account for the role of 

precipitation, a simple formula used by the U.S. EPA when calculating the controlling role of 

precipitation on fugitive dust from unpaved roads can be adapted to windblown dust production 

(US EPA, 2006). 

                                                           

5

 A “Thiessen polygon” depicts an area whose boundaries define the region that is closest to a given point, relative 

to all other given points. 

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@

A@ A@

A@

A@

A@

A@

A@

A@

A@

A@ A@ A@

A@

A@

A@

A@

2820

1557

1747

3416

198

3535

973

865

2069

758

1685

851

1926

162

1059

520

987

842

6

984 222

377

186

170

1003

103

120 663

210

651

377

162

641

137

Meteorological Stations

A@ AZMET

A@ MCAQD

A@ PCAQCD

PM-10 Nonattainment Area

Thiessen Polygon
2008 Maricopa Co. PM10 Emission Inventory A4–16 June 2011

The adapted equation is represented as: 

E = B × (1 – P/N) 

Where E equals emissions, B equals emissions before precipitation, P equals the annual number 

of “wet” days with at least 0.254 mm (0.01 in) of precipitation (39 days in 2008), and N equals 

the number of days in the year (366 in 2008). Using this formula equates to applying a 10.66% 

annual reduction in windblown dust due to precipitation. 

Calculation of Windblown Dust Emissions 

After developing the input data necessary to calculate windblown dust emissions (e.g., wind 

speed bin counts, disturbed and stable vertical flux equations, etc.), emission estimates of PM10

are calculated for both the PM10 nonattainment area and Maricopa County. These emission 

estimates represent the maximum potential emissions from each land use category since they are 

a product of only local wind speeds and emission factors developed from soils expected to emit 

high levels of dust. These emissions will be standardized (adjusted to match observed PM10

concentration under high winds) in the next section to account for a range of controlling factors 

(e.g., surface roughness lengths, soil moisture, vegetation, supply-limitation, etc.) where either 

adequate quantitative data does not exist or cannot be represented as a unique variable in an 

emission estimate equation (see section on Standardized Windblown Dust Emissions). Figure 

A4–6 contains a flow chart showing the steps involved in calculating PM10 emissions from 

windblown dust. 

Figure A4–6. Flow chart of steps involved in developing PM10 emissions from windblown dust. 

 

Calculation of pre-standardized emission estimates begins through the use of GIS to spatially 

assign the 5-minute wind speed bin counts to the underlying land use categories (as shown 

previously in Figure A4–5). These base data are exported from GIS as a spreadsheet, with each 

row of the spreadsheet representing a spatially unique land use category polygon with associated 

wind speed bin counts. The land use and wind speed specific emission factors for disturbed and 

stable soils listed in Table A4–1 are applied to each row of the spreadsheet to produce prestandardized emissions. Since the specific geographic location of surface disturbance is 

unknown and varies throughout the year, each land use polygon is assumed to have the same 

proportion of disturbed and stable soils throughout the year as expressed by the percentages in 

Table A4–1 (i.e., all vacant parcels are assumed to be 95% stable and 5% disturbed). Base data 

and emissions from a sample vacant land use polygon are shown in Table A4–6. All prestandardized emissions from land use categories except active agricultural fields are calculated 

per the methodology presented in Table A4–6. 

 

Develop GIS 

data: 

5-minute 

wind speeds 

& land uses 

Export and apply 

stable and 

disturbed soil 

emission factors 

and correction for 

precipitation 

Pre-standardized 

emissions

Standardized 

Emissions

Standardize 

emissions to 

observed high 

wind PM10

concentrations
2008 Maricopa Co. PM10 Emission Inventory A4–17 June 2011

Table A4–6. Base data and pre-standardized emissions from a sample vacant land use polygon. 

   Polygon 

Acres 

Count of 5-

Minute 

Periods for 

12 - 15 mph 

Count of 5-

Minute 

Periods for 

15 - 20 mph 

Count of 5-

Minute 

Periods for 

20 - 25 mph 

Count of 5-

Minute 

Periods for 

25 - 30 mph 

Count of 5-

Minute 

Periods for 

30 - 35 mph

Vacant Land Use Base Data 22.15 2280 1003 118 8 0

Emission Factors (tons/acre–5-min) 12 - 15 mph 15 - 20 mph 20 - 25 mph 25 - 30 mph 30 - 35 mph

Stable Soil Emission Factor 1.10×10-5 2.93×10-5 7.68×10-5 1.64×10-4 3.10×10-4

Disturbed Soil Emission Factor 5.44×10-5 1.69×10-4 5.14×10-4 1.24×10-3 2.57×10-3

Annual Emissions Acreage 

12 - 15 mph 

Emissions 

(tons) 

15- 20 mph 

Emissions 

(tons) 

20 - 25 mph 

Emissions 

(tons) 

25 - 30 mph 

Emissions 

(tons) 

30 - 35 mph 

Emissions 

(tons) 

Stable Emissions 

(95% of acreage)1 21.04 0.53 0.62 0.19 0.03 0.00

Disturbed Emissions 

(5% of acreage)2

 1.11 0.14 0.19 0.07 0.01 0.00

Total Emissions3 22.15 0.66 0.81 0.26 0.04 0.00 1

 Stable Emissions = Stable Acreage × Wind Speed Bin Count × Wind Speed Bin Emission Factor 

2

 Disturbed Emissions = Disturbed Acreage × Wind Speed Bin Count × Wind Speed Bin Emission Factor 

3

 Total (Pre-standardized) Emissions = Stable Emissions + Disturbed Emissions 

Windblown Dust Emissions from Active Agricultural Areas

Since crop cover dramatically affects windblown dust production, windblown dust from active 

agricultural areas (fields or orchards with harvested or planted crops) cannot be calculated using 

the vertical fluxes developed for the other land use categories. Some crops, like alfalfa, maintain 

dense vegetative cover all year long and virtually eliminate the possibility of windblown dust 

from these types of fields. Thus, windblown dust from active agricultural fields is calculated 

using a soil erodibility formula developed by the U.S. Department of Agriculture (in US EPA, 

1974): 

Es = a I C K L’ V’ 

where Es equals suspended PM in tons/acre-year, a is a constant (0.0125) representing the portion 

of PM as PM10, I is soil erodibility, C is a climatic factor, K is surface roughness, L' is unsheltered field width and V' is vegetative cover. 

The number of acres harvested in 2008 serves as a surrogate for the amount of active agricultural 

areas in Maricopa County. Data on the amount of acres harvested for 2008 is available through 

the Arizona Agricultural Statistics Bulletin and the U.S. Department of Agriculture National 

(USDA) Agricultural Statistics Service for 2008 (USDA, 2008; AASS, 2009). Data for the other 

variables in the equation is taken from the 1999 Serious Area PM-10 Plan (MAG, 2000). Table 

A4–7 lists the crop-specific values for each variable. 

 
2008 Maricopa Co. PM10 Emission Inventory A4–18 June 2011

Table A4–7. Active Maricopa County agricultural acreage and default values for USDA equation variables, 

by crop type. 

Crop 

2008 

Acreage a I C K L' V' Es

Cotton 18,800 0.0125 63.6 0.318 0.5 0.74 0.7 0.065 

Alfalfa 83,000 0.0125 63.6 0.318 1 0.76 0 0 

Other hay 4,500 0.0125 63.6 0.318 0.8 0.83 0 0 

Wheat 30,100 0.0125 63.6 0.318 0.6 0.77 0 0 

Barley 9,900 0.0125 63.6 0.318 0.6 0.77 0 0 

Corn 700 0.0125 63.6 0.318 0.6 0.77 0.44 0.051 

Potatoes 1,400 0.0125 63.6 0.318 0.8 0.70 0.6 0.085 

Sorghum 2,200 0.0125 63.6 0.318 0.6 0.77 0 0 

Other vegetables 16,072 0.0125 63.6 0.318 0.6 0.48 0.77 0.056 

Citrus 2,124 0.0125 63.6 0.318 0.6 0.48 0.77 0.056 

Application of the formula to develop annual PM10 emissions from active agricultural fields is 

achieved by multiplying crop type Es by the number of acres in each crop type. In addition to 

applying the USDA formula, a control factor of 72.28% (1 – 27.72%) was applied to active 

agricultural emission estimates to reflect the effectiveness of the agricultural BMP program. 

This control factor is a combination of the rule effectiveness of the BMP program (55.33%; see 

Appendix 3) and the estimated control effectiveness of the BMP program (50.10%)6, for an overall effectiveness of 27.72%. Emissions are allocated to the PM10 nonattainment area based upon 

the percentage (41.35%) of agricultural land use acres located with the nonattainment area. 

Summary of Pre-standardized Windblown Dust Emission Calculations 

To account for precipitation, pre-standardized emission estimates have been reduced by 10.66% 

(see section on Precipitation for more detail) for all land uses except active agricultural areas, as 

factor C in the USDA formula considers precipitation and the effects of soil moisture content. 

Annual pre-standardized PM10 emissions from active agricultural areas and all other land uses are 

listed in table A4–8 for Maricopa County and the PM10 nonattainment area. 

Table A4–8. Annual pre-standardized PM10 emissions from windblown dust in Maricopa County and the 

PM10 nonattainment area. 

Land use category 

Annual emissions (tons/yr) 

Maricopa County PM10 Nonattainment Area 

Active open space 3,191.63 2,660.86 

Agriculture – active 1,739.06 719.10 

Agriculture – inactive 16,711.81 3,686.87 

Auto test tracks 2,192.92 534.01 

Developing 5,897.93 4,863.19 

Landfill 78.76 78.76 

Mining 723.15 295.40 

Passive open space/wash 268,122.10 22,669.38 

Sand & gravel 1,511.72 1,341.04 

Vacant 283,176.99 23,037.24 

Totals: 582,326.11 59,885.85 

 

                                                           

6 Derived from Table 4-2 of the Technical Support Document for Quantification of Agricultural Best Management 

Practices, prepared for ADEQ by URS and ERG, June 2001. 
2008 Maricopa Co. PM10 Emission Inventory A4–19 June 2011

Standardized Windblown Dust Emissions 

Pre-standardized windblown dust emission calculations represent maximum windblown dust 

emission rates from land uses that have the capability to emit windblown dust. This is largely 

due to the fact that the vertical fluxes used to calculate pre-standardized emissions are based 

upon wind tunnel tests done in areas selected a priori as areas suspected of generating large 

quantities of windblown dust (Nickling and Gillies, 1989). These are areas that are mostly free 

of vegetation, have low surface roughness, and have surfaces that are either disturbed or easily 

disturbed. Only a small percentage of the land use categories assumed to emit windblown dust 

have characteristics identical to the wind tunnel test sites. Many areas have much denser 

vegetation, higher surface roughness values, topography that shelters the wind, higher surface 

moisture, desert pavement crusts, etc. For those areas disturbed by anthropogenic activities, the 

role of active controls (e.g., applying water) is not represented in the vertical fluxes. The vertical 

fluxes also do not take into account the supply-limited nature of desert soils in Maricopa County, 

because the wind tunnel tests were only performed for a period of 10 to 30 minutes at most 

(ibid). During a sustained high-wind event, some soils will stop emitting before the wind speeds 

fall below the threshold friction velocity because the available reservoir of dust particles has 

been exhausted due to the supply-limitations of the soil. Because these windblown dust-limiting 

variables are not represented in the wind tunnel tests, they need to be accounted for outside the 

vertical flux equations. To account for this on an annual basis, a sensitivity analysis was 

performed by comparing windblown PM10 emission estimates against observed PM10 

concentrations under high wind conditions. 

In 2008, there were eight MCAQD PM10 monitors that recorded PM10 concentrations and 

associated wind speed in 5-minute averages. A simple test to see the impact of PM10

concentrations under high winds is to compare the measured PM10 mass associated with wind 

speeds below 12 mph (threshold friction velocity for windblown dust generation) against the 

mass associated with wind speeds at 12 mph or greater. While PM10 concentrations are not an 

exact surrogate for emissions since high wind PM10 concentrations can be the result of long 

distance transport from upwind sources in some cases, on an annual basis they are a rough 

approximation of the sources and magnitude of PM10 emissions in the area around the 

monitoring site. Table A4–9 shows the percentage of PM10 mass associated with wind speeds at 

or above 12 mph for eight MCAQD monitors with 5-minute data. 

Table A4–9. Percentage of PM10 mass associated with wind speeds at or above 12 mph for eight MCAQD 

monitors in calendar year 2008. 

Monitor 

Sum of 5-min PM10 mass 

when 5-min winds ≥ 12mph 

(μg/m3

) 

Sum of all 5-min 

PM10 mass 

(μg/m3

) 

Percent PM10 mass 

associated with 5-min 

winds ≥ 12 mph 

Buckeye 646,732 4,596,071 14.07% 

Central Phoenix 96,398 2,014,492 4.79% 

Durango Complex 361,223 5,023,592 7.19% 

Greenwood 140,729 4,175,273 3.37% 

Higley 293,153 4,468,163 6.56% 

South Phoenix 204,019 4,753,036 4.29% 

West Phoenix 133,834 3,698,296 3.62% 

West Forty-Third 751,052 5,928,634 12.67% 

All Monitors 2,627,139 34,657,557 7.58% 
2008 Maricopa Co. PM10 Emission Inventory A4–20 June 2011

The analysis in Table A4–9 shows that as a weighted average, about 7.6% of annual PM10

emissions are associated with wind speeds greater than or equal to 12 mph. The monitors that 

are surrounded by land uses that are likely to produce windblown dust (e.g., Buckeye, West 

Forty-Third) have higher mass associated with winds ≥ 12 mph than do more urban monitors 

(e.g., Greenwood) where land uses have limited opportunity to produce windblown dust. A 

simple statistical analysis of the eight monitors produces a mean of about 7% and a standard 

deviation of 4%. Given that the monitors do not capture all emissions associated with high 

winds and that the limited numbers of monitors covering a large geographic area like Maricopa 

County do not represent all land use mixes, it is assumed that up to 10% (within one standard 

deviation of the monitor concentrations) of PM10 in an annual inventory of Maricopa County and 

the PM10 nonattainment area is windblown dust. 

Annual PM10 emissions from sources other than windblown dust total 61,282.27 tons for 

Maricopa County and 43,333.20 tons for the PM10 nonattainment area. If windblown dust 

emissions are to represent 10% of an annual inventory, than PM10 emissions for the 

nonattainment area and Maricopa County should be standardized to 4,814.80 tons and 6,809.13 

tons, respectively.7

Initial evaluation of the 10% standardized emission targets raises some questions. Despite the 

presence of significantly more acreage subject to windblown dust in the areas of Maricopa 

County outside the PM10 nonattainment area than within, the standardized emissions suggest that 

these areas emit at a lower rate than the PM10 nonattainment area. While this may seem counterintuitive at first, given the disparity between acreages, there are theoretical reasons why these 

areas would emit less. It is important to point out initially that when high magnitude dust events 

do occur (wind speeds above saltation thresholds) the areas outside of the nonattainment area are 

going to be the dominant contributor of windblown dust during the event. This is because as 

saltation occurs, supply-limitation concerns are less important, and the potential for long-range 

transport increases. However, these events are rare, occurring only a handful of times in a year; 

while the majority of windblown dust generated on an annual basis occurs during higher 

frequency/lower intensity wind speeds where supply-limitations control dust production. 

The following reasons therefore help to explain why the areas outside of the nonattainment area 

have greater supply-limitations (on an annual basis) during the more common lower magnitude/ 

higher frequency wind events, and thus lower dust emissions rates. First, the rates of soil 

disturbance are developed largely upon MCAQD inspections done only within the nonattainment 

area; it is very likely that areas outside the nonattainment area experience significantly fewer 

disturbances due to their isolation (e.g., Tonto National Forest, Goldwater Bombing Range). 

Second, vegetation in vacant areas outside the nonattainment area, both on the surface and just 

below the surface, is likely to be greater than vegetation existing on an area such as an urban 

vacant lot; this provides extra cohesion for the soil, limiting the reservoir of dust available to be 

entrained during a high wind event. Third, significantly large mountain ranges exist to the west 

and east of the nonattainment area, providing topographic protection from high winds and 

effectively funneling the winds to the valleys of the nonattainment area (Washington et al., 

2006). Fourth, a recently installed temporary (March 2010 – February 2011) PM10 monitor 

located near Arlington, Arizona (approximately twelve miles west of the nonattainment border) 

indicated that approximately 8% of PM10 concentration are associated with wind speeds ≥ 12 

mph. This is the only PM10 monitor that operated any significant distance outside the PM10

                                                           

7

 43,333.20 tons ÷ 90% = 48,148.00 tons; 61,282.27 ÷ 90% = 68,091.30 tons. 10% of each represents standardized 

windblown dust emissions. 
2008 Maricopa Co. PM10 Emission Inventory A4–21 June 2011

nonattainment area.8 As such, PM10 concentrations associated with high winds in other areas of 

Maricopa County outside the nonattainment area are assumed to be similar to the Arlington 

monitor given the lack of monitoring data available. Given these observations, it is not 

unreasonable to assume that on an annual basis, areas outside of the nonattainment area will emit 

windblown dust at lower rates than areas inside the nonattainment area. 

As a final note, it is critical to remember that an emissions inventory of windblown dust does not 

deal with the processes of transport and deposition. It seeks to quantify the amount of dust 

produced by the wind within a defined geographic area. Transport and deposition can consider 

sources of emissions hundreds or even thousands of miles away from the monitors during 

extreme high wind events (Prospero, 1999; VanCuren and Cahill, 2002). There are clearly 

sources of windblown dust immediately surrounding Maricopa County that will affect monitor 

concentrations during these high wind events. The purpose of air quality modeling is to combine 

all three stages of a dust event, particle entrainment, transport and deposition; while the purpose 

of this inventory is to quantify particle entrainment from sources within Maricopa County and 

the PM10 nonattainment area. 

