# 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. Ma ricopa County Air Quality Department.

Revised June 2011.

APPENDIX B

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

PM-10 for the Maricopa County Nonattainment Area. Maricopa

Association of Governments.

Exhibit 2: Calculation of B enefits 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 Du st 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

# 200 8 PM 10 

# Periodic Emissions Inventory

for the

Maricopa County, Arizona, Nonattainment Area



# REVISED

June 20112008 Maricopa Co. PM 10 Emission Inventory i June 2011 

### 200 8 PM 10 

### Periodic Emission Inventory

for the Maricopa County, A rizona 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 Nonr oad 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 p rocess

................................ ................................ ................................ ................. 10

2. Point Sources

................................ ................................ ................................ ................................ 11

2.1 Introduction and scope

................................ ................................ ................................ ................ 11

2.2 Identification of point sources

................................ ................................ ................................ .... 11

2.3 Procedures for estimating emissio ns from point sources

................................ ............................ 12

2.3.1 Calculation of PM 2.5 

### 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

................................ ................................ ................................ .............. 222008 Maricopa Co. PM 10 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 ind ustrial 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 Accid ental releases

................................ ................................ ................................ ........... 72

3.5.6 Humans

................................ ................................ ................................ ............................ 72

3.5.7 Leaf blower fugitive dust

................................ ................................ ................................ . 732008 Maricopa Co. PM 10 Emission Inventory iii June 2011 

### 3.5.8 Offroad recreation vehicles fugitive dust

................................ ................................ ......... 74

3.5.9 Unpaved pa rking 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 Agricultu ral 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 emissi ons

................................ ................................ .......... 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 o utputs

................................ ................................ ................................ ... 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 Unpave d 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

................................ ................................ ................................ ............... 1222008 Maricopa Co. PM 10 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

................................ ................................ ................................ ................ 12 8

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 PM 10 

### nonattainment area.

.............. 3

Table 1.5

– 2. Land use categories used to apportion emi ssions.

................................ ......................... 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 Marico pa

County.

................................ ................................ ................................ ........................... 4

Table 1.6

– 3. Summary of annual and typical daily emissions from area sources in the PM 10



### 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

PM 10 

### NAA.

................................ ................................ ................................ .................... 5

Table 1.6

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

Mari copa County.

................................ ................................ ................................ .......... 6

Table 1.6

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

PM 10 

### NAA.

................................ ................................ ................................ .................... 6

Table 1.6

– 8. Annual and season

- day NO

x 

### 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 PM 10



### 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 PM 10 

### 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.

................................ .............. 212008 Maricopa Co. PM 10 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 emiss ions 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. Emissi on 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 com bustion.

................................ ................................ ............................... 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 resid ential 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 co mbustion in

Maricopa County.

................................ ................................ ................................ ........ 30

Table 3.2

– 16. Annual and typical daily emissions from all area

- source fuel combustion for

the PM 10 

### NAA.

................................ ................................ ................................ ............. 30

Table 3.3

– 1. NAICS codes and descriptions for chemical ma nufacturing.

................................ ...... 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 piec es 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. PM 10 

### and PM 2.5 

### 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

PM 10 

### NAA.

................................ ................................ ................................ .................. 34

Table 3.3

– 12. Annual and typical daily emissions from area

- source grain handling and

processi ng.

................................ ................................ ................................ ................... 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 product2008 Maricopa Co. PM 10 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

Ta ble 3.3

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

the PM 10 

### nonattainment area, by project type.

................................ ............................. 43

Table 3.3

– 26. Annual emissions from construction in the Pinal County portion of the PM 10



### NAA , by project type.

................................ ................................ ................................ .. 44

Table 3.3

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

the PM 10 

### NAA.

................................ ................................ ................................ ............. 44

Table 3.3

– 28. Annual and typical daily emissions from area

- source e lectric 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 unpave d 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 fr om 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 PM 10 

### NAA.

................................ ................................ ................................ ............. 48

Table 3.4

– 1. Annual an d 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 PM 10 

### NAA.

................ 51

Table 3.4

– 7. Annual and typical daily emissions from landfills.

................................ ..................... 52

Table 3.4

– 8. NH 3 

### emi ssions 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 fro m 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

PM 10 

### NAA.

................................ ................................ ................................ .................. 53

Table 3.5

– 1. Sources and input da ta 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 dat a 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 Mar icopa County and the PM 10 

### NAA.

............... 562008 Maricopa Co. PM 10 Emission Inventory vii June 2011 

### Table 3.5

– 6. Average daily emissions from wildfires in Maricopa County and the PM 10



### NAA.

................................ ................................ ................................ ............................ 56

Table 3.5

– 7. Summary of data used to estimate emissions from prescribe d 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 PM 10 

### 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

– 1 4. Annual and typical daily emissions from engine testing.

................................ ............ 60

Table 3.5

– 15. 2008 crop acreage, activity, and annual uncontrolled PM 10 

### emissions in

Maricopa County.

................................ ................................ ................................ ........ 61

Table 3.5

– 16. Annual emission s from agricultural tillage in Maricopa County and Area A

(tons/yr).

................................ ................................ ................................ ....................... 63

Table 3.5

– 17. Annual emissions from agricultural tillage in the PM 10 

### NAA (tons/yr).

..................... 63

Table 3.5

– 18. Controlled typical dail y 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

to ns/yr).

................................ ................................ ................................ ........................ 66

Table 3.5

– 21. Annual emissions from harvesting in the PM 10 

### 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 NH 3 

### 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 NH 3 

### 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 NH 3 

### 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 emi ssions 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 r ecreational 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

PM 10 

### NAA.

................................ ................................ ................................ .................. 792008 Maricopa Co. PM 10 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

PM 10 

### 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

PM 10 

### 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. Annu al emissions (tons/yr) from agricultural equipment in the PM 10 

### 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 PM 10



### 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 emis sions (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 con struction 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 r ailway 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 PM 10 

### emission factors for aircraft, by activity type.

............................ 99

T able 4.11

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

within the PM 10 

### NAA.

................................ ................................ ............................... 100

Table 4.11

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

PM 10 

### 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 emis sions (in tons/yr) from locomotives in the PM 10 

### 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 PM 10



### nonattainment area.

................................ ................................ ................................ .... 102

Table 4.13

– 1. Annual and typical daily emissions from nonroad mobile sources in Maricopa2008 Maricopa Co. PM 10 Emission Inventory ix June 2011 

### County.

................................ ................................ ................................ ....................... 103

Table 4.13

– 2. Annual and typical daily emi ssions from nonroad mobile sources in the PM 10



### 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 em issions by facility type and

vehicle class in the PM 10 

### 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 uncontr olled 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 averag e 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 aver age 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 NO

x 

### in the PM 10 

### NAA and Maricopa

County, by month.

................................ ................................ ................................ ...... 129

Table 6.4

– 2. Monthly biogenic emissions of NO

x 

### in the PM 10 

### NAA and Maricopa County.

........ 130

Table 6.5

– 1. Daily mean and annual total NO

x 

### emissions from biogenic sources.

........................ 130

List of Figures

Figure 1.4

– 1. Map of Maricopa County and the PM 10 

### nonattainment area.

................................ ........ 2

Figure 2.7

– 1. Data flow for annual point sourc e emission inventory reporting.

............................... 16

Figure 6.3

– 1. Mask of the PM 10 

### 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. Boundari es of the PM 10 

### 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 tem perature (top panel) and

downward short wave radiation (bottom panel) in 2008.

................................ .......... 128

Figure 6.4

– 1. Monthly emissions of NO

x 

### in Maricopa County (pink solid line, abbreviated

as “MC”) and the PM 10 

### NAA (blue solid line, abbreviated as “NA”).

...................... 1292008 Maricopa Co. PM 10 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 Instr uctions 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 Act ivities, 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 Ref erences

................................ ................................ ................................ ....... 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

S tandardized Windblown Dust Emissions

................................ ...................... A 4

– 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

– 62008 Maricopa Co. PM 10 Emission Inventory 1 June 2011 

## 1. Introduction

1.1 Overview

This 2008 periodic PM 10 

### 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 seri ous

nonattainment for PM 10



### .

PM 10 

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

inven tory includes primary emissions of PM 10 

### and PM 2.5 

### as well as three particulate matter

precursors: nitrogen ox ides (NO

x 

### ), sulfur dioxides (SO

x 

### ) and ammonia (NH 3 

### ). The inventory

provides emis sion 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

indep endent 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 PM 10 

### Emissions Inventory for Maricopa County. P oint sources

an d 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 s ome area and nonroad mobile source categories

. Ta ble 1.2

– 1

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

which are described in the respective chapters.