Functionally, pre-standardized emissions are scaled down to the standardized target emissions in 

two steps to account for the different emissions rates between Maricopa County and the 

nonattainment area. The first step simply takes the pre-standardized emissions of the 

nonattainment area and adjusts them to match the target emissions of 4,814.80 tons. This results 

in a uniform 91.96% reduction of the emissions in all land use categories. The second step 

assumes that the balance of emissions between the nonattainment area and the county 

standardized emission targets, 1,994.33 tons9

, originates in the “donut” area of Maricopa County 

outside the nonattainment area. Pre-standardized emissions from this “donut” area of the county 

were calculated using GIS and the methods described in previous sections; then standardized to 

the target of 1,994.33 tons, a 99.62% reduction of pre-standardized emissions. 

Summary of Standardized Windblown Dust Emissions 

Using the emission methodologies listed above, annual, standardized PM10 emissions for 

Maricopa County and the PM10 nonattainment area are calculated. PM2.5 emissions are assumed 

to be 15% of PM10 emissions (WGA, 2006). Daily emissions are obtained by dividing annual 

emissions by the number of days in calendar year 2008 (366). Annual and daily standardized 

emissions for Maricopa County and the PM10 nonattainment area are shown in Tables A4–10 and 

A4–11, respectively. 

                                                           

8

 The Buckeye monitor is also located outside the nonattainment area, however at only a distance of 0.75 miles from 

the western border. In 2008 the Buckeye monitor had 14% of PM10 mass associated with wind speeds ≥ 12 mph, 

suggesting that the rural areas of Maricopa County outside of the nonattainment area may have more of their PM10

concentrations associated with high winds. However, when high wind PM10 concentrations of the Buckeye monitor 

are compared to the same time period of the temporary Arlington monitor (March 2010 – February 2011), the high 

wind percentage is reported to be approximately 7% of the PM10 mass, which is similar to the percentage reported 

by the Arlington monitor (8%). 

9

 County standardized emission target of 6,809.13 tons – nonattainment area target of 4,814.80 tons = 1,994.33 tons. 
2008 Maricopa Co. PM10 Emission Inventory A4–22 June 2011

Table A4–10. Standardized, annual and daily PM10 and PM2.5 emissions from windblown dust in the 

Maricopa County, by land use category. 

Land use category 

Annual emissions (tons/yr) Average daily emissions (lbs/day)

PM10 PM2.5 PM10 PM2.5

Active open space 215.94 32.39 1,180.0 177.0 

Agriculture – active 61.69 9.25 337.1 50.6 

Agriculture – inactive 345.86 51.88 1,890.1 283.5 

Auto test tracks 49.23 7.38 269.0 40.4 

Developing 394.98 59.25 2,158.4 323.8 

Landfill 6.33 0.95 34.6 5.2 

Mining 25.37 3.81 138.7 20.8 

Passive open space/wash 2,755.11 413.27 15,058.1 2,258.7 

Sand & gravel 108.47 16.27 592.7 88.9 

Vacant 2,846.15 426.92 15,555.8 2,333.4 

Totals: 6,809.13 1,021.37 37,214.6 5,582.2 

Table A4–11. Standardized, annual and daily PM10 and PM2.5 emissions from windblown dust in the PM10 

nonattainment area, by land use category. 

Land use category 

Annual emissions (tons/yr) Average daily emissions (lbs/day)

PM10 PM2.5 PM10 PM2.5

Active open space 213.93 32.09 1,169.0 175.4 

Agriculture – active 57.82 8.67 315.9 47.4 

Agriculture – inactive 296.42 44.46 1,619.8 243.0 

Auto test tracks 42.93 6.44 234.6 35.2 

Developing 391.00 58.65 2,136.6 320.5 

Landfill 6.33 0.95 34.6 5.2 

Mining 23.75 3.56 129.8 19.5 

Passive open space/wash 1,822.61 273.39 9,959.6 1,493.9 

Sand & gravel 107.82 16.17 589.2 88.4 

Vacant 1,852.19 277.83 10,121.2 1,518.2 

Totals: 4,814.80 722.22 26,310.4 3,946.6 

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entrainment of dust by wind. J. Geophys. Res., 98, 12719–12726 

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2008 Maricopa Co. PM10 Emission Inventory A4–25 June 2011

Attachment I 

MAG 2009 GIS Existing Land Use Database Information 

 
2008 Maricopa Co. PM10 Emission Inventory A4–26 June 2011

The following attachment exists in draft form, as the land use database is 

continually updated to reflect new source data and GIS methodologies. The 

draft as presented here was created on November 16, 2010. 

Database Information 

Database Name

EXISTING_LAND_USE_2009 

Common Names

Existing Land Use, 2009 

EXLU, 2009 

Description

The Existing Land Use (EXLU) dataset was created as a joint effort of MAG and MAG 

member agency staff. This dataset serves as a land use inventory and is used for a variety 

of planning purposes including socioeconomic forecasting and air quality modeling. 

This database has three components:

1. MAG parcels: Serves as the primary element of the land use inventory. The parcel 

base integrates Maricopa County Assessor's office (MCA) parcels, Arizona State 

Land Department (ASLD) land surface ownership and Bureau of Land Management 

(BLM) designated wilderness areas. Additional supplementary parcels have been 

created for areas not covered by the other datasets (e.g. within Tribal Lands) based 

on air photo interpretation and previous EXLU inventories. MCA parcels within the 

dataset have been modified in some cases to support data requirements for 

modeling efforts. In particular, groups of related or associated MCA parcels are often 

aggregated based on a MCA designated Economic Unit or Assessor Subdivision 

(MCRNUM). However, the majority of parcels retain the original geometry provided 

by the MCA. All parcels are assigned a detailed MAG land use code and can be 

related to original MCA parcels via a lookup table. 

2. Land use overlays: Overrides the parcel base for cases in which the MCA parcels 

do not adequately distinguish changes in land use. Examples of this include areas 

encompassing public facilities and institutions, areas adjacent to water courses and 

major transportation corridors. 

3. Generalized EXLU: Provides a generalized and contiguous representation of the 

land use inventory. Derived by integrating the MAG parcel based with the land use 

overlays and applying a series of GIS-based generalization procedures. The finest 

level of categorical detail provided is the MAG ‘Long Display Code’. 

Frequency of Update

Updates are made to this dataset on an annual basis. 
2008 Maricopa Co. PM10 Emission Inventory A4–27 June 2011

Format

ArcSDE geodatabase feature classes 

Projection

Coordinate System = State Plane 

Zone = 3176 (Arizona Central) 

Horizontal Datum = NAD83 HARN 

Linear units = international feet 

Data Sources

1. Maricopa County Assessor Office Parcels, February 2009 

2. Maricopa County Assessor’s Office Subdivisions, February 2009 

3. Maricopa County Assessor’s Office Secured Master File, February 2009 

4. Maricopa County Assessor’s Office Residential Master File, February 2009 

5. Maricopa County Assessor’s Office Commercial Master File, February 2009 

6. Arizona State Land Department Land surface management 

7. Arizona State Land Department Arizona Preserve Initiative lands 

8. Arizona State Land Department Wilderness areas 

9. Salt River Project canals 

10. Central Arizona Project canals 

11. MAG aerial imagery, 2009 (procured from Aerials Express) 

12. MAG Existing Land Use, 2004 

13. MAG Employer Database, 2008 

14. MAG Residential Completions 

15. Maricopa County Elections Department Streets 

16. Kammrath property databases 

Reference

MAG Land Use Codes 

See Appendix A. 

Assessor Property Use Codes 

See http://www.maricopa.gov/assessor/gis/pdf/puc.pdf. 
2008 Maricopa Co. PM10 Emission Inventory A4–28 June 2011

Database Standards and Structure 

Naming Conventions and Update Schedule

The naming convention for the Existing Land Use feature class is as follows: 

EXISTING_LAND_USE_20xx 

Where xx represents the two digit year 

File Location

The final version of this dataset is in an ArcSDE geodatabase. This includes the following 

feature classes: 

- MAG_PARCELS: the detailed MAG parcel base 

- EXLU_POLYGONS: the generalized EXLU 

- CANALS_ROW: land use overlay for canals and surrounding areas 

- PARCEL_ADJUNCTS: used to split or override parcel geometries 

- FREEWAYS_ROW: land use overlay for freeways and surrounding areas 

- PARKS: land use overlay for areas of significant active open space areas 

- RAIL_ROW: land use overlay for railroads and surrounding areas 

- WATER_COURSES: land use overlay for significant water areas such as residential 

lakes and stream beds 

Update Schedule

Updates will be performed on this dataset on an annual basis. New secured data are 

released by the Assessor’s Office in September of each year. Following acquisition of this 

data from the Assessor’s Office, an incremental update to the Existing Land Use dataset will 

be undertaken. 

Versioning

The Existing Land Use dataset is actively maintained on the giswork instance of ArcSDE. 

Editors create child versions of the database from the QA/QC version and perform all edits 

against the child version. Edits are reconciled and posted to the QA/QC version from the 

editor’s child version. Edits are checked for completeness and correctness, and are then 

posted to the DEFAULT version on giswork. 

At the end of each quarter, or on an as needed basis, the Existing Land Use data are 

replicated to the production database, gismag. The replicated feature class on the gismag
2008 Maricopa Co. PM10 Emission Inventory A4–29 June 2011

instance is renamed with the naming convention described below. The fourth quarter 

iteration represents the final iteration for a calendar year. 

Topological Relationships

None 

Database Structure

 

Attributes of the generalized EXLU feature class are: 

 

Field Description Format Instance 

OBJECTID 

ESRI geodatabase unique 

identifier ObjectID giswork 

LONG_DISPLAY_CODE 

MAG generalized land use 

class Text giswork 

ACRES Area of the polygon Double giswork 

MPA MPA the polygon is within Text giswork 

Shape ESRI feature geometry Geometry giswork 

Dependencies

1. Tabular data maintained in the form of the Parcel Information Table, Residential 

Information Table, and Non-Residential Information Table. These datasets provides 

input to the AZSMART model. These tables are a modified version of the Secured 

Master, Residential Master, and Commercial Master files acquired from the Maricopa 

County Assessor’s Office. Work done to the existing land use dataset that modifies the 

land use also forces an update of the Parcel Information Table, Residential Information 

Table, and Non-Residential Information Table. 

2. A feature class called MAG Parcels was constructed to serve as the basis for an Existing 

Land Use feature class. A MAG Parcel Number (MPN) was assigned to each feature in 

the dataset. In most cases the MPA is identical to the APN. In some cases, however, it 

was necessary to aggregate parcels together based on a shared Economic Unit (this 

was the case with large shopping centers and some buildings). The MPN, then, was 

edited to reflect this change. In these cases, the MPN was changed to reflect the 

Economic Unit value shared by the original parcels. 
2008 Maricopa Co. PM10 Emission Inventory A4–30 June 2011

Database Creation 

Summary

 Data are collected from various sources as outlined in this document. 

 Assign a MAG Parcel Number (MPN) to each parcel. 

 Merge parcels that fall within a single economic unit, as defined by the Maricopa County 

Assessor’s Office. MPN is updated to reflect value of economic unit. 

 Assign a property use code to the MAG Parcels by joining with the Secured Master File. 

 Assign MAG land use codes based on a lookup table between property use codes and 

MAG land use codes. 

 Locate parcels with null property uses are located and assigned a property use code and 

MAG land use code. 

 Identify single family residential (SFR) land uses. Determine density of SFR parcels and 

assign a MAG land use code to these parcels. 

 Identify parcels associated with airports, proving grounds, and public facilities and 

reviewed for assignment of correct MAG land use code. 

 Compare MAG Parcels to Kammrath property databases. 

 Visually inspect MAG Parcels with the aid of contextual datasets such as MAG aerial 

imagery, MAG employers database, and MAG residential completions database; 

recoding erroneous land uses. 

 Construct Existing Land Use dataset for review by MAG member agencies. 

 Incorporate comments from member agencies to Existing Land Use Parcels 

 Construct final Existing Land Use dataset. 

Ancillary Tables or Databases

MCA_MAG_LU_LOOKUP – a lookup table between Assessor property use codes and MAG 

land use codes. 

APN_MPN_LOOKUP – a lookup table that maps MPN to APN 

MAG_LU_CODES – a lookup table that provides additional information about the MAG land 

use codes and maps detailed land use codes to simple land use codes 

Preliminary Steps

Data was collected from the Maricopa County Assessor’s Office and the Arizona State Land 

Department. These datasets were loaded into the Enterprise geodatabase. A separate 

database for MAG Parcels was created. The purpose of the MAG parcel database was to 

aggregate parcels with shared economic units, thus aggregating multiple parcels into logical 

whole units. A MAG Parcel Number (MPN) was then assigned to each parcel remaining. 

For the majority of parcels, the MPN is the same as the APN. For parcels that were merged 

based on similar economic units, a new MPN was created. Following this, each parcel and 

property use file was checked for records with duplicate MPNs. The resulting MPN is the 

shared economic unit of the merged parcels or the MCR Number of the subdivision 

depending on if the percent ownership file is less than 100 in the Commercial Master File. 

The latter case was used in cases where an economic unit did not exist (i.e. condominiums) 

or where multiple economic units functioned as a logical whole. 
2008 Maricopa Co. PM10 Emission Inventory A4–31 June 2011

Editing Steps

Initial Feature Class Construction 

For each parcel and property use file, a field called FILE was added. This field was used 

calculate to the source of the parcels (e.g. ME for Mesa). The purpose of this was to 

provide a lineage back to the source file. Following this, all parcel files were merged into 

a single feature class, retaining the FILE, MPN, and shape fields. A new column, KEY, 

was added and calculated to the value of FILE + “ “ + MPN. The KEY field provides a 

unique identifier for cases in which MPN values exist in multiple files. Parcel property 

use tables were also merged into a single file, retaining the MPN and PROPERTY_USE 

fields. A similar KEY field was added to the property use table. 

A PROPERTY_USE field was then added to the parcels feature class. The feature class 

and the property use table were then joined based on the KEY field and the 

PROPERTY_USE in the feature class was calculated based on the property use value in 

the joined table. 

PROP_USE_COMMENT, REVIEW_PROP_USE, and MAG_LU fields were added to the 

feature class. PROP_USE_COMMENT was intended to detail problems or other 

information about property use codes. REVISE_PROP_USE stored changes made to 

the PROPERTY_USE field. Finally, MAG_LU stored the subsequent MAG land use 

code based on the MCA_MAG_LU lookup table. 

Next, duplicate MPNs (most likely existing at the edges of merged regions) were 

dropped from the feature class. For parcels to be dropped, the REVISE_PROP_USE 

was set to -9999 and annotated using the PROP_USE_COMMENT field. 

Addressing Null Property Uses 

Next, null property uses were located in the feature class. Null property uses arose from 

one of two reasons: the parcel/MPN did not have a corresponding record in the property 

use table or the property use was null in the secured master file acquired from the 

Assessor’s Office. This condition most likely arose due to the parcels and secured files 

being out of sync with one another, the secured files being more current than the 

parcels. Null values were reconciled by querying the Assessor’s Office website. A script 

was written to scrape property uses from the Assessor’s website. Most of the null values 

were resolved in this way, while the remainders were fixed manually. 

Assigning densities to single family uses 

When the ‘default’ MAG land use classes are assigned based on the MCA property use 

code, all single family residential (SFR) parcels are assigned a single class (e.g. 100). 

This class needs to be refined to provide additional detail about the density of the SFR 

parcel. Multiple definitions and approaches may be used to classify the SFR densities. 

The approach employed here is based on the assumption that (a.) MCA subdivisions 

provide a logical grouping of parcels within which to assess density since the subdivision 

boundaries likely reflect the original intents of the development and (b.) that SFR parcels 

falling outside of subdivisions may be grouped according to neighboring SFR parcels 

that are not separated by other land uses. This entails the following: 

 
2008 Maricopa Co. PM10 Emission Inventory A4–32 June 2011

1. Assign each parcel to the subdivision it falls within: 

a. Obtain centroids for the parcel 

b. Perform a spatial join in which each parcel centroid is assigned to the 

subdivision it falls within 

c. Perform an attribute join (based on MPN) between the parcel polygons and 

their corresponding centroids to assign the subdivision to the parcel 

polygons. For parcel polygons falling outside of a centroid this value will be 

NULL 

2. For SFR parcels falling outside a MCA subdivision, assign a pseudo subdivision 

based on a contiguous set of SFR parcels it falls within: 

a. Select a subset of SFR parcel polygons with NULL subdivisions 

b. Dissolve these parcels to obtain contiguous blocks: these blocks are pseudo 

subdivisions 

c. Assign a unique identity to each pseudo subdivision. The identity is assigned 

by concatenating the character ‘b’ with the OBJECTID of the pseudo 

subdivision 

d. Obtain centroids for the parcels identified in 2a. 

e. Perform a spatial join in which each centroid from 2b is assigned to the 

pseudo subdivision it falls within 

f. Perform an attribute join between the centroids resulting from 2e with the 

parcel polygons from 2b. Assign each parcel’s subdivision field the values of 

the pseudo subdivision id of its corresponding centroid. 

3. Assign a refined SFR land use based on the total number of units and the total 

number of SFR acres in its subdivision or pseudo subdivision. 

a. If it does not already exist, add a field called ACRES and use the Calculate 

Geometry tool to assign area in acres for each parcel 

b. Get a subset of SFR parcels 

c. Dissolve parcels on the subdivision field; retain the sum of ACRES field 

d. Join the parcels from 3b with the dissolved attribute table from 3c 

e. Use the following VBA code block to assign a density based SFR land use 

class to the parcels: 

d = sumSubdivision Units/ sumSubdivisionAcres 

if d <= 0.2 then 

 lu = 110 

elseif d > 0.2 and d <= 1 then 

 lu = 120 

elseif d > 1 and d <= 2 then 

 lu = 130 

elseif d > 2 and d <= 4 then 

 lu = 140 

elseif d > 4 and d <= 6 then 

 lu = 150 

elseif d > 6 then 

 lu = 160 

end if 

Initial and Automated Land Use Checks 

Areas in and around airports were checked. Parcels comprising the regional airports 

were flagged and recoded to an airport property use and MAG land use code. In most 
2008 Maricopa Co. PM10 Emission Inventory A4–33 June 2011

cases, the parcel configurations closely resembled the actual airport boundaries were 

kept as-is. However, overlays needed to be created for Sky Harbor, Buckeye, Gila 

Bend, and Pleasant Valley airports whose boundaries are distinctly different from the 

parcel boundaries. 

Proving ground areas were also examined in detail. These areas typically consist of 

very large parcels that end up being coded as “industrial.” This tends to skew the 

acreage of industrial land in the county. These large parcels were sought out and 

recoded. Several landfills were also captured in this process. 

Parcels representing large public facilities, prisons and jails, city halls, community 

centers, and religious institutions were also checked using aerial imagery, Google Street 

View, employer points, 2004 existing land use, and the values of neighboring parcels. 

Kammrath property databases were also used during this process to check correctness 

of MAG land use code assignment. Property types addressed by this check were 

apartment complexes, mobile home and RV parks, and industrial parks in which the 

classification on warehousing versus light industrial use was not clear. 

City by City Review 

Having resolved a number of issues out of the gate, the next step was to perform a city 

by city review of the parcels. This was accomplished by the use of a tracking grid based 

on the PLSS to avoid duplication of effort. MAG GIS staff reviewed each city individually 

for assumed correctness of land use coding, to recode land uses or flag for exclusion 

sliver parcels. Parcels in which the land use was in question were primarily reviewed 

using aerial imagery, however the MAG employer database and MAG residential 

completions database were also used to provide supplementary information about the 

types of activities, and hence potential uses, taking place on individual parcels. 

Overlay feature classes were also edited during this time. Since the underlying 

assumption in this editing process was that parcels could not be modified because they 

had to be tied back to an original parcel base for change tracking, overlays were used to 

approximate splits. For example, in many cases near water courses, property lines are 

not coincident with natural land use breaks. A parcel whose primary land use is 

agricultural may extend into the river bottom. The portion of the parcel in the river 

bottom is not agricultural, therefore a polygon is added to an overlay feature class 

representing that portion of the parcel that is in the river bottom and coded as “passive 

open space.” Layers used for this purpose include cultural features, freeway right-ofways, railroad right-of-ways, parks, canals, and water courses and lakes. 

Rules observed during the city by city review were: 

1. As a general rule, parcel geometries were not changed. Significant non-road void 

areas were filled to account for public lands and State Trust not otherwise present in 

the Assessor’s data. 

2. Developing residential parcels should be “parcelized” or broken into groups of 

parcels that look like a residential development. If this is not the case, these are 

recoded as vacant. 

3. Developing residential and commercial parcels were generally recoded as vacant, 

unless it was demonstrable through review of aerial photos that the parcel in 

question was indeed developing. 
2008 Maricopa Co. PM10 Emission Inventory A4–34 June 2011

4. Residential parcels that appeared to be connected with another already developed 

residential parcel were coded to match their associated parcel and flagged as 

“AZSMART EXCLUDE.” The purpose of including this flag was so as not to change 

the total number of residential parcels. 

5. Very small public facilities were excluded. 

6. River bottoms and floodways are coded as Passive Open Space unless some other 

land use was evident. In most cases, this other land use would be sand and gravel 

operations. 

7. For mobile homes or trailers sitting on large lots, as opposed to within mobile 

home/RV parks, the parcel was coded to match the adjacent residential parcels. 

8. Parking lots and parking structures were coded to match adjacent commercial or 

office parcels if the parking feature was visibly associated with another parcel. 

Some edits were made to the underlying parcels during this review. The Assessor’s 

Parcels cover only those areas not occupied by State Trust or Federal public lands, 

including National Forests, BLM public lands, and Bureau of Reclamation sites. These 

were added as features to the Existing Land Use Parcels. These are identifiable by their 

lack of an MPN and being flagged in the comments field as being BLM, Bureau of 

Reclamation, Forest Service, Military or State Trust. 

Once a MAG staff member had completed a review of a city, the MAG GIS Program 

Manager reviewed the city a second time to ensure consistency among editors and 

across cities. 

Construction of Existing Land Use Feature Classes for Member Agency Review 

Following these initial activities, the generalized existing land use for an individual city 

was constructed. Land use blocks were first generated using a selected subset of 

parcels (i.e. those parcels not flagged for exclusion). These were clipped to the MPA 

boundary of the individual city in question. The resulting clipped blocks were joined with 

a lookup table to assign generalized long display codes. The blocks were then dissolved 

on the long display code. 

Next, land use blocks were integrated with Assessor Subdivisions. The intent in this 

operation was to identify subdivisions with homogenous residential land use and to 

remove most of the neighborhood active open space land use. These land uses were 

problematic because they tend to form long, continuous landscaping parcels that, in 

many cases, encircle a subdivision. These also include neighborhood parks of all sizes. 

Some parks were necessary to maintain because of their size, and the geometry of 

these were copied into the parks overlay. 

The integration proceeded by first dividing the contiguous land use blocks into two sets: 

those contained within subdivisions and those falling outside of subdivisions. This was 

achieved by performing a union between the subdivisions and the land use blocks and 

then selected out the results based on the combinations of resulting values (more 

specifically, the FID values). Next, areas within subdivisions were further divided into 

areas within homogenous subdivisions and those falling within heterogeneous 

subdivisions. This classification was obtained by grouping the areas by subdivision (via 

the ‘Summarize’ tool in ArcGIS) and identifying those subdivisions that had a single long 

display code value. A minimum area threshold was also specified to eliminate slivers 

that are artifacts of the union process. Areas within homogenous subdivisions were 

replaced with a subdivision boundary. Areas within heterogeneous subdivisions were 

then independently fed into a cost allocation algorithm that assigned that land use at a 

given location based on the land use it was closest to (here distance was based on 
2008 Maricopa Co. PM10 Emission Inventory A4–35 June 2011

impedance rather than Euclidean distance). Following this, the land use outside of 

subdivisions, the homogenous subdivision boundaries and the results of the cost 

allocation algorithms were merged into a single dataset. The resulting dataset was then 

fed into another cost allocation to fill in the voids for areas falling outside of subdivisions. 

The final step in this process was to integrate overlays via successive erases and 

merges. This began by integrating all the overlays into a single feature class. The 

overlays were integrated in the following order: 

1. Open space 

2. Parks 

3. Water courses 

4. Canal rows 

5. Railroad rows 

6. Freeways 

7. Cultural adjuncts 

Finally, the resulting integrated overlay feature class was combined with results of the 

final cost allocation. This was achieved by erasing the overlay areas from the allocated 

feature class and then merging the results of the erase with the integrated overlay class. 

Database Update 

Ancillary Tables or Databases

Parcels and secured master files from the previous year are used as a point of comparison 

with new data collected from the Assessor’s Office. 

MCA_MAG_LU_LOOKUP – a lookup table between Assessor property use codes and MAG 

land use codes 

APN_MPN_LOOKUP – a lookup table that maps MPN to APN 

MAG_LU_CODES – a lookup table that provides additional information about the MAG land 

use codes and maps detailed land use codes to simple land use codes 

Preliminary Steps

Data is collected from the Maricopa County Assessor’s Office and the Arizona State Land 

Department. These datasets are loaded into the Enterprise geodatabase. 

Preparatory Steps

A determination of the extent of changes between data vintages is made. For the Land 

Department data, the changes will tend to be small. The likely impact of these changes will 

be removal of State Trust land into private ownership or to another government entity, the 

end result of either case being that Assessor parcels will be created from the transfer of 

ownership. For the Assessor data, the change will be more substantial and will include: 

1. Parcels that have been retired through splits or merges 

2. Parcels that have been added due to splits from a parent parcel or transfer from State or 

Federal ownership 
2008 Maricopa Co. PM10 Emission Inventory A4–36 June 2011

3. Parcels that have new property uses assigned to them 

These changes may be identified by comparing the APNs and property use codes among 

the parcels in the current year with those in the previous year. This can be handled via SQL 

queries: 

Births 

select * from dataloader.PARCELS_2010 

where APN not in ( 

select APN from dataloader.PARCELS_2009 

) 

Retirements/deaths 

select * from dataloader.PARCELS_2009 

where APN not in ( 

Select APN from dataloader.PARCELS_2010 

) 

Transitions/changes 

select a.APN, a.MAG_LU as MAG_LU_2010, b.MAG_LU as MAG_LU_2009 

from ( 

select a.APN, b.PropertyUseCode, c.MAG_Lucode as MAG_LU 

from dataloader.PARCELS_2010 a 

inner join dataloader.SECURED_MASTER_2010 b 

on a.APN = b.APN 

inner join GISWORK.dataloader.MCA_MAG_LU_LOOKUP c 

on b.PropertyUseCode = c.Property_Use_code 

) a 

inner join( 

select a.APN, b.PropertyUseCode, c.MAG_Lucode as MAG_LU 

from dataloader.PARCELS_2009 a 

inner join dataloader.SECURED_MASTER_2009 b 

on a.APN = b.APN 

inner join GISWORK.dataloader.MCA_MAG_LU_LOOKUP c 

on b.PropertyUseCode = c.Property_Use_code 

) b 

on a.APN = b.APN 

where a.MAG_LU <> b.MAG_LU 

MAG Parcels Update Process

1. For all parcels that have not changed, (i.e. they have the same property use code and 

their APN exists in both years) assign the MAG_LU based on the previous year 

2. For parcels that have changed (i.e. their property use codes have changed) assign 

MAG_LU based on the default value provided in the MCA_MAG_LU_LOOKUP. 

3. Re-build MAG Parcels for the parcels that have not changed. Note: this step is only 

necessary if the parcel geometries have shifted, otherwise the MAG Parcels from the 
2008 Maricopa Co. PM10 Emission Inventory A4–37 June 2011

previous year can be used. 

4. For all deaths/retiree parcels identify any MAG Parcels that will also need to be retired. It 

may also be necessary to identify related parcels that may or may not also be retired 

(e.g. a single parcel is retired but other parcels in the Economic Unit or subdivision 

remain unchanged). 

5. Identify parcel births that will need to be aggregated to create new Existing Land Use 

Parcels: 

select a.APN, count(*) as NUM_IMPROVEMENTS from ( 

select APN 

from dataloader.PARCELS_2010 

where APN not in ( 

select APN from dataloader.PARCELS_2009 

) 

) a 

inner join dataloader.COMMERCIAL_MASTER_2010 b 

on a.APN = b.APN 

where LTRIM(RTRIM(b.PercentOfOwnership)) <> '100' 

group by a.APN 

order by count(*) desc 

6. Re-assign single family residential densities for parcel births and surrounding areas. 

Generalized Existing Land Use Update Process

Determine if the parcels have shifted across years. If the parcels have shifted, re-build the 

generalized land use for the entire dataset per the process discussed for the initial 

construction. If the parcels have not shifted, identify regions surrounding births and 

transitions. These neighborhoods may simply involve generating minimum bounding 

rectangles (MBRs) or may be more complicated using something like a Voronoi diagram. 

Finally, re-build the generalized EXLU for each of the identified change regions. 

Reporting

Report the number of changes that will be made to the database. This might include: the 

number of parcel births, deaths and transitions. Also, report the number of MAG Parcels that 

will consequently be retired or updated. It may also be worthwhile to report the types of 

transitions that are occurring, as well as the dominant land uses of the births and deaths. 

For example, to report the types of land use transitions occurring: 

select cast(b.MAG_LU as int) as MAG_LU_2009, cast(a.MAG_LU as 

int) as MAG_LU_2010, count(*) as Parcel_Count from ( 

select a.APN, b.PropertyUseCode, c.MAG_Lucode as MAG_LU from 

dataloader.PARCELS_2010 a inner join 

dataloader.SECURED_MASTER_2010 b 
2008 Maricopa Co. PM10 Emission Inventory A4–38 June 2011

on a.APN = b.APN 

inner join GISWORK.dataloader.MCA_MAG_LU_LOOKUP c 

on b.PropertyUseCode = c.Property_Use_code 

) a 

inner join ( 

select a.APN, b.PropertyUseCode, c.MAG_Lucode as MAG_LU from 

dataloader.PARCELS_2009 a inner join 

dataloader.SECURED_MASTER_2009 b 

on a.APN = b.APN 

inner join GISWORK.dataloader.MCA_MAG_LU_LOOKUP c 

on b.PropertyUseCode = c.Property_Use_code 

) b 

on a.APN = b.APN 

where a.MAG_LU <> b.MAG_LU 

group by a.MAG_LU, b.MAG_LU 

order by count(*) desc, a.MAG_LU asc, b.MAG_LU asc 

This will return the following: 

 

2009 land use 2010 land use Parcel count 

910 100 6902

750 910 2567

910 710 1397

910 750 1310

900 910 1194

910 170 980

910 900 523

100 170 468

900 750 404

100 910 376

... ... ... 

Review Process 

Internal Review

Preliminary Steps

Perform the steps in the previous section. The resulting data should be in a versioned 

SDE database. 

Review Steps

1. Perform QA/QC on births with “problematic” property use codes. For example most 

single family parcels will be fine, but parcels with a Property Use Code of 9000 will 

require additional review. 

2. Examine problematic land use transitions. For example a transition from 910 (developing 

residential) to 100 (single family residential) is a reasonable transition. However, a 

transition, such as from 110 to 552 (public services), likely represents a problem in one 

of the base datasets and bears further investigation. 

3. Generate acreages for all medium-level land use classes and compared against the 

previous existing land use acreages to determine if an error has occurred. The changes 
2008 Maricopa Co. PM10 Emission Inventory A4–39 June 2011

between vintages should not be significant. Substantial changes in one land use class 

between vintages will be indicative of a problem in one of the underlying datasets, and 

will force a review of that land use class in the new data. 

4. Perform point-in-polygon analysis between geocoded Kammrath data or other similar 

dataset and the MAG parcels. Check for parcels that contain points with incompatible 

uses (e.g. industrial point falling on a retail parcel) and make appropriate corrections as 

warranted with a secondary examination of aerial imagery for the area of interest. 

Reporting

Report changes in acreages across the two years for the detailed MAG land use codes. 

Generate ‘change maps’ to highlight spatial trends in the land use transitions. Generate 

a semi-detailed report and dataset for the Air Quality division and Maricopa County using 

a course land use classification. The semi-detailed dataset contains parcel boundaries 

dissolved using the course classification and has overlays integrated but remaining voids 

are left alone and treated as ‘Transportation’ uses. 

Member Agency Review

Preliminary Steps

The existing land use dataset is sent to members of the MAG POPTAC and GIS 

professionals who have been identified as key GIS contacts within the member 

agencies. A tracking database that includes a list of recipients and status of review 

material delivery and responses should be completed prior to sending any data out for 

review. It is also preferable to let members of the POPTAC know to expect the review 

materials within a certain period of time. This is best accomplished at a monthly MAG 

POPTAC meeting. 

Review Steps

Notify members of the POPTAC that the existing land use dataset will be provided to 

them immediately. Members of the POPTAC will receive the low-detail dataset as a file 

geodatabase of their or as a paper map of their MPA, a summary table of existing land 

use classifications within their MPA at the low-detail level, and a lookup table of APN to 

MAG land use codes at the high-detail level. Data and maps will be mailed to members 

of the POPTAC. Members of the POPTAC will be instructed that they should provide 

feedback to MAG within six weeks. Feedback may be provided by individuals receiving 

paper maps may mark up the maps with any corrections or by individuals receiving 

geospatial data may provide a polygon feature class of recommended changes. 

Comments received from member agencies shall be incorporated into the Existing Land 

Use as quickly as possible. 

Reporting

Notify Members of the POPTAC that a final version of existing land use exists and that 

they will be provided with the dataset upon request. 
2008 Maricopa Co. PM10 Emission Inventory A4–40 June 2011

Final Output 

Metadata Update

Export the metadata from the current version of the Existing Land Use feature class to a 

local directory. This can then be imported to serve as the new feature class’s metadata. 

Metadata fields that will then need to be updated are the citation name, publication date, 

and last update fields. Any additional changes to the feature class should be noted in the 

metadata at this time. 

Export for Distribution

Export the current year’s Existing Land Use feature classes from the data instance to 

I:\data\distribution\exlu. The frequency of export from ArcSDE is dependent on the 

frequency of replication from the work instance to the data instance. 

Reporting

Report changes in acreages across the two years for the detailed MAG land use codes. 