Table 1.2

– 1. Chapter au thors and QA/QC contacts for this report

. Chapter Author(s) QA/QC contac t s

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) 25 4

- 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 Mo bile

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

- 67902008 Maricopa Co. PM 10 Emission Inventory 2 June 2011 

### 1.3 Temporal scope

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

the Maricopa County PM 10 

### nonattainment area (NAA)

.

1.4 Geographic scope

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

PM 10 

### nonattainment ar ea. Maricopa County encompasses approximately 9,2 23 square miles of

land area, while the Maricopa County PM 10 

### nonattainment area is approximately 2,880 square

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

County an d the PM 10 

### n onattain ment area is provided in Figure 1. 4

– 1

.

Figure 1.4

– 1. Map of Mar icopa County and the PM 10 nonattainment area

.2008 Maricopa Co. PM 10 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 calculate d using demo graphic 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 nonattainm ent area

and vice versa. (For example, county

- level emis sions from residential natural gas usage in Mari

copa 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, a long with the data sources used.

1. 5 .1 Demographic p rofile

The demographic data provided by MAG included population

, employment data , and single

family/multi

- family splits for calendar year 200 8 , for both Maricopa County and the P M 10 

### non

attain ment area. Table 1.5

– 1 provides an overview of the demographic data used in this report.

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

emissions within the PM 10 

### NAA from county

- level calcula tions. It is important to note, how

ever, that the nonattain ment area includes a portion of Pina l County, AZ (Apache Junction) as

shown in Figure 1.4

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

total popu lation), the multi plier 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 Mari copa County and the PM 10 nonattainment area.

Demographic variable Maricopa

County PM 10 NAA Percent within

PM 10 NAA

Total resident population 4

, 026

, 000 4,024,530 99

. 9 6 %

Total non

- resident population 253,760 272,610 10 7

. 43 %

Total population: 4,279,76 0 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 9 8

. 52 %

Other employment 191,770 189,010 98.56 %

Constructi on 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 20 10 ) . The draft 2009 land use data was

assumed to be representative of 2008 . Table 1.5

– 2 presents a summary of the land use cate gories

and acreage s used to develop emissions estimates f or this inventory.2008 Maricopa Co. PM 10 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 PM 10

NAA Percen tage

within PM 10

NAA

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

Passive /r estricted open space (e.g., mountain preserves) 2, 37 3 ,545 302,999 12.77 %

Lakes 12,525 9

, 510 75.93%

Agriculture 295,509 1 30,445 44.14 %

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



### 1.6 Emissions overview by source category

1.6.1 P oint s ources

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

pollu tion into the air such as power plants, industrial processes and large manufac turing

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 sou rces in Maricopa

County and the PM 10 

### nonattainment area, respectively. A detailed breakdown of emissions

calcu lations for all point sources is contained in Chapter 2.

Table 1.6

– 1. Summary of annual and typical dai ly emissions from point sources in Maric opa County.

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

Geographic Area PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 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

PM 10 NAA 149.84 132.94 1,317.85 28.76 132.18 84 1.2 747.7 7,2 5 4. 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 s tationary sources that were not identified as point sources in this report have

been included in the area source inventory. Examples of area sourc e categories include residen

tial 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 PM 10 

### nonattainment area , respectively. A detailed

break down 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 PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 19,0 48.2 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 91,223.52008 Maricopa Co. PM 10 Emission Inventory 5 June 2011 Table 1.6

– 3

. Summary of annual and typical daily emissions from area sources in the PM 10 NAA.

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

Category PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 16 1,147.8 46,738.0 83,325.3 7,694.7 61,982.0



### 1.6.3 Nonroad mobile sources

Nonroad mobile sources include off

- high way vehicles and engines that move or are moved with

in a 12

- month period. Tables 1.6

– 4 and 1.6

– 5 summarize annual and season

- day emissions f rom

nonroad mobile sources, for Maricopa County and the PM 10 

### nonattainment area, respec tively. A

detailed breakdown of emissions calculations for each source ca tegory is contained in Chapter 4

.

Table 1.6

– 4

. Annual and typical daily emissions from nonroa d mobile sources in Maricopa County.

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

Category PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 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 187.91 181.4 2 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

mob ile sources: 2,038.46 1,959.9 6 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 PM 10 NAA.

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

Category PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 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 7 22.4 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 183.80 177.6 1 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 1,856.1 8 23,793.26 367.42 128.87 12,275.2 11,81 2.0 149,537.7 2,030.5 852.9



### 1.6.4 O nroad mo bile sources

Emission s from o nroad mobile sources were calculated for the PM 10 

### nonattainment area located

primarily within Maricopa County

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

break out of emissions calculations for each area source cate gory is contained in Chapter 5.

Tables 1.6

– 6 and 1.6

– 7 summarize annual and typical daily emissions from o nroad mobile

sources in Maricopa County and the PM 10 

### non attainment area, respectively.2008 Maricopa Co. PM 10 Emission Inventory 6 June 2011 Table 1.6

– 6

. Annual and average daily emissions from all o nroa d mobile sources in Maricopa County.

Emission

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

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 Exhaust, tire wear,

and brake wear 3,295.74 2,417.89 75,033.9 314.5 1,294.1 18,009.2 13,2 12.4 410,021.3 1,718.2 7,072.1

Paved road

fugitive dust 7,227. 77 1,912.4 2

— — — 39

, 496.0 10,450.4

— — — Unpaved road and

alley fugitive dust 12,358.2 0 1,233.6 0

— — — 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 o nroad mobile sources in the PM 10 NAA.

Emission

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

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 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 6,694.2 2 1,774. 76

— — — 36,580.5 9,698.1

— — — Unpaved road and

alley fugitive dust 11,710.7 0 1 ,169.0 0

— — — 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 PM 10 

### 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 Nat ional 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 PM 10 

### nonattainment area. Annual and daily NO

x 

### emiss ions from biogenic

sources are shown in Table 1.6

– 8 for Maricopa County and the PM 10 

### nonattainment area.

Tab le 1.6

– 8

. Annual and season

- day NO

x emissions from biogenic sources.

Geographic area Annual emissions

(tons/yr) Typical daily emissions

(lbs/day)

Maricopa County 896.27 4,890.0

PM 10 NAA 332.77 1,815.3



### 1.6.6 Summary of a ll s ource categories

Tables 1.6

– 9 and 1.6

– 1 0 provide summary totals of annual and typical daily emissions from all

emission sources in Maricopa County and the PM 10 

### nonattainment ar ea, respectively.2008 Maricopa Co. PM 10 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)

PM

10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

Point Sources 601.27 555.15 2,20 4.9

1 81.15 279.06 3,323.2 3,069.1 12,1 51.5 449.3 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 14 9.3 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 55.2 0 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

Comm ercial 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 porta bles 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 1,73 1.34 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 42 5.4 132.9 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

Wildfi res 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

Airc raft 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 2 9.7

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. 52008 Maricopa Co. PM 10 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)

PM

10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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

Construct ion 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

Ai rcraft 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 f ugitive 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 11,812.7 100,720.42008 Maricopa Co. PM 10 Emission Inventory 9 June 2011 Table 1.6

– 1 0

. Annual and typical daily emissions from all sources in the PM 10 nonattain ment area.

Section Annual emissions (tons/yr) Typical daily emission s (lbs/day)

PM

10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

Point Sources 149.84 132.94 1,31 7.8 5 28.76 132.18 841.2 747.7 7,2 5 4. 3 158.2 727.0

Area Sources:

Fuel combustion

Industrial natural gas 30.70 30.70 573.79 2.41 1 2.66 196.8 196.8 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 ba tch, 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 b urning 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 7 31.03 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 relea ses 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 61,982.02008 Maricopa Co. PM 10 Emission Inventory 10 June 2011 Table 1.6

– 1 0 (cont’d ). Annual and typical daily emissions from all sources in the PM 10 nonattainment area.

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

Section PM 10 PM 2.5 N O

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 gar den

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 mainten ance

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 200 8

PM 10 

### 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 di scuss the draft inventory. No formal comments were

received during the 30

- day public comment period.2008 Maricopa Co. PM 10 Emission Inventory 11 June 2011 

## 2. Point Sources

2.1 Introduction and scope

This inventory of PM 10 

### and related polluta nts 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 PM 10 

### nonattainment area (NAA)

as a commitment under the current PM 10 

### State Implementation Plan (SIP), the federal Air Emis

sion Reporting Requirements ( A ERR) rule requires that state and local agencies prepare emis

sions estimates on a county basis, and submit data electronically to the US EPA for inclusion in

the National Emiss ion Inventory (N EI) for 2008 . This inventory is being developed concurrently

with similar inventories for CO and ozone precursors (VOC, NO

x 

### , and CO), as part of Maricopa

County's requirements under the respective SIPs.

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

definition of a “poin t 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 pa rt 70 for the pollutants for which reporting is

required, i.e., CO, VOC, NO

x 

### , SO 2 

### , PM 2.5 

### , PM 10 

### , lead and NH 3 

### but without regard

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

report ing point sources, which in turn will faci litate elimination of over laps and

gaps in estimating point source emissions, as compared to nonpoint source emis

sions. 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 pur

poses to consider point sources with 25 miles of the nonattainment area boundary. No additional

point sources met this reporting threshold.

Several t ables have been constructed to provide the point source emissions a nd category totals.

Table 2.2

– 1 provides an alphabetical list ing of all point sources and their locat ion. Table 2.4

– 1

shows the 2008 annual and typical day emissions of PM 10 

### , PM 2.5 

### , NO

x 

### , S O

x 

### and NH 3 

### for those

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

Table 2.6

– 1 summarize s point source emissions by source category for the county and PM 10 

### non

attain ment area . Note that totals shown i n 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 Mari

copa County through its electronic permit sys tem database, EMS , and the 2008 annual emissions

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

sources using the definition described in S ection 2.1

. There are no additional point sources

within the 25

- mi le boundary around the PM 10 

### nonattainment area with permits issued by the

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

Environ mental Quality (ADEQ) retains permitting authority for a limited number of industrial2008 Maricopa Co. PM 10 Emission Inventory 12 June 2011 

### so urce 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 list ing of all point sources, including a unique business

identifi cation 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 Tol leson 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 Goo drich 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

– 56t h Fighter Wing 14002 W Marauder St Glendale 85309

62 33711 Mastercraft Cabinets Inc 3 05 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 363r d 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 i s outside the PM 10 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 tele phone contacts with sources.

For most of the sources, material balance methods were used for determining emissions. Emis

sions were estimated using the emission factors from AP

– 42, source tests, engineering calcula

tions, or manu facturers' specification s.

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

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

control devices, operating sch edules, and process

- level infor ma tion 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 mus t sub mit 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 F actor Information and REtrieval ( web FIRE )2008 Maricopa Co. PM 10 Emission Inventory 13 June 2011 

### software, and other EPA docu mentation. Control efficiencies are determined by source tests

when avail able, or by AP

– 42 factors, engineering calculations, or manufacturers' specifications.

MCAQD has conducted an nual emissions surveys for permitted facili ties 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 PM 2.5 

### emissions

For all count y

- permitted sources that submitted an annual emission inventory report, all process

level emissions for PM 10 

### , NO

x 

### , SO

x 

### , and NH 3 

### were calculated for each facility. Actual emissions

for these pollutants were calculated using reported emission factors (from A P

– 42 or source test

results) and reflecting any control devices installed. PM 2.5 

### 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 PM 2.5 

### , using EPA

- recommended emission factors and

typical control efficiencies.

2. For processes with no PM 10 

### controls, emission factors for PM 2.5 

### published by the

California Air Resources Board (CARB, 200 4) were used where available.

3. For all other processes (where neither of the above resources provided guidance), PM 2.5 

### was assumed equal to PM 10 

### as a conservative estimate.

2.3.2 Application of rule effectiveness

Rule effectiveness reflects the actual abi lity 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 per

cent effectiv e for some source categories. Rule effectiveness ( “ RE ” ) is applied to those sources

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

and control efficiency estimates.

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

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

**•** For manually controlled processes that are regulated under Maricopa County Rule 316 (Non

metallic Mineral Processing)

, the analysis showed an ove rall rule effectiveness of 65.44 %

.

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

de vice, RE c alculations were performed separately for Title V and non

- Title V sources.

O verall RE values of 90.94 % (for Title V p rocesses) 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 PM 10 

### nonattainment area. Sources for which rule effectiveness has been

applied (for PM 10 

### emissions) are noted. Values of “0.00” and “0.0” for annual and daily emis

sions denote a value below the level of significance (0.005 tons/yr and 0.05 lbs/day,

respectively).2008 Maricopa Co. PM 10 Emission Inventory 14 June 2011 Table 2.4

– 1. Annual an d typical daily point source emissions, by facility.

Annual emissions (tons/yr) Typical da il y (lbs/day)

ID # Business name PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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

– 56t h 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 † 116.35 116.1 1 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 0.2 9 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 PM 10 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 emission s

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 acqui ring 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 offsetti ng, 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 PM 10 

### , NO

x 

### , and SO

x 

### . Only one

previously operational facility maintains emission reduction cre dits 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 

### PM 10 

### NO

x 

### SO

x

1151 Freescale Semiconductor, Inc. (formerly Motorola Mesa) 1 .80 8.0 0 0.162008 Maricopa Co. PM 10 Emission Inventory 15 June 2011 

### 2.6 Summary of point source emissions

Table 2.6

– 1 provide s an overview of source category contributions to point source emissions for

Maricopa County and the PM 10 

### nonattainment area.

Table 2.6

– 1. A nnual and typical daily point source emis sions (including emission reduction credits)

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

Geographic Area PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 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

PM 10 NAA 149.8 4 132.94 1,317.85 28.76 132.18 841.2 747.7 7,2 5 4. 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 pol lutant

emis sion 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 m ethods 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 instruct ions is included as Appendix 2 ). The EI Unit

asks sources to verify and update the data. The EI Unit a lso holds workshops from February

through April to assist businesses in completing EI forms.

The general data flow for data collection an d inventory preparation is shown in Figure 2.7

– 1.2008 Maricopa Co. PM 10 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 recei pts are issued for emissions fees

paid. The data are input “as received” into the department's data base. During data entry, a vari

ety 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 cod es 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

followin g:

**•** Comparing reported emission factors to SCC reference lists

**•** Comparing reported emission factors to material name reference list2008 Maricopa Co. PM 10 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 tech nical 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. C onfidential business informa

tion (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 reasonable ness, and assured that all

point sources had been identified and that the methodology applied to calculate emissions was

appropri ate and that the calculations were correct. Other reasonableness checks were conducted

by recalculating emissions using metho ds other than those used to make the initial emissions cal

cu lations and then comparing results. QA was conducted by checking all emissions reports sub

mitted to MCAQD for the year 200 8 for missing and questionable data and by checking the

accu racy and reasonableness of all emissions calculations made for such reports. Notes con

cerning follow

- up calls and corrections to calculations were documented on each 200 8 annual

emissions report.

The QA point source coordinator reviewed and checked calcu lations , 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 Reportin g Requirements . 73 Fed. Reg. 76539. Available at: .

http://www.epa.gov/ttn/chief/aerr/final_published_aerr.pdf

.2008 Maricopa Co. PM 10 Emission Inventory 18 June 2011 

### This page intentionally blank.2008 Maricopa Co. PM 10 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 Environ

mental Management System (EMS) data base, and previous SIP inven tories, were evaluated to

develop the list of area

- source categories for inclusion. Some source categ ories were deemed

“insignificant” because there are no large production facilities and/or very few small sources, and

theref ore 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 PM 10 inventory.