Generate ‘change maps’ to highlight spatial trends in the land use transitions. It may also 

be worthwhile to generate ArcGIS server sites to deliver results and support land use 

queries. 
2008 Maricopa Co. PM10 Emission Inventory A4–41 June 2011

Appendix A 

MAG Land Use Codes

LUCODE Land Use - Detailed Land Use Description 

110 Rural Residential <= 1/5 du per acre (SF) 

120 Estate Residential 1/5 du per acre to 1 du per acre (SF) 

130 Large Lot Residential (SF) 1 du per acre to 2 du per acre (SF) 

140 Medium Lot Residential (SF) 2-4 du per acre (SF) 

150 Small Lot Residential (SF) 4-6 du per acre (SF) 

160 Very Small Lot Residential (SF) >6 du per acre (SF) 

161 

Very Small Lot Residential (SF-Mobile 

Homes) 

Mobile home parks/RV Parks (>6 du 

per acre) 

170 Medium Density Residential (MF) 5-10 du per acre (MF) 

180 High Density Residential (MF) 10-15 du per acre (MF) 

190 Very High Density Residential (MF) 15-50 DU/AC Residential (MF) 

191 High Rise Residential >50 DU/AC (MF) 

210 Low Density Commercial 

Movie Theatres, Skating Rinks, 

Amusement Facilities 

220 Greenhouse Commercial Nurseries, Greenhouses 

230 Specialty Commercial <=50,000 square feet 

240 Neighborhood Commercial 50,000 to 100,000 square feet 

250 Community Commercial 100,000 to 500,000 square feet 

260 Regional Commercial 500,000 to 1,000,000 square feet 

270 Super-Regional Commercial >= 1,000,000 square feet 

310 Storage Facilities Storage Facilities 

320 Warehouse Warehouse/Distribution Centers 

330 Light Industrial Laboratory/Back Office 

340 Heavy Industrial Manufacturing 

410 Office Low Rise 1-4 stories 

420 Office Mid Rise 5-12 stories 

430 Office High Rise 13 stories or more 
2008 Maricopa Co. PM10 Emission Inventory A4–42 June 2011

510 Motels/Hotels Motels/Hotels 

511 Resorts Resorts 

520 Educational 

Educational institutions where no detail 

available 

521 Preschool/Daycare facilities Preschool/Daycare facilities 

522 Schools (K-12 grade) Schools 

523 Post High School Institutions 

Including public and private colleges 

and technical training institutions 

524 Arizona State University ASU Main and Extended Campuses 

525 Dormitories 

Dormitories associated with educational 

institutions 

530 Institutional 

Institutions where no details are 

available 

531 Religious Institutions Churches/Religious Institutions 

532 Medical Offices Medical Offices 

533 Hospitals/Medical Centers Hospitals/Medical Centers 

534 Nursing Homes/Assited Care Facilities 

Nursing Homes/Assited Care Facilites 

(Group Quarter) 

540 Cemeteries 

Cemeteries, Mausoleums, 

Crematoriums 

551 Public Offices Includes city halls 

552 Public Services 

Includes community centers, libraries, 

police and fire stations, courts and 

other government services 

553 Large Public Facilities 

Includes power sub-stations, Work 

yards, Sewer and Water treatment 

plants 

554 Military Military Use 

555 Prisons Prisons and jails 

560 Special Events 

Includes stadiums, sports complexes, 

and fairgrounds 

571 Landfill Landfill 

572 Sand and Gravel Sand and Gravel 

573 Automotive Proving Grounds Automotive Proving Grounds 

574 Mining Mining 
2008 Maricopa Co. PM10 Emission Inventory A4–43 June 2011

575 Solar Generating Stations 

Solar generation stations not 

associated with other power facilities 

610 Transportation 

Freeways/Expressways/ Highways/ 

Major Roads/ Arterials/ ROWs where 

no detail available 

611 Parking Lots Parking Lots 

612 Parking Structures Parking Structures 

613 Park and Ride lots Park and Ride lots 

614 Transit Center Transit Center 

615 Freeways/Expressways/ Highways Freeways/Expressways/ Highways 

616 Major Roads, Arterials Major Roads, Arterials 

617 Neighborhood roads Neighborhood roads 

618 Railroads Railroads 

620 Airports Public use airports 

621 Sky Harbor Airport Sky Harbor Airport 

622 Private airport Private use airports 

710 City/Regional Active Open Space 

Includes city/regional parks, 

playgrounds/fields 

711 

Local/Neighborhood Active Open 

Space 

Includes Local/Neighborhood common 

areas, parks, playgrounds 

720 Golf courses Golf Courses 

730 Passive Open Space 

Includes mountain preserves and 

washes 

731 Restricted Open Space 

Restricted Open Space (Including 

Firing Range) 

732 Limited Use Public Facilities Very small difficult to access parcels 

733 Floodplain Floodplain 

740 Water Reservoirs/Rivers/Lakes 

741 Canal Canal 

742 Intermittant Water Intermittant Water 

743 Residential Lake Residential Lake 

750 Agriculture General Agriculture 

810 Business Park 

Includes enclosed industrial, office or 

retail in a planned environment 

820 Mixed Use Jurisdiction defined 

821 Mixed Use/Indian Community Mixed Use/Indian Community 

830 Planned Community Planned Community 
2008 Maricopa Co. PM10 Emission Inventory A4–44 June 2011

900 

Vacant (existing land use database 

only) Vacant 

910 Developing Residential Residential Under Construction 

920 Developing Commercial Commercial Under Construction 

930 Developing Industrial Industrial Under Construction 

940 Developing Office Office Under Construction 

950 Developing Public/Other Employment Employment Under Construction 

960 Developing Transportation Transportation Under Construction 

970 Developing Open Space Developing Open Space 

980 Developing Multiple Use Multiple Use Under Construction 

999 Unknown Unknown 
2008 Maricopa Co. PM10 Emission Inventory A5–1 June 2011 

Appendix 5. MOVES2010a Local Input Data and RunSpecs

In order to calculate the 2008 annual and average day onroad source emissions, MOVES2010a 

was executed using local input data for each month of the year and each geographical area 

(Maricopa County and the PM10 NAA).

A portion of the MOVES2010a RunSpec Summary, RunSpec, and local input data for Maricopa 

County are provided in this appendix as an example.
2008 Maricopa Co. PM10 Emission Inventory A5–2 June 2011 

MOVES2010a RunSpec Summary (Maricopa County, July 2008)

Output Database Server Name: [using default]

Output Database Name: 2008_pm10_pei_mc_07_out

Time Spans:

Aggregate By: Hour

Years:

2008

Months:

July

Days:

Weekend

Weekdays

Hours:

Begin Hour: 00:00 - 00:59

End Hour: 23:00 - 23:59

Geographic Bounds:

COUNTY geography

Selection: ARIZONA - Maricopa County

On Road Vehicle Equipment:

Diesel Fuel - Combination Long-haul Truck

Diesel Fuel - Combination Short-haul Truck

Diesel Fuel - Intercity Bus

Diesel Fuel - Light Commercial Truck

Diesel Fuel - Motor Home

Diesel Fuel - Motorcycle

Diesel Fuel - Passenger Car

Diesel Fuel - Passenger Truck

Diesel Fuel - Refuse Truck

Diesel Fuel - School Bus

Diesel Fuel - Single Unit Long-haul Truck

Diesel Fuel - Single Unit Short-haul Truck

Diesel Fuel - Transit Bus

Gasoline - Combination Long-haul Truck

Gasoline - Combination Short-haul Truck

Gasoline - Intercity Bus

Gasoline - Light Commercial Truck

Gasoline - Motor Home

Gasoline - Motorcycle

Gasoline - Passenger Car

Gasoline - Passenger Truck

Gasoline - Refuse Truck

Gasoline - School Bus

Gasoline - Single Unit Long-haul Truck

Gasoline - Single Unit Short-haul Truck

Gasoline - Transit Bus

Road Types:

Off-Network

Rural Restricted Access

Rural Unrestricted Access

Urban Restricted Access

Urban Unrestricted Access

Pollutants And Processes:

Running Exhaust Ammonia (NH3)

Start Exhaust Ammonia (NH3)

Crankcase Running Exhaust Ammonia (NH3)

Crankcase Start Exhaust Ammonia (NH3)

Crankcase Extended Idle Exhaust Ammonia (NH3)

Extended Idle Exhaust Ammonia (NH3)

Running Exhaust Oxides of Nitrogen (NOx)

Start Exhaust Oxides of Nitrogen (NOx)

Crankcase Running Exhaust Oxides of Nitrogen (NOx)

Crankcase Start Exhaust Oxides of Nitrogen (NOx)

Crankcase Extended Idle Exhaust Oxides of Nitrogen (NOx)

Extended Idle Exhaust Oxides of Nitrogen (NOx)

Running Exhaust Primary Exhaust PM10 - Total

Start Exhaust Primary Exhaust PM10 - Total

Crankcase Running Exhaust Primary Exhaust PM10 - Total

Crankcase Start Exhaust Primary Exhaust PM10 - Total

Crankcase Extended Idle Exhaust Primary Exhaust PM10 - Total

Extended Idle Exhaust Primary Exhaust PM10 - Total

Running Exhaust Primary Exhaust PM2.5 - Total

Start Exhaust Primary Exhaust PM2.5 - Total

Crankcase Running Exhaust Primary Exhaust PM2.5 - Total

Crankcase Start Exhaust Primary Exhaust PM2.5 - Total

Crankcase Extended Idle Exhaust Primary Exhaust PM2.5 - Total

Extended Idle Exhaust Primary Exhaust PM2.5 - Total

Brakewear Primary PM10 - Brakewear Particulate

Running Exhaust Primary PM10 - Elemental Carbon

Start Exhaust Primary PM10 - Elemental Carbon

Crankcase Running Exhaust Primary PM10 - Elemental Carbon

Crankcase Start Exhaust Primary PM10 - Elemental Carbon

Crankcase Extended Idle Exhaust Primary PM10 - Elemental Carbon

Extended Idle Exhaust Primary PM10 - Elemental Carbon

Running Exhaust Primary PM10 - Organic Carbon

Start Exhaust Primary PM10 - Organic Carbon

Crankcase Running Exhaust Primary PM10 - Organic Carbon

Crankcase Start Exhaust Primary PM10 - Organic Carbon

Crankcase Extended Idle Exhaust Primary PM10 - Organic Carbon

Extended Idle Exhaust Primary PM10 - Organic Carbon

Running Exhaust Primary PM10 - Sulfate Particulate

Start Exhaust Primary PM10 - Sulfate Particulate

Crankcase Running Exhaust Primary PM10 - Sulfate Particulate

Crankcase Start Exhaust Primary PM10 - Sulfate Particulate

Crankcase Extended Idle Exhaust Primary PM10 - Sulfate 

Particulate

Extended Idle Exhaust Primary PM10 - Sulfate Particulate

Tirewear Primary PM10 - Tirewear Particulate

Brakewear Primary PM2.5 - Brakewear Particulate

Running Exhaust Primary PM2.5 - Elemental Carbon

Start Exhaust Primary PM2.5 - Elemental Carbon

Crankcase Running Exhaust Primary PM2.5 - Elemental Carbon

Crankcase Start Exhaust Primary PM2.5 - Elemental Carbon

Crankcase Extended Idle Exhaust Primary PM2.5 - Elemental 

Carbon

Extended Idle Exhaust Primary PM2.5 - Elemental Carbon

Running Exhaust Primary PM2.5 - Organic Carbon

Start Exhaust Primary PM2.5 - Organic Carbon

Crankcase Running Exhaust Primary PM2.5 - Organic Carbon

Crankcase Start Exhaust Primary PM2.5 - Organic Carbon

Crankcase Extended Idle Exhaust Primary PM2.5 - Organic Carbon

Extended Idle Exhaust Primary PM2.5 - Organic Carbon

Running Exhaust Primary PM2.5 - Sulfate Particulate

Start Exhaust Primary PM2.5 - Sulfate Particulate

Crankcase Running Exhaust Primary PM2.5 - Sulfate Particulate

Crankcase Start Exhaust Primary PM2.5 - Sulfate Particulate

Crankcase Extended Idle Exhaust Primary PM2.5 - Sulfate 

Particulate

Extended Idle Exhaust Primary PM2.5 - Sulfate Particulate

Tirewear Primary PM2.5 - Tirewear Particulate

Running Exhaust Sulfur Dioxide (SO2)

Start Exhaust Sulfur Dioxide (SO2)

Crankcase Running Exhaust Sulfur Dioxide (SO2)

Crankcase Start Exhaust Sulfur Dioxide (SO2)

Crankcase Extended Idle Exhaust Sulfur Dioxide (SO2)

Extended Idle Exhaust Sulfur Dioxide (SO2)

Running Exhaust Total Energy Consumption

Start Exhaust Total Energy Consumption

Extended Idle Exhaust Total Energy Consumption

Rate of Progress:

Rate of Progress calculations are disabled

Manage Input Data Sets:

selection: / stageii_input / 
2008 Maricopa Co. PM10 Emission Inventory A5–3 June 2011 

MOVES2010a RunSpec (Maricopa County, July 2008)

<runspec>

<description><![CDATA[Updated 2008 PEI

- Maricopa County

- inventory mode

- both weekdays and weekend days

- output by SCC

- July 2008]]></description>

<modelscale value="Inv"/>

<modeldomain value="SINGLE"/>

<geographicselections>

<geographicselection type="COUNTY" key="4013" description="ARIZONA - Maricopa County"/>

</geographicselections>

<timespan>

<year key="2008"/>

<month id="7"/>

<day id="2"/>

<day id="5"/>

<beginhour id="1"/>

<endhour id="24"/>

<aggregateBy key="Hour"/>

</timespan>

<onroadvehicleselections>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetypeid="62" sourcetypename="Combination 

Long-haul Truck"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetypeid="61" sourcetypename="Combination 

Short-haul Truck"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetypeid="41" sourcetypename="Intercity 

Bus"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetypeid="32" sourcetypename="Light 

Commercial Truck"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetypeid="54" sourcetypename="Motor Home"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetypeid="11" 

sourcetypename="Motorcycle"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetypeid="21" sourcetypename="Passenger 

Car"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetypeid="31" sourcetypename="Passenger 

Truck"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetypeid="51" sourcetypename="Refuse 

Truck"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetypeid="43" sourcetypename="School Bus"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetypeid="53" sourcetypename="Single Unit 

Long-haul Truck"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetypeid="52" sourcetypename="Single Unit 

Short-haul Truck"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetypeid="42" sourcetypename="Transit 

Bus"/>

<onroadvehicleselection fueltypeid="1" fueltypedesc="Gasoline" sourcetypeid="62" sourcetypename="Combination 

Long-haul Truck"/>

<onroadvehicleselection fueltypeid="1" fueltypedesc="Gasoline" sourcetypeid="61" sourcetypename="Combination 

Short-haul Truck"/>

<onroadvehicleselection fueltypeid="1" fueltypedesc="Gasoline" sourcetypeid="41" sourcetypename="Intercity 

Bus"/>

<onroadvehicleselection fueltypeid="1" fueltypedesc="Gasoline" sourcetypeid="32" sourcetypename="Light 

Commercial Truck"/>

<onroadvehicleselection fueltypeid="1" fueltypedesc="Gasoline" sourcetypeid="54" sourcetypename="Motor Home"/>

<onroadvehicleselection fueltypeid="1" fueltypedesc="Gasoline" sourcetypeid="11" sourcetypename="Motorcycle"/>

<onroadvehicleselection fueltypeid="1" fueltypedesc="Gasoline" sourcetypeid="21" sourcetypename="Passenger 

Car"/>

<onroadvehicleselection fueltypeid="1" fueltypedesc="Gasoline" sourcetypeid="31" sourcetypename="Passenger 

Truck"/>

<onroadvehicleselection fueltypeid="1" fueltypedesc="Gasoline" sourcetypeid="51" sourcetypename="Refuse Truck"/>

<onroadvehicleselection fueltypeid="1" fueltypedesc="Gasoline" sourcetypeid="43" sourcetypename="School Bus"/>

<onroadvehicleselection fueltypeid="1" fueltypedesc="Gasoline" sourcetypeid="53" sourcetypename="Single Unit 

Long-haul Truck"/>

<onroadvehicleselection fueltypeid="1" fueltypedesc="Gasoline" sourcetypeid="52" sourcetypename="Single Unit 

Short-haul Truck"/>

<onroadvehicleselection fueltypeid="1" fueltypedesc="Gasoline" sourcetypeid="42" sourcetypename="Transit Bus"/>

</onroadvehicleselections>

<offroadvehicleselections>

</offroadvehicleselections>

<offroadvehiclesccs>

</offroadvehiclesccs>

<roadtypes>

<roadtype roadtypeid="1" roadtypename="Off-Network"/>

<roadtype roadtypeid="2" roadtypename="Rural Restricted Access"/>

<roadtype roadtypeid="3" roadtypename="Rural Unrestricted Access"/>

<roadtype roadtypeid="4" roadtypename="Urban Restricted Access"/>

<roadtype roadtypeid="5" roadtypename="Urban Unrestricted Access"/>

</roadtypes>

<pollutantprocessassociations>

<pollutantprocessassociation pollutantkey="30" pollutantname="Ammonia (NH3)" processkey="1" processname="Running 

Exhaust"/>

<pollutantprocessassociation pollutantkey="30" pollutantname="Ammonia (NH3)" processkey="2" processname="Start 

Exhaust"/>

<pollutantprocessassociation pollutantkey="30" pollutantname="Ammonia (NH3)" processkey="15" 

processname="Crankcase Running Exhaust"/>

<pollutantprocessassociation pollutantkey="30" pollutantname="Ammonia (NH3)" processkey="16" 

processname="Crankcase Start Exhaust"/>

<pollutantprocessassociation pollutantkey="30" pollutantname="Ammonia (NH3)" processkey="17" 

processname="Crankcase Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="30" pollutantname="Ammonia (NH3)" processkey="90" 
2008 Maricopa Co. PM10 Emission Inventory A5–4 June 2011 

processname="Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="3" pollutantname="Oxides of Nitrogen (NOx)" processkey="1" 

processname="Running Exhaust"/>

<pollutantprocessassociation pollutantkey="3" pollutantname="Oxides of Nitrogen (NOx)" processkey="2" 

processname="Start Exhaust"/>

<pollutantprocessassociation pollutantkey="3" pollutantname="Oxides of Nitrogen (NOx)" processkey="15" 

processname="Crankcase Running Exhaust"/>

<pollutantprocessassociation pollutantkey="3" pollutantname="Oxides of Nitrogen (NOx)" processkey="16" 

processname="Crankcase Start Exhaust"/>

<pollutantprocessassociation pollutantkey="3" pollutantname="Oxides of Nitrogen (NOx)" processkey="17" 

processname="Crankcase Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="3" pollutantname="Oxides of Nitrogen (NOx)" processkey="90" 

processname="Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="100" pollutantname="Primary Exhaust PM10 - Total" processkey="1" 

processname="Running Exhaust"/>

<pollutantprocessassociation pollutantkey="100" pollutantname="Primary Exhaust PM10 - Total" processkey="2" 

processname="Start Exhaust"/>

<pollutantprocessassociation pollutantkey="100" pollutantname="Primary Exhaust PM10 - Total" processkey="15" 

processname="Crankcase Running Exhaust"/>

<pollutantprocessassociation pollutantkey="100" pollutantname="Primary Exhaust PM10 - Total" processkey="16" 

processname="Crankcase Start Exhaust"/>

<pollutantprocessassociation pollutantkey="100" pollutantname="Primary Exhaust PM10 - Total" processkey="17" 

processname="Crankcase Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="100" pollutantname="Primary Exhaust PM10 - Total" processkey="90" 

processname="Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="110" pollutantname="Primary Exhaust PM2.5 - Total" processkey="1" 

processname="Running Exhaust"/>

<pollutantprocessassociation pollutantkey="110" pollutantname="Primary Exhaust PM2.5 - Total" processkey="2" 

processname="Start Exhaust"/>

<pollutantprocessassociation pollutantkey="110" pollutantname="Primary Exhaust PM2.5 - Total" processkey="15" 

processname="Crankcase Running Exhaust"/>

<pollutantprocessassociation pollutantkey="110" pollutantname="Primary Exhaust PM2.5 - Total" processkey="16" 

processname="Crankcase Start Exhaust"/>

<pollutantprocessassociation pollutantkey="110" pollutantname="Primary Exhaust PM2.5 - Total" processkey="17" 

processname="Crankcase Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="110" pollutantname="Primary Exhaust PM2.5 - Total" processkey="90" 

processname="Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="106" pollutantname="Primary PM10 - Brakewear Particulate" 

processkey="9" processname="Brakewear"/>

<pollutantprocessassociation pollutantkey="102" pollutantname="Primary PM10 - Elemental Carbon" processkey="1" 

processname="Running Exhaust"/>

<pollutantprocessassociation pollutantkey="102" pollutantname="Primary PM10 - Elemental Carbon" processkey="2" 

processname="Start Exhaust"/>

<pollutantprocessassociation pollutantkey="102" pollutantname="Primary PM10 - Elemental Carbon" processkey="15" 

processname="Crankcase Running Exhaust"/>

<pollutantprocessassociation pollutantkey="102" pollutantname="Primary PM10 - Elemental Carbon" processkey="16" 

processname="Crankcase Start Exhaust"/>

<pollutantprocessassociation pollutantkey="102" pollutantname="Primary PM10 - Elemental Carbon" processkey="17" 

processname="Crankcase Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="102" pollutantname="Primary PM10 - Elemental Carbon" processkey="90" 

processname="Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="101" pollutantname="Primary PM10 - Organic Carbon" processkey="1" 

processname="Running Exhaust"/>

<pollutantprocessassociation pollutantkey="101" pollutantname="Primary PM10 - Organic Carbon" processkey="2" 

processname="Start Exhaust"/>

<pollutantprocessassociation pollutantkey="101" pollutantname="Primary PM10 - Organic Carbon" processkey="15" 

processname="Crankcase Running Exhaust"/>

<pollutantprocessassociation pollutantkey="101" pollutantname="Primary PM10 - Organic Carbon" processkey="16" 

processname="Crankcase Start Exhaust"/>

<pollutantprocessassociation pollutantkey="101" pollutantname="Primary PM10 - Organic Carbon" processkey="17" 

processname="Crankcase Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="101" pollutantname="Primary PM10 - Organic Carbon" processkey="90" 

processname="Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="105" pollutantname="Primary PM10 - Sulfate Particulate" processkey="1" 

processname="Running Exhaust"/>

<pollutantprocessassociation pollutantkey="105" pollutantname="Primary PM10 - Sulfate Particulate" processkey="2" 

processname="Start Exhaust"/>

<pollutantprocessassociation pollutantkey="105" pollutantname="Primary PM10 - Sulfate Particulate" processkey="15" 

processname="Crankcase Running Exhaust"/>

<pollutantprocessassociation pollutantkey="105" pollutantname="Primary PM10 - Sulfate Particulate" processkey="16" 

processname="Crankcase Start Exhaust"/>

<pollutantprocessassociation pollutantkey="105" pollutantname="Primary PM10 - Sulfate Particulate" processkey="17" 

processname="Crankcase Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="105" pollutantname="Primary PM10 - Sulfate Particulate" processkey="90" 

processname="Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="107" pollutantname="Primary PM10 - Tirewear Particulate" 

processkey="10" processname="Tirewear"/>

<pollutantprocessassociation pollutantkey="116" pollutantname="Primary PM2.5 - Brakewear Particulate" 

processkey="9" processname="Brakewear"/>

<pollutantprocessassociation pollutantkey="112" pollutantname="Primary PM2.5 - Elemental Carbon" processkey="1" 

processname="Running Exhaust"/>

<pollutantprocessassociation pollutantkey="112" pollutantname="Primary PM2.5 - Elemental Carbon" processkey="2" 

processname="Start Exhaust"/>

<pollutantprocessassociation pollutantkey="112" pollutantname="Primary PM2.5 - Elemental Carbon" processkey="15" 

processname="Crankcase Running Exhaust"/>

<pollutantprocessassociation pollutantkey="112" pollutantname="Primary PM2.5 - Elemental Carbon" processkey="16" 

processname="Crankcase Start Exhaust"/>

<pollutantprocessassociation pollutantkey="112" pollutantname="Primary PM2.5 - Elemental Carbon" processkey="17" 

processname="Crankcase Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="112" pollutantname="Primary PM2.5 - Elemental Carbon" processkey="90" 

processname="Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="111" pollutantname="Primary PM2.5 - Organic Carbon" processkey="1" 

processname="Running Exhaust"/>

<pollutantprocessassociation pollutantkey="111" pollutantname="Primary PM2.5 - Organic Carbon" processkey="2" 

processname="Start Exhaust"/>
2008 Maricopa Co. PM10 Emission Inventory A5–5 June 2011 

<pollutantprocessassociation pollutantkey="111" pollutantname="Primary PM2.5 - Organic Carbon" processkey="15" 

processname="Crankcase Running Exhaust"/>

<pollutantprocessassociation pollutantkey="111" pollutantname="Primary PM2.5 - Organic Carbon" processkey="16" 

processname="Crankcase Start Exhaust"/>

<pollutantprocessassociation pollutantkey="111" pollutantname="Primary PM2.5 - Organic Carbon" processkey="17" 

processname="Crankcase Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="111" pollutantname="Primary PM2.5 - Organic Carbon" processkey="90" 

processname="Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="115" pollutantname="Primary PM2.5 - Sulfate Particulate" processkey="1" 

processname="Running Exhaust"/>

<pollutantprocessassociation pollutantkey="115" pollutantname="Primary PM2.5 - Sulfate Particulate" processkey="2" 

processname="Start Exhaust"/>

<pollutantprocessassociation pollutantkey="115" pollutantname="Primary PM2.5 - Sulfate Particulate" 

processkey="15" processname="Crankcase Running Exhaust"/>

<pollutantprocessassociation pollutantkey="115" pollutantname="Primary PM2.5 - Sulfate Particulate" 

processkey="16" processname="Crankcase Start Exhaust"/>

<pollutantprocessassociation pollutantkey="115" pollutantname="Primary PM2.5 - Sulfate Particulate" 

processkey="17" processname="Crankcase Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="115" pollutantname="Primary PM2.5 - Sulfate Particulate" 

processkey="90" processname="Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="117" pollutantname="Primary PM2.5 - Tirewear Particulate" 

processkey="10" processname="Tirewear"/>

<pollutantprocessassociation pollutantkey="31" pollutantname="Sulfur Dioxide (SO2)" processkey="1" 

processname="Running Exhaust"/>

<pollutantprocessassociation pollutantkey="31" pollutantname="Sulfur Dioxide (SO2)" processkey="2"

processname="Start Exhaust"/>

<pollutantprocessassociation pollutantkey="31" pollutantname="Sulfur Dioxide (SO2)" processkey="15" 

processname="Crankcase Running Exhaust"/>

<pollutantprocessassociation pollutantkey="31" pollutantname="Sulfur Dioxide (SO2)" processkey="16" 

processname="Crankcase Start Exhaust"/>

<pollutantprocessassociation pollutantkey="31" pollutantname="Sulfur Dioxide (SO2)" processkey="17" 

processname="Crankcase Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="31" pollutantname="Sulfur Dioxide (SO2)" processkey="90" 

processname="Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="91" pollutantname="Total Energy Consumption" processkey="1" 

processname="Running Exhaust"/>

<pollutantprocessassociation pollutantkey="91" pollutantname="Total Energy Consumption" processkey="2" 

processname="Start Exhaust"/>

<pollutantprocessassociation pollutantkey="91" pollutantname="Total Energy Consumption" processkey="90" 

processname="Extended Idle Exhaust"/>

</pollutantprocessassociations>

<databaseselections>

<databaseselection servername="" databasename="stageii_input" description=""/>

</databaseselections>

<internalcontrolstrategies>

<internalcontrolstrategy 

classname="gov.epa.otaq.moves.master.implementation.ghg.internalcontrolstrategies.rateofprogress.RateOfProgressStrategy"><![CDATA

[

useParameters No

]]></internalcontrolstrategy>

</internalcontrolstrategies>

<inputdatabase servername="" databasename="" description=""/>

<uncertaintyparameters uncertaintymodeenabled="false" numberofrunspersimulation="0" numberofsimulations="0"/>

<geographicoutputdetail description="COUNTY"/>

<outputemissionsbreakdownselection>

<modelyear selected="false"/>

<fueltype selected="true"/>

<emissionprocess selected="false"/>

<onroadoffroad selected="true"/>

<roadtype selected="false"/>

<sourceusetype selected="false"/>

<movesvehicletype selected="false"/>

<onroadscc selected="true"/>

<offroadscc selected="false"/>

<estimateuncertainty selected="false" numberOfIterations="2" keepSampledData="false" keepIterations="false"/>

<sector selected="false"/>

<engtechid selected="false"/>

<hpclass selected="false"/>

</outputemissionsbreakdownselection>

<outputdatabase servername="" databasename="2008_pm10_pei_mc_07_out" description=""/>

<outputtimestep value="Hour"/>

<outputvmtdata value="true"/>

<outputsho value="false"/>

<outputsh value="false"/>

<outputshp value="false"/>

<outputshidling value="false"/>

<outputstarts value="false"/>

<outputpopulation value="true"/>

<scaleinputdatabase servername="localhost" databasename="2008_pm10_pei_mc_in" description=""/>

<pmsize value="0"/>

<outputfactors>

<timefactors selected="true" units="Hours"/>

<distancefactors selected="true" units="Miles"/>

<massfactors selected="true" units="Grams" energyunits="Joules"/>

</outputfactors>

<savedata>

</savedata>

<donotexecute>

</donotexecute>

<generatordatabase shouldsave="false" servername="" databasename="" description=""/>

<donotperformfinalaggregation selected="false"/>

<lookuptableflags scenarioid="" truncateoutput="true" truncateactivity="true"/>

</runspec>
2008 Maricopa Co. PM10 Emission Inventory A5–6 June 2011 

MOVES2010a Local Input Data (Maricopa County, July 2008)

[FuelFormulation] Fuel

Formulation

Fuel

Subtype RVP

Sulfur

Level

ETOH

Volume

MTBE

Volume

ETBE

Volume

TAME

Volume

Aromatic

Content

Olefin

Content

Benzene

Content e200 e300

volToWt

PercentOxy

BioDiesel

Ester Cetane

Index

PAH

Content

10801 12 8.76 35.00 9.5 0 0 0 14.4 4.9 1.0 53.0 91.0 3.4933 0 0 0

10802 12 8.42 23.14 9.2 0 0 0 12.8 3.9 0.9 50.3 91.1 3.4229 0 0 0

10803 12 8.40 49.00 9.2 0 0 0 12.0 4.0 0.8 50.3 92.0 3.4075 0 0 0

10804 14 7.77 23.00 5.6 0 0 0 17.7 6.0 1.0 45.5 88.5 2.0567 0 0 0

10805 14 6.95 26.04 1.3 0 0 0 16.8 7.6 0.8 40.2 88.4 0.5086 0 0 0

10806 11 6.64 25.20 0.0 0 0 0 16.3 7.0 0.7 38.4 86.4 0.0000 0 0 0

10807 14 7.07 18.83 0.7 0 0 0 16.6 7.3 0.8 37.9 89.0 0.3367 0 0 0

10808 14 6.81 28.59 0.4 0 0 0 15.0 7.4 0.8 38.9 89.2 0.1495 0 0 0

10809 11 6.48 34.56 0.0 0 0 0 18.2 10.1 0.9 40.3 88.8 0.0000 0 0 0

10810 13 7.91 24.95 6.8 0 0 0 17.1 8.0 0.9 46.5 89.5 2.5173 0 0 0

10811 12 8.41 15.17 9.5 0 0 0 16.1 5.9 1.1 53.3 90.9 3.5425 0 0 0

10812 13 8.38 29.45 8.8 0 0 0 14.5 5.3 0.9 50.7 90.9 3.2767 0 0 0

30801 20 0 6.18 0 0 0 0 0 0 0 0 0 0 0 0 0

30802 20 0 6.27 0 0 0 0 0 0 0 0 0 0 0 0 0

30803 20 0 6.65 0 0 0 0 0 0 0 0 0 0 0 0 0

30804 20 0 6.60 0 0 0 0 0 0 0 0 0 0 0 0 0

30805 20 0 5.78 0 0 0 0 0 0 0 0 0 0 0 0 0

30806 20 0 5.60 0 0 0 0 0 0 0 0 0 0 0 0 0

30807 20 0 4.20 0 0 0 0 0 0 0 0 0 0 0 0 0

30808 20 0 6.25 0 0 0 0 0 0 0 0 0 0 0 0 0

30809 20 0 6.25 0 0 0 0 0 0 0 0 0 0 0 0 0

30810 20 0 6.49 0 0 0 0 0 0 0 0 0 0 0 0 0

30811 20 0 6.49 0 0 0 0 0 0 0 0 0 0 0 0 0

30812 20 0 6.85 0 0 0 0 0 0 0 0 0 0 0 0 0

[FuelSupply]

countyID fuelYearID monthGroupID fuelFormulationID marketShare marketShareCV

4013 2008 1 10801 1 0.5

4013 2008 1 30801 1 0.5

4013 2008 2 10802 1 0.5

4013 2008 2 30802 1 0.5

4013 2008 3 10803 1 0.5

4013 2008 3 30803 1 0.5

4013 2008 4 10804 1 0.5

4013 2008 4 30804 1 0.5

4013 2008 5 10805 1 0.5

4013 2008 5 30805 1 0.5

4013 2008 6 10806 1 0.5

4013 2008 6 30806 1 0.5

4013 2008 7 10807 1 0.5

4013 2008 7 30807 1 0.5

4013 2008 8 10808 1 0.5

4013 2008 8 30808 1 0.5

4013 2008 9 10809 1 0.5

4013 2008 9 30809 1 0.5

4013 2008 10 10810 1 0.5

4013 2008 10 30810 1 0.5

4013 2008 11 10811 1 0.5

4013 2008 11 30811 1 0.5

4013 2008 12 10812 1 0.5

4013 2008 12 30812 1 0.5

[HPMSvTypeYear]

HPMSVtypeID yearID VMTGrowthFactor HPMSBaseYearVMT baseYearOffNetVMT

10 2008 0 645,186,775 0

20 2008 0 10,853,816,218 0

30 2008 0 18,712,863,968 0

40 2008 0 120,356,976 0

50 2008 0 1,301,102,686 0

60 2008 0 1,675,478,378 0

[SourceTypeYear]