SCC Code Category Description Section

Fuel combustion:

2102006000 Industrial natural gas 3.2.1

2102004000 Industrial fuel oil 3.2.2

210300600 0 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 Ch emical 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

2325 000000 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 c onstruction 3.3.9

2311020000 Commercial c ons truction 3.3.9

2311030000 Road c onstruction 3.3.9

n/a Other c onstruction 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 Indust rial 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 Ot her industrial waste disposal 3.4.5

Miscellaneous area sources:

2810001000 Wildfires 3.5.1.1

2810014000 Prescribed fires 3.5.1.22008 Maricopa Co. PM 10 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 gin ning 3.5.2.4

2801700000 Fertilizer application 3.5.2.5

28 10 0 6 0000 Livestock 3.5.3

28 1006 0000 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 cond ucting 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 catego ries (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 e missions 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 specifi c 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 se ven 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

emissi ons 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 nat ural 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. PM 10 Emission Inventory 21 June 2011 

### Area

- source emissions for wood and fuel oil combustion were calculated from Arizona state

level sales and con sumption data as described in the following subsections. Area

- source emis

sions from coal and liquid petroleum gas were not calculated, as emissions from these categories

were determin ed 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 cat egory, within the county in 2008 . Area

- source industrial

natural g as usage for the county is based on the reported total volume of natural gas sold to

indus trial sources, minus natural gas used by industrial point sources:

County area

- source = Total reported industrial

– Industrial point source

industrial natural gas u sage natural gas sales natural gas usage

= 8,576.57 MMCF

– 516.15 MMCF

= 8,060.4 2 MMCF



### Natural gas is used for both external combustions (boilers and heaters) and internal combustion

(generators), each of which have different emission factors. Thus t he 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 indus

trial area sources in 2008

.

Annual emission s for the county and the PM 10 

### nonattainment area were calcula ted by multiply

ing natural gas usage by the respective AP

- 42 emission factors for external and internal com

bustion, as in this example for PM 10 

### emissions from external natural gas combustion:

PM 10 emissions from

= External industrial natural × PM 10 emission factor for ÷ 2,000 lb s /ton

external natural gas gas usage (MMCF) external natural gas

combustion com bustion (lb/MMCF)

= 7,934.68 × 7.6 ÷ 2,000

= 30.15 tons PM 10 /yr

Table 3.2

– 2. Natu ral gas usage, e mission factors

, and annual emissions from area

- source industrial natural

gas combustion, by combustion type.

Type of

Combustion % of

total Natural gas

us e (MMCF) Emission factors (lb/MMCF) Annual emissions (tons/yr)

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 12 5.74 10.0 10.0 2840 0.6 n/a 0.6 3 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 emissio ns for the county were calcula ted by dividing annual emissions by the

number of days that activity occurs throughout the year:

T ypical daily PM 10 emissions

= Annual PM 10 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 PM 10 /day2008 Maricopa Co. PM 10 Emission Inventory 22 June 2011 

### Annual and typical daily emissions within the PM 10 

### nonattainment area were calcula ted by

applying the ratio of industrial employment in the nonattainment area to county

- level emission

calculati ons. (See Section 1.5.1 for a discussion of the employment data used).

Emissions from area

- source = Annual county PM 10 × NAA:County industrial employment ratio

industrial natural gas combustion emissions (tons/yr) in the PM 10 NAA

= 30.78 × 0.9974

= 3 0.70 tons PM 10 /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 PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 Maricopa Co unty 30.78 30.78 575.29 2.42 12.70 197.3 197.3 3,687.7 15.5 81.4

PM 10 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 calcula ted by a multi

- step

pr ocess which allocates Arizona state

- level industrial fuel oil sales as reported by the U.S.

Department of Energy, Energy Information Administration (US DOE, 20 10a ) to Maricopa

County.

To derive industrial fuel oil usage in Maricopa County, reported Arizon a state

- level sales of

high

- s ulfur 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 c onditions.

State industrial fuel oil sales

= Reported state total

– Reported state high

- sulfur diesel sales

other than high

- sulfur diesel industrial fuel oil sales

(in thou sand gallons, or Mgal)

= 137,044 Mgal

– 224 Mgal

= 136,820 Mgal/yr



### Arizona sta te 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 (20 10a ) to estimate annual Maricopa County

- lev el 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 × 0.70 07

= 95,869.77 Mgal/yr



### To a void 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 ar ea sources:2008 Maricopa Co. PM 10 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

– 136.8 2 Mgal

= 84,136.09 Mgal/yr



### Industrial fuel oil is used for both external combustions (boilers, heaters) and internal combus

tion (generators), each of which have different emission factors. Thus the area

- source industrial

fuel oil sales derived above mu st be apportioned between these two categories. This apportion

ment was based on the percentages of external and internal fuel oil combustion reported by all

industri al area sources surveyed in 2008 (shown in Table 3.2

– 4 below).

Annual emissions for the county and the PM 10 

### nonattainment area were calcula ted by multi

plying industrial fuel oil sales by the respective AP

- 42 emission factors for external and internal

combustion, as in this example for PM 10 

### emissions from external fuel oil combustion:

Annual PM 10 emissions

= External industrial fuel × PM 10 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 PM 10 /yr

Table 3.2

– 4. Emissi on 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)

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 emissio ns for the county were calcula ted by dividing annual emissions by the

number of days during which activity occurs throughout the year, as recommended by EIIP

guidance (US EPA, 2001a):

Ty pical daily PM 10 emissions

= Annual PM 10 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 PM 10 /day



### Annual and typical daily emissions in the PM 10 

### nonattainment area were calcula ted by applying

the ratio of industrial employment in the nonattain ment area to county

- level emission

calculations. (See Section 1.5.1 for a discussion of the employment data used).

PM 10 NAA emissions from area

= Annual county × NAA:County industrial employment ratio

source industrial fuel oil combustion PM 10 emissions

= 458.79 tons/yr × 0.9974

= 457.60 tons PM 10 /yr2008 Maricopa Co. PM 10 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 PM 10 PM 2.5 NO

x SO

x NH 3 PM 1 0 PM 2.5 NO

x SO

x NH 3 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

PM 10 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 ga s suppliers in Maricopa County were surveyed to gather information on the volume

of natural gas distributed, by user cat egory, within the county in 2008 . Area

- source commercial

and institutional (C&I) natural gas usage for the county is based on the repor ted 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 MM CF



### 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 categor ies. 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 calcula ted by multiplying natural gas usage by the

respective AP

- 42 emissi on factors for external and internal combustion, as in this example for

PM 10 

### emis sions from external natural gas combustion:

Annual PM 10 emissions

= External C&I natural × PM 10 emission factor for ÷ 2,000 lbs/ton

from external natural gas gas usage (MMC F) external natural gas

combustion com bustion (lb/MMCF)

= 17,130.07 × 7.6 ÷ 2,000

= 65.09 tons PM 10 /yr

Table 3.2

– 6. Emission factors and annual emissions from area

- source commercial/institutional natural gas

combustion, by combustion type.

Combusti on

type % of

total C&I natural

gas usage

(MMCF) Emission factors (lb/MMCF) Annual emissions (tons/yr)

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 1 0.0 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 calcula ted by dividing annual emissions by the

number of days that activity occurs throughout the year:

T ypical daily PM 10 emissions

= Annual PM 10 emissions ÷ (days/week × w ks/yr) × 2,000 lbs/ton

from comm./inst. natural gas (tons/yr)

= 66.54 ÷ (6 × 52) × 2,000

= 426.54 lbs/day2008 Maricopa Co. PM 10 Emission Inventory 25 June 2011 

### Annual and typical daily emissions within the PM 10 

### nonattainment area were c alcula ted by

apply ing 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 employ

ment data used).

PM 10 NAA e missions from area

- sour ce = Annual county PM 10 emissions × NAA:County C&I employment ratio

comm./ inst. natural gas combustion (tons/yr)

= 66.54 × 0.9949

= 6 6

. 20 tons PM 10 /yr

Table 3.2

– 7. Annual and typical daily emissions from area

- source commercial/institutional natural ga s

combustion.

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

Geographic area PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 Maricopa County 66.54 66.54 1,267.11 5.23 4.20 426.5 426.5 8,122.5 33.5 26.9

PM 10 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

calcula ted by a multi

- step process of allocating Arizona state

- level C&I fuel oil sales as r eported

by the U.S. Department of Energy, Energy Information Administration (US DOE, 20 10 b) to

Maricopa County.