yearID sourceTypeID sourceTypePopulation

2008 11 72,411

2008 21 2,056,832

2008 31 474,713

2008 32 183,510

2008 41 1,109

2008 42 680

2008 43 7,115

2008 51 832

2008 52 27,284

2008 53 1,756

2008 54 3,599

2008 61 13,958

2008 62 11,504
2008 Maricopa Co. PM10 Emission Inventory A5–7 June 2011 

[ZoneMonthHour] monthID zoneID HourID temperature relHumidity

7 40130 1 90.0 39.0

7 40130 2 89.0 41.0

7 40130 3 88.0 42.0

7 40130 4 88.0 43.0

7 40130 5 87.0 44.0

7 40130 6 86.0 46.0

7 40130 7 87.0 45.0

7 40130 8 89.0 41.0

7 40130 9 92.0 37.0

7 40130 10 94.0 34.0

7 40130 11 96.0 30.0

7 40130 12 99.0 27.0

7 40130 13 100.0 25.0

7 40130 14 102.0 23.0

7 40130 15 103.0 22.0

7 40130 16 104.0 21.0

7 40130 17 103.0 23.0

7 40130 18 103.0 23.0

7 40130 19 101.0 24.0

7 40130 20 99.0 26.0

7 40130 21 97.0 30.0

7 40130 22 95.0 32.0

7 40130 23 93.0 35.0

7 40130 24 91.0 38.0

[SourceTypeAgeDistribution] Source

TypeID YearID AgeID AgeFraction

11 2008 0 0.097639

11 2008 1 0.153685

11 2008 2 0.124466

11 2008 3 0.088073

11 2008 4 0.100239

11 2008 5 0.075075

11 2008 6 0.060726

11 2008 7 0.050223

11 2008 8 0.041801

11 2008 9 0.030675

11 2008 10 0.024748

11 2008 11 0.023188

11 2008 12 0.019341

11 2008 13 0.014557

11 2008 14 0.013518

11 2008 15 0.009462

11 2008 16 0.006967

11 2008 17 0.006863

11 2008 18 0.006447

11 2008 19 0.006239

11 2008 20 0.006551

11 2008 21 0.010190

11 2008 22 0.008734

11 2008 23 0.006239

11 2008 24 0.004456

11 2008 25 0.003183

11 2008 26 0.002274

11 2008 27 0.001624

11 2008 28 0.001160

11 2008 29 0.000829

11 2008 30 0.000829

21 2008 0 0.058600

21 2008 1 0.089800

21 2008 2 0.090900

21 2008 3 0.084700

21 2008 4 0.078600

21 2008 5 0.071000

21 2008 6 0.069000

21 2008 7 0.063900

21 2008 8 0.062800

21 2008 9 0.053900

21 2008 10 0.044000

21 2008 11 0.038300

21 2008 12 0.029700

21 2008 13 0.029400

21 2008 14 0.023000

21 2008 15 0.018700

21 2008 16 0.014700

21 2008 17 0.012900

21 2008 18 0.010600

21 2008 19 0.008800

21 2008 20 0.006600

21 2008 21 0.005600

21 2008 22 0.004300

Source

TypeID YearID AgeID AgeFraction

21 2008 23 0.003600

21 2008 24 0.003014

21 2008 25 0.002523

21 2008 26 0.002113

21 2008 27 0.001769

21 2008 28 0.001481

21 2008 29 0.001240

21 2008 30 0.014461

31 2008 0 0.056148

31 2008 1 0.089988

31 2008 2 0.092916

31 2008 3 0.074872

31 2008 4 0.076932

31 2008 5 0.063022

31 2008 6 0.057914

31 2008 7 0.065833

31 2008 8 0.061920

31 2008 9 0.048255

31 2008 10 0.042507

31 2008 11 0.042947

31 2008 12 0.031419

31 2008 13 0.030928

31 2008 14 0.028403

31 2008 15 0.018757

31 2008 16 0.012649

31 2008 17 0.011138

31 2008 18 0.010056

31 2008 19 0.011393

31 2008 20 0.008919

31 2008 21 0.005793

31 2008 22 0.007552

31 2008 23 0.005668

31 2008 24 0.004272

31 2008 25 0.003242

31 2008 26 0.002452

31 2008 27 0.001919

31 2008 28 0.001515

31 2008 29 0.001206

31 2008 30 0.029464

32 2008 0 0.059763

32 2008 1 0.095684

32 2008 2 0.099128

32 2008 3 0.077088

32 2008 4 0.074825

32 2008 5 0.060022

32 2008 6 0.054098

32 2008 7 0.061759

32 2008 8 0.062509

32 2008 9 0.047608

32 2008 10 0.041619

32 2008 11 0.043153

32 2008 12 0.031489

32 2008 13 0.031005

32 2008 14 0.029429

Source

TypeID YearID AgeID AgeFraction

32 2008 15 0.019239

32 2008 16 0.011888

32 2008 17 0.010528

32 2008 18 0.009695

32 2008 19 0.011148

32 2008 20 0.008679

32 2008 21 0.005441

32 2008 22 0.007091

32 2008 23 0.005301

32 2008 24 0.004014

32 2008 25 0.003071

32 2008 26 0.002418

32 2008 27 0.001846

32 2008 28 0.001426

32 2008 29 0.001119

32 2008 30 0.027915

41 2008 0 0.054400

41 2008 1 0.127000

41 2008 2 0.137800

41 2008 3 0.114200

41 2008 4 0.062400

41 2008 5 0.042000

41 2008 6 0.031200

41 2008 7 0.041300

41 2008 8 0.057600

41 2008 9 0.053600

41 2008 10 0.030900

41 2008 11 0.029700

41 2008 12 0.030500

41 2008 13 0.029100

41 2008 14 0.054600

41 2008 15 0.014200

41 2008 16 0.008200

41 2008 17 0.007600

41 2008 18 0.014800

41 2008 19 0.023100

41 2008 20 0.017500

41 2008 21 0.004500

41 2008 22 0.003500

41 2008 23 0.002300

41 2008 24 0.001511

41 2008 25 0.000993

41 2008 26 0.000653

41 2008 27 0.000429

41 2008 28 0.000282

41 2008 29 0.000185

41 2008 30 0.003947

42 2008 0 0.054400

42 2008 1 0.127000

42 2008 2 0.137800

42 2008 3 0.114200

42 2008 4 0.062400

42 2008 5 0.042000

42 2008 6 0.031200
2008 Maricopa Co. PM10 Emission Inventory A5–8 June 2011 

Source

TypeID YearID AgeID AgeFraction

42 2008 7 0.041300

42 2008 8 0.057600

42 2008 9 0.053600

42 2008 10 0.030900

42 2008 11 0.029700

42 2008 12 0.030500

42 2008 13 0.029100

42 2008 14 0.054600

42 2008 15 0.014200

42 2008 16 0.008200

42 2008 17 0.007600

42 2008 18 0.014800

42 2008 19 0.023100

42 2008 20 0.017500

42 2008 21 0.004500

42 2008 22 0.003500

42 2008 23 0.002300

42 2008 24 0.001511

42 2008 25 0.000993

42 2008 26 0.000653

42 2008 27 0.000429

42 2008 28 0.000282

42 2008 29 0.000185

42 2008 30 0.003947

43 2008 0 0.091684

43 2008 1 0.148636

43 2008 2 0.157944

43 2008 3 0.098690

43 2008 4 0.056752

43 2008 5 0.033430

43 2008 6 0.020118

43 2008 7 0.025423

43 2008 8 0.069363

43 2008 9 0.042739

43 2008 10 0.034531

43 2008 11 0.046342

43 2008 12 0.032930

43 2008 13 0.031173

43 2008 14 0.038212

43 2008 15 0.021940

43 2008 16 0.004822

43 2008 17 0.004813

43 2008 18 0.006470

43 2008 19 0.009141

43 2008 20 0.006922

43 2008 21 0.002448

43 2008 22 0.002714

43 2008 23 0.001715

43 2008 24 0.001077

43 2008 25 0.000681

43 2008 26 0.000430

43 2008 27 0.000290

43 2008 28 0.000183

43 2008 29 0.000115

43 2008 30 0.008269

51 2008 0 0.091611

51 2008 1 0.148519

51 2008 2 0.157820

51 2008 3 0.098612

51 2008 4 0.056707

51 2008 5 0.033404

51 2008 6 0.020103

51 2008 7 0.025403

51 2008 8 0.069309

51 2008 9 0.042705

51 2008 10 0.034504

51 2008 11 0.046306

51 2008 12 0.032904

51 2008 13 0.031602

51 2008 14 0.038601

51 2008 15 0.022601

51 2008 16 0.004899

51 2008 17 0.004900

51 2008 18 0.006499

51 2008 19 0.009099

51 2008 20 0.006797

51 2008 21 0.002400

51 2008 22 0.002700

51 2008 23 0.001700

51 2008 24 0.001070

51 2008 25 0.000674

51 2008 26 0.000424

Source

TypeID YearID AgeID AgeFraction

51 2008 27 0.000267

51 2008 28 0.000168

51 2008 29 0.000106

51 2008 30 0.007586

52 2008 0 0.082905

52 2008 1 0.133171

52 2008 2 0.140432

52 2008 3 0.091977

52 2008 4 0.061324

52 2008 5 0.040558

52 2008 6 0.029326

52 2008 7 0.035280

52 2008 8 0.066813

52 2008 9 0.043674

52 2008 10 0.036113

52 2008 11 0.044920

52 2008 12 0.032191

52 2008 13 0.031518

52 2008 14 0.036333

52 2008 15 0.022117

52 2008 16 0.006913

52 2008 17 0.006552

52 2008 18 0.007429

52 2008 19 0.009720

52 2008 20 0.007356

52 2008 21 0.003264

52 2008 22 0.004084

52 2008 23 0.002855

52 2008 24 0.002131

52 2008 25 0.001652

52 2008 26 0.001562

52 2008 27 0.001023

52 2008 28 0.000676

52 2008 29 0.000468

52 2008 30 0.015661

53 2008 0 0.090873

53 2008 1 0.146351

53 2008 2 0.155089

53 2008 3 0.097122

53 2008 4 0.056197

53 2008 5 0.033312

53 2008 6 0.020196

53 2008 7 0.025496

53 2008 8 0.068212

53 2008 9 0.042125

53 2008 10 0.034022

53 2008 11 0.045480

53 2008 12 0.032373

53 2008 13 0.033217

53 2008 14 0.040496

53 2008 15 0.025464

53 2008 16 0.005390

53 2008 17 0.005435

53 2008 18 0.006778

53 2008 19 0.009212

53 2008 20 0.006638

53 2008 21 0.002389

53 2008 22 0.003010

53 2008 23 0.001941

53 2008 24 0.001400

53 2008 25 0.001053

53 2008 26 0.001075

53 2008 27 0.000559

53 2008 28 0.000310

53 2008 29 0.000179

53 2008 30 0.008605

54 2008 0 0.092048

54 2008 1 0.149226

54 2008 2 0.158572

54 2008 3 0.099082

54 2008 4 0.056977

54 2008 5 0.033563

54 2008 6 0.020198

54 2008 7 0.025524

54 2008 8 0.069639

54 2008 9 0.042909

54 2008 10 0.034669

54 2008 11 0.046526

54 2008 12 0.033061

54 2008 13 0.030138

54 2008 14 0.036854

54 2008 15 0.020274

Source

TypeID YearID AgeID AgeFraction

54 2008 16 0.004587

54 2008 17 0.004591

54 2008 18 0.006362

54 2008 19 0.009049

54 2008 20 0.007043

54 2008 21 0.002525

54 2008 22 0.002703

54 2008 23 0.001719

54 2008 24 0.001069

54 2008 25 0.000675

54 2008 26 0.000432

54 2008 27 0.000338

54 2008 28 0.000212

54 2008 29 0.000131

54 2008 30 0.009302

61 2008 0 0.092019

61 2008 1 0.149180

61 2008 2 0.158522

61 2008 3 0.099051

61 2008 4 0.056959

61 2008 5 0.033553

61 2008 6 0.020192

61 2008 7 0.025516

61 2008 8 0.069617

61 2008 9 0.042895

61 2008 10 0.034658

61 2008 11 0.046512

61 2008 12 0.033051

61 2008 13 0.031559

61 2008 14 0.037665

61 2008 15 0.022381

61 2008 16 0.004788

61 2008 17 0.004864

61 2008 18 0.006421

61 2008 19 0.008694

61 2008 20 0.006439

61 2008 21 0.002319

61 2008 22 0.002610

61 2008 23 0.001634

61 2008 24 0.001022

61 2008 25 0.000627

61 2008 26 0.000397

61 2008 27 0.000256

61 2008 28 0.000154

61 2008 29 0.000090

61 2008 30 0.006355

62 2008 0 0.091775

62 2008 1 0.148783

62 2008 2 0.158101

62 2008 3 0.098788

62 2008 4 0.056808

62 2008 5 0.033464

62 2008 6 0.020138

62 2008 7 0.025448

62 2008 8 0.069432

62 2008 9 0.042781

62 2008 10 0.034566

62 2008 11 0.046388

62 2008 12 0.032963

62 2008 13 0.031586

62 2008 14 0.038240

62 2008 15 0.022517

62 2008 16 0.004855

62 2008 17 0.004882

62 2008 18 0.006464

62 2008 19 0.008940

62 2008 20 0.006652

62 2008 21 0.002363

62 2008 22 0.002658

62 2008 23 0.001670

62 2008 24 0.001049

62 2008 25 0.000654

62 2008 26 0.000412

62 2008 27 0.000262

62 2008 28 0.000162

62 2008 29 0.000100

62 2008 30 0.007099
2008 Maricopa Co. PM10 Emission Inventory A5–9 June 2011 

[IMCoverage]

polProcess

ID

State

ID

County

ID yearID sourceTypeID fuelTypeID IMProgramID

Beg

ModelYearID

End

ModelYearID inspectFreq

Test

StandardsID useIMyn

Compliance

Factor

101 4 4013 2008 21 1 103 1967 1980 1 13 Y 57.62

101 4 4013 2008 21 1 106 1981 1995 2 31 Y 64.12

101 4 4013 2008 21 1 110 1996 2004 2 51 Y 90.04

101 4 4013 2008 31 1 103 1967 1980 1 13 Y 57.62

101 4 4013 2008 31 1 106 1981 1995 2 31 Y 64.12

101 4 4013 2008 31 1 110 1996 2004 2 51 Y 90.04

101 4 4013 2008 32 1 103 1967 1980 1 13 Y 57.62

101 4 4013 2008 32 1 106 1981 1995 2 31 Y 64.12

101 4 4013 2008 32 1 110 1996 2004 2 51 Y 90.04

101 4 4013 2008 52 1 103 1967 2004 1 13 Y 87.20

102 4 4013 2008 21 1 103 1967 1980 1 13 Y 57.62

102 4 4013 2008 21 1 106 1981 1995 2 31 Y 64.12

102 4 4013 2008 21 1 110 1996 2004 2 51 Y 90.04

102 4 4013 2008 31 1 103 1967 1980 1 13 Y 57.62

102 4 4013 2008 31 1 106 1981 1995 2 31 Y 64.12

102 4 4013 2008 31 1 110 1996 2004 2 51 Y 90.04

102 4 4013 2008 32 1 103 1967 1980 1 13 Y 57.62

102 4 4013 2008 32 1 106 1981 1995 2 31 Y 64.12

102 4 4013 2008 32 1 110 1996 2004 2 51 Y 90.04

102 4 4013 2008 52 1 103 1967 2004 1 13 Y 87.20

112 4 4013 2008 21 1 108 1996 2004 2 43 Y 83.81

112 4 4013 2008 21 1 109 1981 1995 2 44 Y 64.12

112 4 4013 2008 31 1 108 1996 2004 2 43 Y 83.81

112 4 4013 2008 31 1 109 1981 1995 2 44 Y 64.12

112 4 4013 2008 32 1 108 1996 2004 2 43 Y 83.81

112 4 4013 2008 32 1 109 1981 1995 2 44 Y 64.12

112 4 4013 2008 52 1 107 1981 2004 1 41 Y 86.29

113 4 4013 2008 21 1 108 1996 2004 2 43 Y 83.81

113 4 4013 2008 21 1 109 1981 1995 2 44 Y 64.12

113 4 4013 2008 31 1 108 1996 2004 2 43 Y 83.81

113 4 4013 2008 31 1 109 1981 1995 2 44 Y 64.12

113 4 4013 2008 32 1 108 1996 2004 2 43 Y 83.81

113 4 4013 2008 32 1 109 1981 1995 2 44 Y 64.12

113 4 4013 2008 52 1 107 1981 2004 1 41 Y 86.29

201 4 4013 2008 21 1 103 1967 1980 1 13 Y 57.62

201 4 4013 2008 21 1 106 1981 1995 2 31 Y 64.12

201 4 4013 2008 21 1 110 1996 2004 2 51 Y 90.04

201 4 4013 2008 31 1 103 1967 1980 1 13 Y 57.62

201 4 4013 2008 31 1 106 1981 1995 2 31 Y 64.12

201 4 4013 2008 31 1 110 1996 2004 2 51 Y 90.04

201 4 4013 2008 32 1 103 1967 1980 1 13 Y 57.62

201 4 4013 2008 32 1 106 1981 1995 2 31 Y 64.12

201 4 4013 2008 32 1 110 1996 2004 2 51 Y 90.04

201 4 4013 2008 52 1 103 1967 2004 1 13 Y 87.20

202 4 4013 2008 21 1 103 1967 1980 1 13 Y 57.62

202 4 4013 2008 21 1 106 1981 1995 2 31 Y 64.12

202 4 4013 2008 21 1 110 1996 2004 2 51 Y 90.04

202 4 4013 2008 31 1 103 1967 1980 1 13 Y 57.62

202 4 4013 2008 31 1 106 1981 1995 2 31 Y 64.12

202 4 4013 2008 31 1 110 1996 2004 2 51 Y 90.04

202 4 4013 2008 32 1 103 1967 1980 1 13 Y 57.62

202 4 4013 2008 32 1 106 1981 1995 2 31 Y 64.12

202 4 4013 2008 32 1 110 1996 2004 2 51 Y 90.04

202 4 4013 2008 52 1 103 1967 2004 1 13 Y 87.20

301 4 4013 2008 21 1 103 1967 1980 1 13 Y 57.62

301 4 4013 2008 21 1 106 1981 1995 2 31 Y 64.12

301 4 4013 2008 21 1 110 1996 2004 2 51 Y 90.04

301 4 4013 2008 31 1 103 1967 1980 1 13 Y 57.62

301 4 4013 2008 31 1 106 1981 1995 2 31 Y 64.12

301 4 4013 2008 31 1 110 1996 2004 2 51 Y 90.04

301 4 4013 2008 32 1 103 1967 1980 1 13 Y 57.62

301 4 4013 2008 32 1 106 1981 1995 2 31 Y 64.12

301 4 4013 2008 32 1 110 1996 2004 2 51 Y 90.04

301 4 4013 2008 52 1 103 1967 2004 1 13 Y 87.20

302 4 4013 2008 21 1 103 1967 1980 1 13 Y 57.62

302 4 4013 2008 21 1 106 1981 1995 2 31 Y 64.12

302 4 4013 2008 21 1 110 1996 2004 2 51 Y 90.04

302 4 4013 2008 31 1 103 1967 1980 1 13 Y 57.62

302 4 4013 2008 31 1 106 1981 1995 2 31 Y 64.12

302 4 4013 2008 31 1 110 1996 2004 2 51 Y 90.04

302 4 4013 2008 32 1 103 1967 1980 1 13 Y 57.62

302 4 4013 2008 32 1 106 1981 1995 2 31 Y 64.12

302 4 4013 2008 32 1 110 1996 2004 2 51 Y 90.04

302 4 4013 2008 52 1 103 1967 2004 1 13 Y 87.20
2008 Maricopa Co. PM10 Emission Inventory A5–10 June 2011 

[RoadType]

roadTypeID rampFraction

2 0.042906

4 0.083904

[RoadTypeDistribution]

sourceTypeID roadTypeID roadTypeVMTFraction

11 1 0.00000

11 2 0.01276

11 3 0.06796

11 4 0.28067

11 5 0.63861

21 1 0.00000

21 2 0.02030

21 3 0.04908

21 4 0.28647

21 5 0.64415

31 1 0.00000

31 2 0.04043

31 3 0.05352

31 4 0.33805

31 5 0.56801

32 1 0.00000

32 2 0.04043

32 3 0.05352

32 4 0.33805

32 5 0.56801

41 1 0.00000

41 2 0.03007

41 3 0.03859

41 4 0.48841

41 5 0.44293

42 1 0.00000

42 2 0.03007

42 3 0.03859

42 4 0.48841

42 5 0.44293

43 1 0.00000

43 2 0.03007

43 3 0.03859

43 4 0.48841

43 5 0.44293

51 1 0.00000

51 2 0.04242

51 3 0.03293

51 4 0.51248

51 5 0.41217

52 1 0.00000

52 2 0.04242

52 3 0.03293

52 4 0.51248

52 5 0.41217

53 1 0.00000

53 2 0.04242

53 3 0.03293

53 4 0.51248

53 5 0.41217

54 1 0.00000

54 2 0.04242

54 3 0.03293

54 4 0.51248

54 5 0.41217

61 1 0.00000

61 2 0.07911

61 3 0.03800

61 4 0.51530

61 5 0.36759

62 1 0.00000

62 2 0.07911

62 3 0.03800

62 4 0.51530

62 5 0.36759
2008 Maricopa Co. PM10 Emission Inventory A5–11 June 2011 

[MonthVMTFraction]

sourceTypeID isLeapYear monthID monthVMTFraction

11 Y 7 0.07881

21 Y 7 0.07881

31 Y 7 0.07881

32 Y 7 0.07881

41 Y 7 0.07881

42 Y 7 0.07881

43 Y 7 0.07881

51 Y 7 0.07881

52 Y 7 0.07881

53 Y 7 0.07881

54 Y 7 0.07881

61 Y 7 0.07881

62 Y 7 0.07881

[DayVMTFraction] Source

TypeID

Month

ID

Road

TypeID dayID

Day

VMTFraction

11 7 1 5 0.78131

21 7 1 5 0.78131

31 7 1 5 0.78131

32 7 1 5 0.78131

41 7 1 5 0.78131

42 7 1 5 0.78131

43 7 1 5 0.78131

51 7 1 5 0.78131

52 7 1 5 0.78131

53 7 1 5 0.78131

54 7 1 5 0.78131

61 7 1 5 0.78131

62 7 1 5 0.78131

11 7 2 5 0.78337

21 7 2 5 0.78337

31 7 2 5 0.78337

32 7 2 5 0.78337

41 7 2 5 0.78337

42 7 2 5 0.78337

43 7 2 5 0.78337

51 7 2 5 0.78337

52 7 2 5 0.78337

53 7 2 5 0.78337

54 7 2 5 0.78337

61 7 2 5 0.78337

62 7 2 5 0.78337

11 7 3 5 0.77907

21 7 3 5 0.77907

31 7 3 5 0.77907

32 7 3 5 0.77907

41 7 3 5 0.77907

42 7 3 5 0.77907

43 7 3 5 0.77907

51 7 3 5 0.77907

52 7 3 5 0.77907

53 7 3 5 0.77907

54 7 3 5 0.77907

61 7 3 5 0.77907

62 7 3 5 0.77907

11 7 4 5 0.78337

21 7 4 5 0.78337

31 7 4 5 0.78337

32 7 4 5 0.78337

41 7 4 5 0.78337

42 7 4 5 0.78337

43 7 4 5 0.78337

Source

TypeID

Month

ID

Road

TypeID dayID

Day

VMTFraction

51 7 4 5 0.78337

52 7 4 5 0.78337

53 7 4 5 0.78337

54 7 4 5 0.78337

61 7 4 5 0.78337

62 7 4 5 0.78337

11 7 5 5 0.77907

21 7 5 5 0.77907

31 7 5 5 0.77907

32 7 5 5 0.77907

41 7 5 5 0.77907

42 7 5 5 0.77907

43 7 5 5 0.77907

51 7 5 5 0.77907

52 7 5 5 0.77907

53 7 5 5 0.77907

54 7 5 5 0.77907

61 7 5 5 0.77907

62 7 5 5 0.77907

11 7 1 2 0.21869

21 7 1 2 0.21869

31 7 1 2 0.21869

32 7 1 2 0.21869

41 7 1 2 0.21869

42 7 1 2 0.21869

43 7 1 2 0.21869

51 7 1 2 0.21869

52 7 1 2 0.21869

53 7 1 2 0.21869

54 7 1 2 0.21869

61 7 1 2 0.21869

62 7 1 2 0.21869

11 7 2 2 0.21663

21 7 2 2 0.21663

31 7 2 2 0.21663

32 7 2 2 0.21663

41 7 2 2 0.21663

42 7 2 2 0.21663

43 7 2 2 0.21663

51 7 2 2 0.21663

52 7 2 2 0.21663

53 7 2 2 0.21663

54 7 2 2 0.21663

61 7 2 2 0.21663

62 7 2 2 0.21663

11 7 3 2 0.22093

Source

TypeID

Month

ID

Road

TypeID dayID

Day

VMTFraction

21 7 3 2 0.22093

31 7 3 2 0.22093

32 7 3 2 0.22093

41 7 3 2 0.22093

42 7 3 2 0.22093

43 7 3 2 0.22093

51 7 3 2 0.22093

52 7 3 2 0.22093

53 7 3 2 0.22093

54 7 3 2 0.22093

61 7 3 2 0.22093

62 7 3 2 0.22093

11 7 4 2 0.21663

21 7 4 2 0.21663

31 7 4 2 0.21663

32 7 4 2 0.21663

41 7 4 2 0.21663

42 7 4 2 0.21663

43 7 4 2 0.21663

51 7 4 2 0.21663

52 7 4 2 0.21663

53 7 4 2 0.21663

54 7 4 2 0.21663

61 7 4 2 0.21663

62 7 4 2 0.21663

11 7 5 2 0.22093

21 7 5 2 0.22093

31 7 5 2 0.22093

32 7 5 2 0.22093

41 7 5 2 0.22093

42 7 5 2 0.22093

43 7 5 2 0.22093

51 7 5 2 0.22093

52 7 5 2 0.22093

53 7 5 2 0.22093

54 7 5 2 0.22093

61 7 5 2 0.22093

62 7 5 2 0.22093
2008 Maricopa Co. PM10 Emission Inventory A5–12 June 2011 

[HourVMTFraction] (SourceTypeID 21: Passenger Car) Source

TypeID

Road

TypeID dayID hourID

hourVMT

Fraction

21 1 5 1 0.00773

21 1 5 2 0.00526

21 1 5 3 0.00489

21 1 5 4 0.00636

21 1 5 5 0.01666

21 1 5 6 0.03683

21 1 5 7 0.05414

21 1 5 8 0.06525

21 1 5 9 0.06070

21 1 5 10 0.05269

21 1 5 11 0.05070

21 1 5 12 0.05410

21 1 5 13 0.05696

21 1 5 14 0.05867

21 1 5 15 0.06421

21 1 5 16 0.06827

21 1 5 17 0.06945

21 1 5 18 0.06952

21 1 5 19 0.05826

21 1 5 20 0.04182

21 1 5 21 0.03361

21 1 5 22 0.02915

21 1 5 23 0.02116

21 1 5 24 0.01360

21 2 5 1 0.00935

21 2 5 2 0.00655

21 2 5 3 0.00634

21 2 5 4 0.00864

21 2 5 5 0.02363

21 2 5 6 0.04783

21 2 5 7 0.05924

21 2 5 8 0.06055

21 2 5 9 0.05818

21 2 5 10 0.05502

21 2 5 11 0.05157

21 2 5 12 0.05326

21 2 5 13 0.05552

21 2 5 14 0.05931

21 2 5 15 0.06444

21 2 5 16 0.06360

21 2 5 17 0.06052

21 2 5 18 0.05806

21 2 5 19 0.05274

21 2 5 20 0.04064

21 2 5 21 0.03340

21 2 5 22 0.03082

21 2 5 23 0.02436

21 2 5 24 0.01644

21 3 5 1 0.00608

21 3 5 2 0.00395

21 3 5 3 0.00341

21 3 5 4 0.00404

21 3 5 5 0.00958

21 3 5 6 0.02566

21 3 5 7 0.04895

21 3 5 8 0.07002

21 3 5 9 0.06326

21 3 5 10 0.05034

21 3 5 11 0.04983

21 3 5 12 0.05497

21 3 5 13 0.05843

21 3 5 14 0.05802

21 3 5 15 0.06398

21 3 5 16 0.07301

21 3 5 17 0.07853

21 3 5 18 0.08117

21 3 5 19 0.06387

21 3 5 20 0.04302

21 3 5 21 0.03383

21 3 5 22 0.02745

21 3 5 23 0.01791

21 3 5 24 0.01071

21 4 5 1 0.00935

21 4 5 2 0.00655

21 4 5 3 0.00634

21 4 5 4 0.00864

21 4 5 5 0.02363

21 4 5 6 0.04783

21 4 5 7 0.05924

21 4 5 8 0.06055

21 4 5 9 0.05818

21 4 5 10 0.05502

21 4 5 11 0.05157

21 4 5 12 0.05326

21 4 5 13 0.05552

Source

TypeID

Road

TypeID dayID hourID

hourVMT

Fraction

21 4 5 14 0.05931

21 4 5 15 0.06444

21 4 5 16 0.06360

21 4 5 17 0.06052

21 4 5 18 0.05806

21 4 5 19 0.05274

21 4 5 20 0.04064

21 4 5 21 0.03340

21 4 5 22 0.03082

21 4 5 23 0.02436

21 4 5 24 0.01644

21 5 5 1 0.00608

21 5 5 2 0.00395

21 5 5 3 0.00341

21 5 5 4 0.00404

21 5 5 5 0.00958

21 5 5 6 0.02566

21 5 5 7 0.04895

21 5 5 8 0.07002

21 5 5 9 0.06326

21 5 5 10 0.05034

21 5 5 11 0.04983

21 5 5 12 0.05497

21 5 5 13 0.05843

21 5 5 14 0.05802

21 5 5 15 0.06398

21 5 5 16 0.07301

21 5 5 17 0.07853

21 5 5 18 0.08117

21 5 5 19 0.06387

21 5 5 20 0.04302

21 5 5 21 0.03383

21 5 5 22 0.02745

21 5 5 23 0.01791

21 5 5 24 0.01071

21 1 2 1 0.02131

21 1 2 2 0.01510

21 1 2 3 0.01346

21 1 2 4 0.01033

21 1 2 5 0.01242

21 1 2 6 0.01988

21 1 2 7 0.02807

21 1 2 8 0.03490

21 1 2 9 0.04138

21 1 2 10 0.04933

21 1 2 11 0.05577

21 1 2 12 0.05977

21 1 2 13 0.06401

21 1 2 14 0.06459

21 1 2 15 0.06369

21 1 2 16 0.06339

21 1 2 17 0.06375

21 1 2 18 0.06265

21 1 2 19 0.05921

21 1 2 20 0.05076

21 1 2 21 0.04447

21 1 2 22 0.04097

21 1 2 23 0.03542

21 1 2 24 0.02536

21 2 2 1 0.02131

21 2 2 2 0.01510

21 2 2 3 0.01346

21 2 2 4 0.01033

21 2 2 5 0.01242

21 2 2 6 0.01988

21 2 2 7 0.02807

21 2 2 8 0.03490

21 2 2 9 0.04138

21 2 2 10 0.04933

21 2 2 11 0.05577

21 2 2 12 0.05977

21 2 2 13 0.06401

21 2 2 14 0.06459

21 2 2 15 0.06369

21 2 2 16 0.06339

21 2 2 17 0.06375

21 2 2 18 0.06265

21 2 2 19 0.05921

21 2 2 20 0.05076

21 2 2 21 0.04447

21 2 2 22 0.04097

21 2 2 23 0.03542

21 2 2 24 0.02536

21 3 2 1 0.02131

21 3 2 2 0.01510

Source

TypeID

Road

TypeID dayID hourID

hourVMT

Fraction

21 3 2 3 0.01346

21 3 2 4 0.01033

21 3 2 5 0.01242

21 3 2 6 0.01988

21 3 2 7 0.02807

21 3 2 8 0.03490

21 3 2 9 0.04138

21 3 2 10 0.04933

21 3 2 11 0.05577

21 3 2 12 0.05977

21 3 2 13 0.06401

21 3 2 14 0.06459

21 3 2 15 0.06369

21 3 2 16 0.06339

21 3 2 17 0.06375

21 3 2 18 0.06265

21 3 2 19 0.05921

21 3 2 20 0.05076

21 3 2 21 0.04447

21 3 2 22 0.04097

21 3 2 23 0.03542

21 3 2 24 0.02536

21 4 2 1 0.02131

21 4 2 2 0.01510

21 4 2 3 0.01346

21 4 2 4 0.01033

21 4 2 5 0.01242

21 4 2 6 0.01988

21 4 2 7 0.02807

21 4 2 8 0.03490

21 4 2 9 0.04138

21 4 2 10 0.04933

21 4 2 11 0.05577

21 4 2 12 0.05977

21 4 2 13 0.06401

21 4 2 14 0.06459

21 4 2 15 0.06369

21 4 2 16 0.06339

21 4 2 17 0.06375

21 4 2 18 0.06265

21 4 2 19 0.05921

21 4 2 20 0.05076

21 4 2 21 0.04447

21 4 2 22 0.04097

21 4 2 23 0.03542

21 4 2 24 0.02536

21 5 2 1 0.02131

21 5 2 2 0.01510

21 5 2 3 0.01346

21 5 2 4 0.01033

21 5 2 5 0.01242

21 5 2 6 0.01988

21 5 2 7 0.02807

21 5 2 8 0.03490

21 5 2 9 0.04138

21 5 2 10 0.04933

21 5 2 11 0.05577

21 5 2 12 0.05977

21 5 2 13 0.06401

21 5 2 14 0.06459

21 5 2 15 0.06369

21 5 2 16 0.06339

21 5 2 17 0.06375

21 5 2 18 0.06265

21 5 2 19 0.05921

21 5 2 20 0.05076

21 5 2 21 0.04447

21 5 2 22 0.04097

21 5 2 23 0.03542

21 5 2 24 0.02536
2008 Maricopa Co. PM10 Emission Inventory A5–13 June 2011 

[AvgSpeedDistribution] (SourceTypeID 21: Passenger Car and RoadTypeID 2: Rural Restricted Access) Source