To derive commercial/institutional fuel oil usage in Maricopa County, reported Arizona state

level sale s of high

- sulfur diesel for 2008 are fir st 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 gall ons, 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 (20 10 a ) to estimate annual Maricopa County

level commercial/institutional fuel oil sales, as follows:

Maricopa Count y = 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. PM 10 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 ex ternal 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

base d on the percentages of external and internal fuel oil combustion reported by all commercial

and institution al area sources surveyed in 2008 (shown in Table 3.2

– 8 below).

Annual emissions for the county were calcula ted by multiplying comm./inst. fuel oil sales by the

respective AP

- 42 emission factors for external and internal combustion, as in this example for

PM 10 

### emissions from external fuel oil combustion:

Annual PM 10 emissions from

= External C&I fuel oil × PM 10 emission factor for external ÷ 2,000 l bs/ton

external fuel oil combustion sales (Mgal) fuel oil combustion (lb/Mgal)

= 20,321.18 × 1.08 ÷ 2,000

= 10.97 tons PM 10 /yr

Table 3.2

– 8. Emission factors and annual emissions from area

- source commercial/institutional fuel oil

combustion, by combust ion type.

Combustion

type % of

total C&I fuel oil

sales (Mgal) Emission factors (lb/Mgal) Annual emissions (tons/yr)

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 calcula ted by dividing annual emissions by the

number of days activity occurs throughout the year, as recommended by EIIP guidance (US

EPA, 2001a):

Typical daily PM 10 emissions

= Annual PM 10 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 PM 10 

### nonattainment area were calcula ted by

apply ing 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).

PM 10 NAA emissions from area

= Annual county PM 10 × NAA:County C&I employment ratio

source C&I fuel oil combustion emissions (tons/yr)

= 224.14 × 0.9949

= 223.00 tons PM 10 /yr2008 Maricopa Co. PM 10 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 PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 Maricopa County 224.14 224.14 3,273.40 2 71.27 8.13 1,436.8 1,436.8 20,983.3 1,738.9 52.1

PM 10 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 vol ume

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 summar ized in the table below (US EPA,

1998a), as follows:

Table 3.2

– 10. Residential natural gas combustion emission factors.

Emission Factors (lb/MMCF)

PM 10 PM 2.5 NO

x SO

x

7.6 7.6 94 0.6

Annual PM 10 emissions

= Annual sales of r esidential × PM 10 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 PM 10 /yr



### Typical daily emissions were calcula ted by dividing annual emissions by the nu mber of days

(36 6 ) that activity occurs for residential natural gas combustion, as follows:

Typical daily PM 10 emissions from

= Annual PM 10 emissions × 2,000 lbs/ton ÷ days/yr

residential natural gas combustion

= 61.75 tons/yr × 2, 000 ÷ 36 6

= 3 37

. 4 lb s PM 10 /day



### Annual and typical daily residential natural gas emissions in the PM 10 

### nonattainment area were

calcula ted by multiplying county

- level emissions by the percentage of total residential popu

lation in the PM 10 

### nonattainment area as follows:

Annua l PM 10 emissions

= A nnual PM 10 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 PM 10 /yr

Table 3.2

– 11. Annual and typical daily emissions from r esidential natural gas combustion.

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

Geographic area PM 10 PM 2.5 NO

x SO

x PM 10 PM 2.5 NO

x SO

x Maricopa County 61.75 61.75 763.81 4.88 33 7

. 5 33 7

. 5 4,1 73

. 8 26. 6

PM 10 NAA 61.73 61.73 763.51 4.87 33 7

. 3 33 7

. 3 4,1 72

. 2 26. 62008 Maricopa Co. PM 10 Emission Inventory 28 June 2011 

### 3.2.6 Residential wood combustion

Area

- source emissions from residential wood combustion were calcula ted based on the amount

of wood burned in fireplaces and woodstoves in Maricopa County, as recommended by EIIP

guidance (US EPA, 200 1 b ). Residential wood combustion in the c ounty is estimated by multi

ply ing data on statewide residential wood combustion usage from the US Department of Energy

(US DOE, 2010 c ) by the ratio of county to state households that report use of wood for heating

from the US Census Bureau (2010 b ). The latest available data on residential wood use for

house hold heating from the US Department of Energy is for the calendar year 2007. Since all

fireplaces in homes con structed since 1999 are required by Arizona sta tute 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 usag e (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 dens ity of the wood used (US EPA,

2001 b ). 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. ft 3 wood/cor d × Wood density (lbs/ ft 3 ) ÷ 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 calcula ted by multiplying the tons of

wood used by the PM 10 

### emission facto r for residential woodstoves and fireplaces from Table

2.4

– 1 of US EPA (2001 b ).

Annual PM 10 emissions from residential

= Residential wood usage × PM 10 emission factor ÷ 2,000 lbs/ton

wood combustion (tons/yr) (tons) (lbs/ton)

= 26,682 × 34.6 ÷ 2,000

= 461.59 tons PM 10 /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)

PM 10 PM 2.5 * NO

x SO

x PM 10 PM 2.5 * NO

x SO

x 26,681.76 34.6 32.2 2.6 0.4 461.59 429.28 34.69 5.34

*PM 2.5 is assumed to be 93% of PM 10 (Houck and Tiegs, 1998).



### Typical daily emissions were calcula ted 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 record ed. Assuming that no wood burning activity took place during those

months, it is assumed that all r esidential wood burning occurred during the remaining 213 days2008 Maricopa Co. PM 10 Emission Inventory 29 June 2011 

### of the year. Thus, typical daily emissions were calcula ted by dividing annual emissions by th e

number of days residential wood burning occurred, as follows:

Typical daily PM 10 emissions

= Annual PM 10 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 PM 10 /day



### Annual and typical daily emissions within the PM 10 

### 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 t he county. See Section 1.5.1 for a further

discussion of the population used.

A nnual emissions from resi dential wood

= County a nnual emissions × NAA:county residential population ratio

combustion in the PM 10 NAA (tons/yr)

= 461.59 × 0 .9996

= 461.41 t ons PM 10 /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 PM 10 PM 2.5 NO

x SO

x PM 10 PM 2.5 NO

x SO

x Maricopa County 461.59 429.28 34.69 5.34 4 ,334.2 4,030.8 325.7 50.1

PM 10 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 i n 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 (2010 c ):

Maricopa County residential

= Arizona reside ntial × 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 u sing AP

- 42 emission factors (shown below in

Table 3.2

– 14) a nd data on heating degree days and residential housing units described in Section

3.2.6 . A nnual 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 Em ission factors

(lb/Mgal) Annual emissions

(tons/yr) Typical daily emissions

(lbs/day)

PM 10 PM 2.5 NO

x SO

x PM 10 PM 2.5 NO

x SO

x PM 10 PM 2.5 NO

x SO

x 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

PM 10 NAA 0.4 0.4 18 7.1 0.01 0.01 0.25 0. 10 0.1 0.1 2.3 0.92008 Maricopa Co. PM 10 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 PM 10 

### 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)

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 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 2 24.14 224.14 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 PM 10 NAA.

Fuel combustion type Annual emi ssions (tons/yr) Typical daily emissions (lbs/day)

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 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 3 37.3 337.3 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 f rom a subset of sources, and county

- level employment data from the US

Census Bureau (2010 a ) 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.

NA ICS

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 ,4642008 Maricopa Co. PM 10 Emission Inventory 31 June 2011 

### T here were no point sources in this category . A rea

- source employment estimate were used to

“scale up” emissions reported from those facilities surveyed in 2008 as follows:

Area

- source PM 10 = Emissions from surveyed area sources

emissions from Employment at surveyed area sources × Total area

- source employment

chemical mfg.

= 35.71 tons of PM 10 /yr

1,041 employees × 5,464 employees

= 187.43 tons PM 10 /yr



### Typical daily emissions were calcula ted in the same method as annual emissions, only using

su rveyed daily emissions instead of annual totals. Annual and typical daily emissions for the

PM 10 

### 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.)

PM 10 emissions from area

- source = Annual Maricopa County emissions × NAA:county ratio of

chemical mfg. in the PM 10 NAA (tons/yr) (tons/yr) industrial employment

= 187.43 × 0. 9974

= 18 6.94 tons PM 10 /yr



### Table 3.3

– 2 summarizes annual and typical daily emissions from chemical manufacturing in

both Maricopa County and the PM 10 

### nonattainment area.

Table 3.3

– 2. Annual and typical daily emissions from area

- source chemical manufacturing.

Ann ual emissions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM 10 PM 2.5 NO

x SO

x NHx PM 10 PM 2.5 NO

x SO

x 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

PM 10 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 equip

ment using EPA methodology (US EPA, 2006a). The equipment types include: chain

- driven

charbro il ers, 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 & barbe que) based on an

average num ber 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 Marico pa County for the five restaurant types was

obtained from a commercial data base ( www.selectoryonline.com ) and is shown in Table 3.3

– 3.2008 Maricopa Co. PM 10 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 f irst 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).

Numbe r 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 o f 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%

Seafo od 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 e ach cooking

equip ment 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

Gr iddles

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 × averag e number of underfired char

at ethnic food restaurants with underfired charbroilers broilers per ethnic food restaurant

= 431 × 1.54

= 6642008 Maricopa Co. PM 10 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

- = S teak 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 m eat 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, wit h 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 t he appropriate emission factor from Table 3.3

– 9 ( US EPA, 2006a ) . The results

were then summed to estimate annual emissions for each type of co oking 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. PM 10 Emission Inventory 34 June 2011 Table 3.3

– 9. PM 10 a nd PM 2.5 emission factors for commercial cooking equipment, by device type.

Emission Fac tor (lb/ton)

Equipment type PM 10 PM 2.5

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. Ann ual and daily emissions from commercial cooking equipment in Maricopa County.

Equipment type Annual Emissions (tons/yr) Typical Daily Emissions (lbs/day)

PM 10 PM 2.5 PM 10 PM 2.5

Chain

- driven charbroilers 103.88 100.70 570.8 553.3

Underfired charbroiler s 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 PM 10 

### nonattainment a rea 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 a nnual and typical daily emissions from commercial

cooking for the PM 10 

### NAA.

Table 3.3

– 11. Annual and daily PM emissions from commercial cooking equipment in the PM 10 NAA

.

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

PM 10 PM 2.5 PM 10 PM 2.5

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 griddle s 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 grai n 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 repo rted 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 PM 10 

### nonattainment area were derived

based on the location d ata of the individual facilities. Annual and typical daily emissions for

both the County and the PM 10 

### 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 e missions (tons/yr) Typical daily emissions (lbs/day)

PM 10 PM 2.5 PM 10 PM 2.5 Maricopa County 20.59 6.71 149.3 49.5

PM 10 NAA 16.73 5.68 125.3 43.02008 Maricopa Co. PM 10 Emission Inventory 35 June 2011 

### 3.3.2.3 Ammonia cold storage

Area

- source emissions from ammonia cold storage are estimates of ammonia emis sions 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 repo rted by the 2007 County Business

Patterns (US Census Bureau, 20 10 a ). Annual emissions were calcula ted by multiplying

employment numbers by the emission factor for ammonia cold storage as listed in Table 6

- 5 of

“Development and Selection of Ammonia Emissio n Factors” (Battye et al., 1994) as follows:

Annual NH 3 emissions

= Number of employees × NH 3 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 NH 3 /yr



### Typical daily emissions were calcula ted 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)

NH 3 emissions

(lbs/day)

= 1,678.43 × 2,000 ÷ (52 × 6)

= 10

, 759.2 lbs NH 3 /day



### Annual and typical daily emissions for the PM 10 

### nonattainment area (shown in Table 3.3

– 13

below) we re calculated by multiplying Maricopa County emissions by the ratio of County

industrial employ ment that occurs in the PM 10 

### nonattainment area. (See Section 1.5.1 for a more

detailed discussion of the employ ment data used ).

Annual NH 3 emissions from = Annual county emissions (tons/yr) × NAA:County i ndustrial employment ratio

ammonia cold storage in th e

PM 10 NAA (tons/yr)

= 1,678.43 × 0.9974

= 1,6 74.07 tons NH 3 /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

PM 10 NAA 1,674.07 10,731.2



### 3.3.3 Secondary metal prod uction

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 a ssumed

that there were no significant unpermitted sources within Maricopa County. Since all facilities

considered in this section are located within the PM 10 

### nonattainment area, total emission values

for the county and the PM 10 

### NAA from area

- source second ary metal production are equal.

Annual and daily emissions are shown in Table 3.3

– 14.2008 Maricopa Co. PM 10 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 PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 Maricopa County 60.56 52.16 49.73 18.65 0.04 442.7 386.2 358.8 142.7 0.0

PM 10 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 s ource 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 per mitted 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 pe rmits by the Arizona

Department of Environmental Quality (ADEQ). All state

- permitted portable sources are

addressed in Section 3.3.11.

Typical daily emissions were calcula ted based on the operating schedule data reported by

surveyed facilities. Annual a nd typical daily emissions for the PM 10 

### 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 PM 10 

### nonattainment area as a

conser vative estimate.

Table 3.3

– 1 5 summarizes annual and typical daily emissions from non

- metallic mineral

processing activities in both Maricopa County and the PM 10 

### nonattainment area.

Table 3.3

– 1 5

. Annual and typical daily emissions from area

- source non

- met allic mineral products.

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

PM 10 PM 2.5 PM 10 PM 2.5 Maricopa County 192.82 95.47 1,3 3 7. 7 6 59.3

PM 10 NAA 187.73 91.92 1,3 02.8 6 35.6



### 3.3.5 Mining and quarrying

Annual emissions fro m 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

q uarrying 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 dai ly 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 PM 10 

### non attainment area were identified using information on

the location of e ach permitted facility. County

- permitted portable sources with no location data

were assumed to operate within the PM 10 

### nonattainment area as a conservative estimate. Annual

and daily emissions are shown in Table 3. 3

– 1 6

.2008 Maricopa Co. PM 10 Emission Inventory 37 June 2011 Table 3.3

– 1 6

. Annual and typical daily emissions from area

- source mining and quarrying operations.

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

PM 10 PM 2.5 PM 10 PM 2.5 Maricopa County 181.01 55.20 1, 239.2 362.6

PM 10 NAA 156.60 46.81 1, 075.7 3 07.2



### 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 emiss ions data from a subset of sources, and county

- level employment data from the US

Census Bureau (20 10a ) to estimate a n annual per

- employee emission factor that is then used to

estimate emissions from all sources in an industry category.

The most recent emp loyment estimates (for the year 2007) from the US Census Bureau’s County

Business Patterns (CBP) were used. Table 3.3

– 1 7 shows the NAICS codes and employment

estimates used to calculate emissions from wood product manufacturing.

Table 3.3

– 1 7

. County

- leve l 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 s ome larger facilities in this category are considered point sources, they have been

include d in the point source calculations presented earlier in Chapter 2. To avoid double

counting, employ ment at point sources was subtracted from total employment as fo llows:

Total area

- source = Total County employment

– Employment repo r ted 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 we re 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 ar ea sources × Total area

- source employment

Area

- source PM 10 = 102.99 tons PM 10 /yr

emissions from 6,229 employees × 13,140 employees

wood products

= 217.26 tons PM 10 /yr



### Typical daily emissions were calcula ted in the same method, using surveyed daily emissions

estimates from the subs et of surveyed area sources

. From these County totals, emissions

estimates for the PM 10 

### 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. PM 10 Emission Inventory 38 June 2011 PM 10 emissions from area

- source = Total County emissions × NAA:county ratio for

wood product manufacturing industrial employment

in the PM 10 NAA (tons/yr)

= 217.26 tons/yr × 0 .9974

= 216.69 tons PM 10 /yr



### Ta ble 3.3

– 1 8 summarizes annual and typical daily emissions from wood products manufacturing

in both Maricopa County and the PM 10 

### nonattainment area.

Table 3.3

– 1 8

. Annual and typical daily emissions from area

- source wood product manufacturing.

Geographic Are a Annual emissions (tons/yr) Typical daily emissions (lbs/day)

PM 10 PM 2.5 PM 10 PM 2.5 Maricopa County 217.26 203.25 1,668.6 1,548.3

PM 10 NAA 216.69 202.72 1,664.3 1,544.3



### 3.3.7 Rubber/plastics manufacturing

Emissions from area

- source rubber and plast ic 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 employ

ment data from the US Ce nsus Bureau (2010 a ) 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.