TypeID

Road

TypeID

Hour

DayID

avgSpeed

BinID

avgSpeed

Fraction

21 2 15 1 0.00000

21 2 15 2 0.00000

21 2 15 3 0.00000

21 2 15 4 0.00000

21 2 15 5 0.00000

21 2 15 6 0.00000

21 2 15 7 0.00360

21 2 15 8 0.00000

21 2 15 9 0.00000

21 2 15 10 0.06574

21 2 15 11 0.00073

21 2 15 12 0.01326

21 2 15 13 0.12481

21 2 15 14 0.35321

21 2 15 15 0.19430

21 2 15 16 0.24435

21 2 25 1 0.00000

21 2 25 2 0.00000

21 2 25 3 0.00000

21 2 25 4 0.00000

21 2 25 5 0.00000

21 2 25 6 0.00000

21 2 25 7 0.00360

21 2 25 8 0.00000

21 2 25 9 0.00000

21 2 25 10 0.06574

21 2 25 11 0.00073

21 2 25 12 0.01326

21 2 25 13 0.12481

21 2 25 14 0.35321

21 2 25 15 0.19430

21 2 25 16 0.24435

21 2 35 1 0.00000

21 2 35 2 0.00000

21 2 35 3 0.00000

21 2 35 4 0.00000

21 2 35 5 0.00000

21 2 35 6 0.00000

21 2 35 7 0.00360

21 2 35 8 0.00000

21 2 35 9 0.00000

21 2 35 10 0.06574

21 2 35 11 0.00073

21 2 35 12 0.01326

21 2 35 13 0.12481

21 2 35 14 0.35321

21 2 35 15 0.19430

21 2 35 16 0.24435

21 2 45 1 0.00000

21 2 45 2 0.00000

21 2 45 3 0.00000

21 2 45 4 0.00000

21 2 45 5 0.00000

21 2 45 6 0.00000

21 2 45 7 0.00360

21 2 45 8 0.00000

21 2 45 9 0.00000

21 2 45 10 0.06574

21 2 45 11 0.00073

21 2 45 12 0.01326

21 2 45 13 0.12481

21 2 45 14 0.35321

21 2 45 15 0.19430

21 2 45 16 0.24435

21 2 55 1 0.00000

21 2 55 2 0.00000

21 2 55 3 0.00000

21 2 55 4 0.00000

21 2 55 5 0.00000

21 2 55 6 0.00000

21 2 55 7 0.00360

21 2 55 8 0.00000

21 2 55 9 0.00000

21 2 55 10 0.06574

21 2 55 11 0.00073

21 2 55 12 0.01326

21 2 55 13 0.12481

21 2 55 14 0.35321

21 2 55 15 0.19430

21 2 55 16 0.24435

Source

TypeID

Road

TypeID

Hour

DayID

avgSpeed

BinID

avgSpeed

Fraction

21 2 65 1 0.00000

21 2 65 2 0.00000

21 2 65 3 0.00000

21 2 65 4 0.00000

21 2 65 5 0.00000

21 2 65 6 0.00000

21 2 65 7 0.00360

21 2 65 8 0.00000

21 2 65 9 0.00000

21 2 65 10 0.06574

21 2 65 11 0.00073

21 2 65 12 0.01326

21 2 65 13 0.12481

21 2 65 14 0.35321

21 2 65 15 0.19430

21 2 65 16 0.24435

21 2 75 1 0.00000

21 2 75 2 0.00000

21 2 75 3 0.00000

21 2 75 4 0.00038

21 2 75 5 0.00000

21 2 75 6 0.00790

21 2 75 7 0.00338

21 2 75 8 0.02171

21 2 75 9 0.03200

21 2 75 10 0.15639

21 2 75 11 0.13785

21 2 75 12 0.23232

21 2 75 13 0.12192

21 2 75 14 0.06243

21 2 75 15 0.09575

21 2 75 16 0.12797

21 2 85 1 0.00000

21 2 85 2 0.00000

21 2 85 3 0.00000

21 2 85 4 0.00038

21 2 85 5 0.00000

21 2 85 6 0.00790

21 2 85 7 0.00338

21 2 85 8 0.02171

21 2 85 9 0.03200

21 2 85 10 0.15639

21 2 85 11 0.13785

21 2 85 12 0.23232

21 2 85 13 0.12192

21 2 85 14 0.06243

21 2 85 15 0.09575

21 2 85 16 0.12797

21 2 95 1 0.00000

21 2 95 2 0.00000

21 2 95 3 0.00000

21 2 95 4 0.00038

21 2 95 5 0.00000

21 2 95 6 0.00790

21 2 95 7 0.00338

21 2 95 8 0.02171

21 2 95 9 0.03200

21 2 95 10 0.15639

21 2 95 11 0.13785

21 2 95 12 0.23232

21 2 95 13 0.12192

21 2 95 14 0.06243

21 2 95 15 0.09575

21 2 95 16 0.12797

21 2 105 1 0.00000

21 2 105 2 0.00000

21 2 105 3 0.00000

21 2 105 4 0.00000

21 2 105 5 0.00000

21 2 105 6 0.00010

21 2 105 7 0.00307

21 2 105 8 0.00000

21 2 105 9 0.07782

21 2 105 10 0.20747

21 2 105 11 0.22000

21 2 105 12 0.12630

21 2 105 13 0.07248

21 2 105 14 0.09291

21 2 105 15 0.07367

21 2 105 16 0.12618

Source

TypeID

Road

TypeID

Hour

DayID

avgSpeed

BinID

avgSpeed

Fraction

21 2 115 1 0.00000

21 2 115 2 0.00000

21 2 115 3 0.00000

21 2 115 4 0.00000

21 2 115 5 0.00000

21 2 115 6 0.00010

21 2 115 7 0.00307

21 2 115 8 0.00000

21 2 115 9 0.07782

21 2 115 10 0.20747

21 2 115 11 0.22000

21 2 115 12 0.12630

21 2 115 13 0.07248

21 2 115 14 0.09291

21 2 115 15 0.07367

21 2 115 16 0.12618

21 2 125 1 0.00000

21 2 125 2 0.00000

21 2 125 3 0.00000

21 2 125 4 0.00000

21 2 125 5 0.00000

21 2 125 6 0.00010

21 2 125 7 0.00307

21 2 125 8 0.00000

21 2 125 9 0.07782

21 2 125 10 0.20747

21 2 125 11 0.22000

21 2 125 12 0.12630

21 2 125 13 0.07248

21 2 125 14 0.09291

21 2 125 15 0.07367

21 2 125 16 0.12618

21 2 135 1 0.00000

21 2 135 2 0.00000

21 2 135 3 0.00000

21 2 135 4 0.00000

21 2 135 5 0.00000

21 2 135 6 0.00010

21 2 135 7 0.00307

21 2 135 8 0.00000

21 2 135 9 0.07782

21 2 135 10 0.20747

21 2 135 11 0.22000

21 2 135 12 0.12630

21 2 135 13 0.07248

21 2 135 14 0.09291

21 2 135 15 0.07367

21 2 135 16 0.12618

21 2 145 1 0.00000

21 2 145 2 0.00000

21 2 145 3 0.00000

21 2 145 4 0.00000

21 2 145 5 0.00000

21 2 145 6 0.00010

21 2 145 7 0.00307

21 2 145 8 0.00000

21 2 145 9 0.07782

21 2 145 10 0.20747

21 2 145 11 0.22000

21 2 145 12 0.12630

21 2 145 13 0.07248

21 2 145 14 0.09291

21 2 145 15 0.07367

21 2 145 16 0.12618

21 2 155 1 0.00000

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21 2 155 8 0.00000

21 2 155 9 0.07782

21 2 155 10 0.20747

21 2 155 11 0.22000

21 2 155 12 0.12630

21 2 155 13 0.07248

21 2 155 14 0.09291

21 2 155 15 0.07367

21 2 155 16 0.12618
2008 Maricopa Co. PM10 Emission Inventory A5–14 June 2011 

Source

TypeID

Road

TypeID

Hour

DayID

avgSpeed

BinID

avgSpeed

Fraction

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21 2 165 5 0.00000

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21 2 165 8 0.06439

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21 2 165 11 0.05809

21 2 165 12 0.04723

21 2 165 13 0.05493

21 2 165 14 0.07183

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21 2 175 1 0.00000

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21 2 175 4 0.00000

21 2 175 5 0.00000

21 2 175 6 0.00708

21 2 175 7 0.04834

21 2 175 8 0.06439

21 2 175 9 0.17359

21 2 175 10 0.34525

21 2 175 11 0.05809

21 2 175 12 0.04723

21 2 175 13 0.05493

21 2 175 14 0.07183

21 2 175 15 0.04109

21 2 175 16 0.08819

21 2 185 1 0.00000

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21 2 185 4 0.00000

21 2 185 5 0.00000

21 2 185 6 0.00708

21 2 185 7 0.04834

21 2 185 8 0.06439

21 2 185 9 0.17359

21 2 185 10 0.34525

21 2 185 11 0.05809

21 2 185 12 0.04723

21 2 185 13 0.05493

21 2 185 14 0.07183

21 2 185 15 0.04109

21 2 185 16 0.08819

21 2 195 1 0.00000

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21 2 195 6 0.00000

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21 2 195 8 0.00000

21 2 195 9 0.00000

21 2 195 10 0.06574

21 2 195 11 0.00073

21 2 195 12 0.01326

21 2 195 13 0.12481

21 2 195 14 0.35321

21 2 195 15 0.19430

21 2 195 16 0.24435

21 2 205 1 0.00000

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21 2 205 9 0.00000

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21 2 205 11 0.00073

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21 2 205 13 0.12481

21 2 205 14 0.35321

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21 2 215 1 0.00000

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Source

TypeID

Road

TypeID

Hour

DayID

avgSpeed

BinID

avgSpeed

Fraction

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21 2 215 9 0.00000

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21 2 215 12 0.01326

21 2 215 13 0.12481

21 2 215 14 0.35321

21 2 215 15 0.19430

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21 2 225 10 0.06574

21 2 225 11 0.00073

21 2 225 12 0.01326

21 2 225 13 0.12481

21 2 225 14 0.35321

21 2 225 15 0.19430

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21 2 235 1 0.00000

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21 2 235 8 0.00000

21 2 235 9 0.00000

21 2 235 10 0.06574

21 2 235 11 0.00073

21 2 235 12 0.01326

21 2 235 13 0.12481

21 2 235 14 0.35321

21 2 235 15 0.19430

21 2 235 16 0.24435

21 2 245 1 0.00000

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21 2 245 8 0.00000

21 2 245 9 0.00000

21 2 245 10 0.06574

21 2 245 11 0.00073

21 2 245 12 0.01326

21 2 245 13 0.12481

21 2 245 14 0.35321

21 2 245 15 0.19430

21 2 245 16 0.24435

21 2 12 1 0.00000

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21 2 12 9 0.00000

21 2 12 10 0.06574

21 2 12 11 0.00073

21 2 12 12 0.01326

21 2 12 13 0.12481

21 2 12 14 0.35321

21 2 12 15 0.19430

21 2 12 16 0.24435

21 2 22 1 0.00000

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Source

TypeID

Road

TypeID

Hour

DayID

avgSpeed

BinID

avgSpeed

Fraction

21 2 22 5 0.00000

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21 2 22 7 0.00360

21 2 22 8 0.00000

21 2 22 9 0.00000

21 2 22 10 0.06574

21 2 22 11 0.00073

21 2 22 12 0.01326

21 2 22 13 0.12481

21 2 22 14 0.35321

21 2 22 15 0.19430

21 2 22 16 0.24435

21 2 32 1 0.00000

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21 2 32 4 0.00000

21 2 32 5 0.00000

21 2 32 6 0.00000

21 2 32 7 0.00360

21 2 32 8 0.00000

21 2 32 9 0.00000

21 2 32 10 0.06574

21 2 32 11 0.00073

21 2 32 12 0.01326

21 2 32 13 0.12481

21 2 32 14 0.35321

21 2 32 15 0.19430

21 2 32 16 0.24435

21 2 42 1 0.00000

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21 2 42 3 0.00000

21 2 42 4 0.00000

21 2 42 5 0.00000

21 2 42 6 0.00000

21 2 42 7 0.00360

21 2 42 8 0.00000

21 2 42 9 0.00000

21 2 42 10 0.06574

21 2 42 11 0.00073

21 2 42 12 0.01326

21 2 42 13 0.12481

21 2 42 14 0.35321

21 2 42 15 0.19430

21 2 42 16 0.24435

21 2 52 1 0.00000

21 2 52 2 0.00000

21 2 52 3 0.00000

21 2 52 4 0.00000

21 2 52 5 0.00000

21 2 52 6 0.00000

21 2 52 7 0.00360

21 2 52 8 0.00000

21 2 52 9 0.00000

21 2 52 10 0.06574

21 2 52 11 0.00073

21 2 52 12 0.01326

21 2 52 13 0.12481

21 2 52 14 0.35321

21 2 52 15 0.19430

21 2 52 16 0.24435

21 2 62 1 0.00000

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21 2 62 3 0.00000

21 2 62 4 0.00000

21 2 62 5 0.00000

21 2 62 6 0.00000

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21 2 62 8 0.00000

21 2 62 9 0.00000

21 2 62 10 0.06574

21 2 62 11 0.00073

21 2 62 12 0.01326

21 2 62 13 0.12481

21 2 62 14 0.35321

21 2 62 15 0.19430

21 2 62 16 0.24435

21 2 72 1 0.00000

21 2 72 2 0.00000

21 2 72 3 0.00000

21 2 72 4 0.00038

21 2 72 5 0.00000

21 2 72 6 0.00790
2008 Maricopa Co. PM10 Emission Inventory A5–15 June 2011 

Source

TypeID

Road

TypeID

Hour

DayID

avgSpeed

BinID

avgSpeed

Fraction

21 2 72 7 0.00338

21 2 72 8 0.02171

21 2 72 9 0.03200

21 2 72 10 0.15639

21 2 72 11 0.13785

21 2 72 12 0.23232

21 2 72 13 0.12192

21 2 72 14 0.06243

21 2 72 15 0.09575

21 2 72 16 0.12797

21 2 82 1 0.00000

21 2 82 2 0.00000

21 2 82 3 0.00000

21 2 82 4 0.00038

21 2 82 5 0.00000

21 2 82 6 0.00790

21 2 82 7 0.00338

21 2 82 8 0.02171

21 2 82 9 0.03200

21 2 82 10 0.15639

21 2 82 11 0.13785

21 2 82 12 0.23232

21 2 82 13 0.12192

21 2 82 14 0.06243

21 2 82 15 0.09575

21 2 82 16 0.12797

21 2 92 1 0.00000

21 2 92 2 0.00000

21 2 92 3 0.00000

21 2 92 4 0.00038

21 2 92 5 0.00000

21 2 92 6 0.00790

21 2 92 7 0.00338

21 2 92 8 0.02171

21 2 92 9 0.03200

21 2 92 10 0.15639

21 2 92 11 0.13785

21 2 92 12 0.23232

21 2 92 13 0.12192

21 2 92 14 0.06243

21 2 92 15 0.09575

21 2 92 16 0.12797

21 2 102 1 0.00000

21 2 102 2 0.00000

21 2 102 3 0.00000

21 2 102 4 0.00000

21 2 102 5 0.00000

21 2 102 6 0.00010

21 2 102 7 0.00307

21 2 102 8 0.00000

21 2 102 9 0.07782

21 2 102 10 0.20747

21 2 102 11 0.22000

21 2 102 12 0.12630

21 2 102 13 0.07248

21 2 102 14 0.09291

21 2 102 15 0.07367

21 2 102 16 0.12618

21 2 112 1 0.00000

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21 2 112 3 0.00000

21 2 112 4 0.00000

21 2 112 5 0.00000

21 2 112 6 0.00010

21 2 112 7 0.00307

21 2 112 8 0.00000

21 2 112 9 0.07782

21 2 112 10 0.20747

21 2 112 11 0.22000

21 2 112 12 0.12630

21 2 112 13 0.07248

21 2 112 14 0.09291

21 2 112 15 0.07367

21 2 112 16 0.12618

21 2 122 1 0.00000

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21 2 122 3 0.00000

21 2 122 4 0.00000

21 2 122 5 0.00000

21 2 122 6 0.00010

21 2 122 7 0.00307

21 2 122 8 0.00000

Source

TypeID

Road

TypeID

Hour

DayID

avgSpeed

BinID

avgSpeed

Fraction

21 2 122 9 0.07782

21 2 122 10 0.20747

21 2 122 11 0.22000

21 2 122 12 0.12630

21 2 122 13 0.07248

21 2 122 14 0.09291

21 2 122 15 0.07367

21 2 122 16 0.12618

21 2 132 1 0.00000

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21 2 132 4 0.00000

21 2 132 5 0.00000

21 2 132 6 0.00010

21 2 132 7 0.00307

21 2 132 8 0.00000

21 2 132 9 0.07782

21 2 132 10 0.20747

21 2 132 11 0.22000

21 2 132 12 0.12630

21 2 132 13 0.07248

21 2 132 14 0.09291

21 2 132 15 0.07367

21 2 132 16 0.12618

21 2 142 1 0.00000

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21 2 142 3 0.00000

21 2 142 4 0.00000

21 2 142 5 0.00000

21 2 142 6 0.00010

21 2 142 7 0.00307

21 2 142 8 0.00000

21 2 142 9 0.07782

21 2 142 10 0.20747

21 2 142 11 0.22000

21 2 142 12 0.12630

21 2 142 13 0.07248

21 2 142 14 0.09291

21 2 142 15 0.07367

21 2 142 16 0.12618

21 2 152 1 0.00000

21 2 152 2 0.00000

21 2 152 3 0.00000

21 2 152 4 0.00000

21 2 152 5 0.00000

21 2 152 6 0.00010

21 2 152 7 0.00307

21 2 152 8 0.00000

21 2 152 9 0.07782

21 2 152 10 0.20747

21 2 152 11 0.22000

21 2 152 12 0.12630

21 2 152 13 0.07248

21 2 152 14 0.09291

21 2 152 15 0.07367

21 2 152 16 0.12618

21 2 162 1 0.00000

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21 2 162 4 0.00000

21 2 162 5 0.00000

21 2 162 6 0.00708

21 2 162 7 0.04834

21 2 162 8 0.06439

21 2 162 9 0.17359

21 2 162 10 0.34525

21 2 162 11 0.05809

21 2 162 12 0.04723

21 2 162 13 0.05493

21 2 162 14 0.07183

21 2 162 15 0.04109

21 2 162 16 0.08819

21 2 172 1 0.00000

21 2 172 2 0.00000

21 2 172 3 0.00000

21 2 172 4 0.00000

21 2 172 5 0.00000

21 2 172 6 0.00708

21 2 172 7 0.04834

21 2 172 8 0.06439

21 2 172 9 0.17359

21 2 172 10 0.34525

Source

TypeID

Road

TypeID

Hour

DayID

avgSpeed

BinID

avgSpeed

Fraction

21 2 172 11 0.05809

21 2 172 12 0.04723

21 2 172 13 0.05493

21 2 172 14 0.07183

21 2 172 15 0.04109

21 2 172 16 0.08819

21 2 182 1 0.00000

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21 2 182 3 0.00000

21 2 182 4 0.00000

21 2 182 5 0.00000

21 2 182 6 0.00708

21 2 182 7 0.04834

21 2 182 8 0.06439

21 2 182 9 0.17359

21 2 182 10 0.34525

21 2 182 11 0.05809

21 2 182 12 0.04723

21 2 182 13 0.05493

21 2 182 14 0.07183

21 2 182 15 0.04109

21 2 182 16 0.08819

21 2 192 1 0.00000

21 2 192 2 0.00000

21 2 192 3 0.00000

21 2 192 4 0.00000

21 2 192 5 0.00000

21 2 192 6 0.00000

21 2 192 7 0.00360

21 2 192 8 0.00000

21 2 192 9 0.00000

21 2 192 10 0.06574

21 2 192 11 0.00073

21 2 192 12 0.01326

21 2 192 13 0.12481

21 2 192 14 0.35321

21 2 192 15 0.19430

21 2 192 16 0.24435

21 2 202 1 0.00000

21 2 202 2 0.00000

21 2 202 3 0.00000

21 2 202 4 0.00000

21 2 202 5 0.00000

21 2 202 6 0.00000

21 2 202 7 0.00360

21 2 202 8 0.00000

21 2 202 9 0.00000

21 2 202 10 0.06574

21 2 202 11 0.00073

21 2 202 12 0.01326

21 2 202 13 0.12481

21 2 202 14 0.35321

21 2 202 15 0.19430

21 2 202 16 0.24435

21 2 212 1 0.00000

21 2 212 2 0.00000

21 2 212 3 0.00000

21 2 212 4 0.00000

21 2 212 5 0.00000

21 2 212 6 0.00000

21 2 212 7 0.00360

21 2 212 8 0.00000

21 2 212 9 0.00000

21 2 212 10 0.06574

21 2 212 11 0.00073

21 2 212 12 0.01326

21 2 212 13 0.12481

21 2 212 14 0.35321

21 2 212 15 0.19430

21 2 212 16 0.24435

21 2 222 1 0.00000

21 2 222 2 0.00000

21 2 222 3 0.00000

21 2 222 4 0.00000

21 2 222 5 0.00000

21 2 222 6 0.00000

21 2 222 7 0.00360

21 2 222 8 0.00000

21 2 222 9 0.00000

21 2 222 10 0.06574

21 2 222 11 0.00073

21 2 222 12 0.01326
2008 Maricopa Co. PM10 Emission Inventory A5–16 June 2011 

Source

TypeID

Road

TypeID

Hour

DayID

avgSpeed

BinID

avgSpeed

Fraction

21 2 222 13 0.12481

21 2 222 14 0.35321

21 2 222 15 0.19430

21 2 222 16 0.24435

21 2 232 1 0.00000

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21 2 232 3 0.00000

21 2 232 4 0.00000

21 2 232 5 0.00000

21 2 232 6 0.00000

21 2 232 7 0.00360

21 2 232 8 0.00000

Source

TypeID

Road

TypeID

Hour

DayID

avgSpeed

BinID

avgSpeed

Fraction

21 2 232 9 0.00000

21 2 232 10 0.06574

21 2 232 11 0.00073

21 2 232 12 0.01326

21 2 232 13 0.12481

21 2 232 14 0.35321

21 2 232 15 0.19430

21 2 232 16 0.24435

21 2 242 1 0.00000

21 2 242 2 0.00000

21 2 242 3 0.00000

21 2 242 4 0.00000

Source

TypeID

Road

TypeID

Hour

DayID

avgSpeed

BinID

avgSpeed

Fraction

21 2 242 5 0.00000

21 2 242 6 0.00000

21 2 242 7 0.00360

21 2 242 8 0.00000

21 2 242 9 0.00000

21 2 242 10 0.06574

21 2 242 11 0.00073

21 2 242 12 0.01326

21 2 242 13 0.12481

21 2 242 14 0.35321

21 2 242 15 0.19430

21 2 242 16 0.24435