W here CBP employment estimates were presented as a range, the midpoint values were chosen

for these calculations. Table 3.3

– 1 9 lists the NAICS codes and employment data used to

calculate emissions from rubber and plastic manufacturing facilities.

Some fa cilities 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 fr om those

facilities surveyed in 2008 as follows:

Total area

- source PM 10 emissions

= Emissions from surveyed area sources

from rubber/plastic product mfg. Employment at surveyed area sources × Area

- source employment

= 30.37 tons PM 10 /yr

2,256 employees × 10,484 employe es

= 140.94 tons PM 10 /yr2008 Maricopa Co. PM 10 Emission Inventory 39 June 2011 Table 3.3

– 1 9

. 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 Ma terial & 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 Poly styrene 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 Manufactu ring 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 D ealers 2,248



### Typical daily emissions were calcula ted in the same method as annual emissions, only using

surveyed daily emissions instead of annual totals. Annual and typical daily emissions for the

PM 10 

### 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.)

PM 10 emissions from

= Annual Maricopa County × NAA:county ratio of

area

- source plastic/rubber emissions industrial employment

in the PM 10 NAA (tons/yr)

= 1 40.94 tons PM 10 /yr × 0.9974

= 140.57 tons PM 10 /yr



### Table 3.3

– 20 summarizes annual and typical daily emissions from rubber/plastic products

manufacturing in both Maricopa County and the PM 10 

### nonattainment area.

Table 3.3

– 20

. Annual and typical daily emissions from are a

- source rubber/plastic product manufacturing.

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

PM 10 PM 2.5 PM 10 PM 2.5 Maricopa County 140.94 105.96 953.3 698.8

PM 10 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, 200 1a). This method com

bines detailed emissions data from a subset of sources, and county

- level employment data fro m2008 Maricopa Co. PM 10 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 indust ry 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 th is 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 calcula ted by “scaling up” area

- sour ce 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 PM 10 = 18.07 tons of PM 10 /yr

emissions from 4,261 employees × 12, 138 employees

fab. metal products

= 51.48 tons PM 10 /yr



### Typical daily emissions were calcula ted in the same method as annual emissions, only using

surveyed daily emissions instead of annual totals. Annual and typical dail y emissions for the

PM 10 

### 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.)

PM 1 0 emissions from area

- source fabricated

= Annual Maricopa County × NAA:County ratio of

metal production in the PM 10 NAA (tons/yr) emissions (tons/yr) industrial employment

= 51.48 tons/yr × 0.9974

= 51.35 tons PM 10 /yr



### Table 3.3

– 21 summarizes annual an d typical daily emissions from fabricated metal products

manufacturing in both Maricopa County and the PM 10 

### nonattainment area.

Table 3.3

– 21

. Annual and typical daily emissions from area

- source fabricated metal product manufacturing.

Geographic Area Annua l emissions (tons/yr) Typical daily emissions (lbs/day)

PM 10 PM 2.5 NH

x PM 10 PM 2.5 NH

x Maricopa County 51.48 42.62 4.50 538.1 460. 6 28.9

PM 10 NAA 51.35 42.51 4.49 536.7 459.4 28.82008 Maricopa Co. PM 10 Emission Inventory 41 June 2011 

### 3.3.9 Construction

Maricopa County’s air quality permits database wa s 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 co nstruction 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 differ ent 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 recom mended using 0.42 ton PM 10 

### /acre

- month for road

construction to account for the large amount of dirt moved during the construction of road

ways. However, both the South Coast Air Quality Management District (SCAQMD) and the

Clark County Department of Air Q uality and Environmental Management have estimated

that a certain per centage of their road construction projects do not involve large

- scale earth

moving activities, and thus have developed average emission factors for road construction

projects (0.1895 to n PM 10 

### /acre

- month and 0.265 ton PM 10 

### /acre

- month, respectively). Since

Maricopa County and Clark County have similar population growth rates , climatic condi

tions , and PM 10 

### sources, MCAQD used the Clark County road construc tion emission factor

of 0.265 to ns/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 PM 10 

### /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 du ration 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. PM 10 Emission Inventory 42 June 2011 **•** 

### 1

- month duration for trenching, demolition, and weed control.

**•** 

### 8

- month duration for s ite 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 associ ated 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 Durat ion

(months) Emission factor

(tons PM 10 /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 developme nt 8 0.11

Temp. storage yard 12 0.11



### County

- wide annual uncontrolled PM 10 

### emissions for each construction category were then

calculated as follows:

Annual uncontrolled = total acres/yr × no. months × emission factor

PM 10 emissions

Example:

Annual uncontrolled PM 10 = 15,327.8 acres/yr × 6 months × 0.032 tons PM 10 /acre

- month

emissions from single

- family

residential construction = 2,942.93 tons PM 10 /yr



### As in prior years, a control efficiency of 90% was applied to the uncontrolled emissions calcu la

tions. This factor is in line with values applied in a number of earlier SIP documents for Mari

copa and Clark Counties, including:

**•** 

### Revised MAG 1999 Serious Area Particulate Plan for PM 10 

### (Appendices volume two, page

V

- 9, and vol. four), Feb. 200 0.

**•** 

### Revised MAG 1999 Serious Area Particulate Plan for PM 10 

### , (Appendix C, Exhibit 3:

Evaluation for Compliance with 24

- Hour PM 10 

### 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. PM 10 

### Nonattainment Area”, report

by ENSR in: Final Plan for Attainment of the 24

- hour PM 10 

### Standard, ADEQ, May 1997,

Appendix B.

**•** 

### Clark Co. PM 10 

### 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 cont rol at construction sites.2008 Maricopa Co. PM 10 Emission Inventory 43 June 2011 

### Thus, an overall control effectiveness of 80.9 % (= 90% × 89.94 %) was applied. Controlled

PM 10 

### emissions were calculated as follows:

Annual controlled

= Uncontrolled PM 10 emissions (tons/yr) × [1

– (control efficiency × rule ef fectiveness)]

PM 10 emissions

Example:

Annual controlled PM 10 emissions from

= 2,942.93 ton s/yr × [1

– (90% control × 89 .94 % rule effectiveness)]

single

- family residential construction

= 560.75 tons PM 10 /yr



### PM 2.5 

### emissions were estimated to comprise 1 0% of PM 10 

### 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 acre

months Emission factor

(tons /acre

- month) Uncontrolled

PM 10 Controlled

PM 10 Controlled

PM 2.5 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 c onstruction 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 storag e 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 PM 10 

### nonattainment area. The same average duration of con struction

activity and emission factors used to estimate Maricopa County emissions (see Table 3.3

– 18)

were applied to construction activity in the Maricopa County PM 10 

### nonattainment area. Table

3.3

– 2 5 summarizes Maricopa County PM 10 

### nonattainment area con struction activity and

calculations for each project type.

Table 3.3

– 2 5

. Annu al emissions from construction within the Maricopa County portion of the PM 10

nonattainment area , by project type.

Project Type Total

Acres Total acre

months EF (tons/

acre

- month ) Uncontrolled

PM 10 Controlled

PM 10 Controlled

PM 2.5 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 Pina l County portion of the PM 10 

### nonattainment. PCAQD estimated that

approx i mately 0.8 percent of the Pinal County construction activity occurred in the Pinal County

portion of the PM 10 

### nonattainment area, thus, an nual and typical daily emission for the Pin al2008 Maricopa Co. PM 10 Emission Inventory 44 June 2011 

### County portion of the PM 10 

### 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) incor

porated the same assumptions concerning relevant input variables su ch as the average duration of

construction activity, emission factors, control efficiency, and rule effectiveness as Maricopa

County's estimates.

Table 3.3

– 2 6

. Annual emissions from construction in the Pinal County portion of the PM 10 NAA , by project

type

.

Project Type PM 10 PM 2.5 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 activ ity, I t 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 e stimates shown in Table

3.3

– 27

.

Table 3.3

– 27

. Annual and typical daily emissions from construction in Maricopa County and the PM 10 NAA

.

Construction Type Maricopa County PM 10 NAA

Annual emissions

(tons/yr) Ty pical daily emissions

(lbs/day) Annual emissions

(tons/yr) Typical daily emissions

(lbs/day)

PM 10 PM 2.5 PM 10 PM 2.5 PM 10 PM 2.5 PM 10 PM 2.5

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 manufac

turing permitted sources are reported here as area

- sources.

As all facilities addressed in this source category are located within the PM 10 

### nonattainment area,

emission totals for both areas are equal. Annual and typical daily emissions are shown in Table

3.3

– 2 8

.

Table 3.3

– 28

. Annual and typical daily emissions from area

- source el ectric equipment manufacturing.

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

Geographic area PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 Maricopa County 13.94 9.64 20.45 0.18 31.55 76.9 53.2 112.4 1.1 193.7

PM 10 NAA 13.94 9.64 20.45 0 .18 31.55 76.9 53.2 112.4 1.1 193.72008 Maricopa Co. PM 10 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

r equested information from ADEQ for all ADEQ

- permitted sources that reported any activity in

Maricopa County during 200 8 . Annual total emissions for most pollu tants were provided, along

with information on the facility type, and information on the locatio n 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 );

o perated from 10/16

- 12/31 in Goodyear at Northside I

- 10 east of Estrella

.

Total annual emissions:

(tons/yr) PM 10 PM 2.5 * NO

x SO

x 0.9 23 0.46 1 8. 429 2.3 06

* PM2.5 was assumed to be 50% of reported PM10 for crushing/screening operations.



### Using this inf ormation, 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 em issions 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 PM 10 emissions

= Total annual emissions ×

in Maricopa County (tons/yr) total operating days in 200 8 operating days in Maricopa County

= 0.923 ×

13 6 136

= 0. 9 23 tons PM 10 /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. 92 3 tons × 2,000 lbs

136 days ton

= 13.6 lbs PM 10 /day



### Table 3.3

– 2 9 summarizes the annual and typical daily emissions for all ADEQ

- permitted

portable sources that operat ed 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 PM 10 

### nonattainment area ; thus emission estimates for Maricopa County and

the PM 10 

### nonattainment area are equal.2008 Maricopa Co. PM 10 Emission Inventory 46 June 2011 Table 3.3

– 29

. Annual and typical daily e missions from ADEQ

- permitted portable sources.

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

PM 10 PM 2.5 NO

x SO

x PM 10 PM 2.5 NO

x SO

x 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 p ublic 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. PM 10 

### emissions from this source

category were derived from annual emission rep orts 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.

PM 2.5 

### emissions were calculated fro m PM 10 

### using a ratio derived from California Air Resources

Board’s (CARB) PM 2.5 

### Fra ction 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 th en summed to provide total daily emissions

for the county. Emissions totals for the PM 10 

### 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 ty pical daily emissions from paved and unpaved road travel at industrial facilities.

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

Geographic area PM 10 PM 2.5 PM 10 PM 2.5 Maricopa County 566.30 271.29 3,880.4 1,847.2

PM 10 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 faciliti es on their annual emissions rep orts. Typical daily

emissions were calcula ted based on operating schedule information provided by individual

facilities through MCAQD’s annual emissions report ing program . Emissions estimates for the

PM 10 

### nonattainment are a we re 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 othe r industrial processes not else where classified.

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

Geographic area PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 Maricopa County 144.60 107.24 10.22 21.49 16.79 953.3 726.4 69.6 137.7 94.6

PM 10 NAA 136.00 99.12 8.12 21.47 14.10 906.0 681.7 5 5.4 137.6 79.82008 Maricopa Co. PM 10 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 PM 10 

### nonattainment area, respectively.

Tab le 3.3

– 32

. Annual and daily emissions from all area

- source industrial processes in Maricopa County.

Annual emissions (tons/yr)

Source category PM 10 PM 2.5 NO

x SO

x NH 3 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. 2 17.26 203.25

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

Ot her 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 PM 10 PM 2.5 NO

x SO

x NH 3 Chemical manufacturing 1

, 445.8 1

, 164.5 0.0 2.6 0.6

Commercial cooking 5,434.0 5,039.5

Grain ha ndling/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 co nstruction 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 11,077.22008 Maricopa Co. PM 10 Emission Inventory 48 June 2011 Table 3.3

– 33

. Annual and typical daily emissions from all area

- source industrial processes in the PM 10 NAA.

Annual emissions (tons/yr)

Source category PM 10 PM 2.5 NO

x SO

x NH 3

Che mical 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 proces ses 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 construct ion 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 PM 10 PM 2.5 NO

x SO

x NH 3 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 treatmen t 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 crema tories

are addressed in Sectio n 3.5.4. There were no incinerators at residential (e.g., apartment

complexes) or commercial/institutional facilities (e.g., hospitals, service establis hments) in

operation during 2008

.2008 Maricopa Co. PM 10 Emission Inventory 49 June 2011 

### Emissions from on

- site incineration were determined from annual emis sion 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 PM 10 

### non attainment area,

thus total emissions fo r the count y 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 PM 10 PM 2.5 NO

x SO

x PM 10 PM 2.5 NO

x SO

x Maricopa County 0.06 0.04 5.01 0.01 0.7 0 .4 38.9 0.1

PM 10 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 p ermit 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 appli cations 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:



# ∑ **× =**  data activity with permits of number issued permits of number total reported activity activity Total

Example:



### ft linear 398

, 787

data with permits 22 issued permits burn 32 (reported) ft linear 541,336 rows bank/fence - ditch Total

**= ×**  **=**



### Reported and estimated activity data for each open burning category a re 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

p ermits

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 PM 10 

### (and PM 2.5 

### ).2008 Maricopa Co. PM 10 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

(tons/acre) Category PM 10 PM 2.5 NO

x SO

x NH 3

We eds, unspecified 15 15 4 N/A N/A 3.2

Russian Thistle (tumbleweeds) 22 22 4 N/A N/A 0.1

Orchard c rops: 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

ditchbank s and fence rows 43,560 ft 2 / acre

= 809.81 tons /yr



### Activity data for the other categories were similarly converted to derive the total mass o f

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 unper

mitted illegal outdoor burning, all calculated emissions estimates were multiplied by a factor of

2.87, based on complaints r eceived 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 PM 10 emissions from = Total material burned × emission factor × unit convers ion factor

ditchbank and fence row burning

= 809.81 tons × 15 lbs/ton × 1 ton / 2,000 lbs

= 6.07 tons/yr

Total annual PM 10 emissions

= Calculated emissions from permit data × unpermitted burning adjustment factor

including unpermitted burning

= 6.07 to ns/yr × 2.87

= 17.43 tons PM 10 /yr2008 Maricopa Co. PM 10 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/y r) Typical daily emissions (lbs/day)

Category Ton

- equivalents PM 10 PM 2.5 NO

x PM 10 PM 2.5 NO

x 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 circumsta nces). 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).

PM 10 

### typical daily emissions for Maricopa County wer e derived as follows:

Typical daily P M 10 emissions

= annual PM 10 emissions (tons/yr) × 2000 lbs/ton

(burn days/week) × (burn weeks/year)

Typical daily PM 10 emissions from

= 17.45 tons/yr × 2000 lbs/ton

ditchbank/ fence row burning 5 days/wk × 39 wks/yr

= 179.0 lbs PM 10 /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 we re calculated by multiplying the per

centage of agricultural and/or vacant land use with in the PM 10 

### n onattainment 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 PM 10 

### non

attainment area.

Table 3.4

– 5. Surrog ate 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 v acant 23.91 %

Tumbleweeds Agriculture and vacant 23.91 %

Table 3.4

– 6. Annual and typical daily emissions from open burning in the PM 10 NAA.

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

Category PM 10 PM 2.5 NO

x PM 10 PM 2.5 NO

x 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 62.52008 Maricopa Co. PM 10 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

l ocated 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 emi ssions (tons/yr) Typical daily emissions (lbs/day)

Geographic area PM 10 PM 2.5 NO

x SO

x PM 10 PM 2.5 NO

x SO

x Maricopa County 86.21 75.92 24.11 7.57 486.1 425. 4 132.9 41.7

PM 10 NAA 60.25 50.78 19.47 6.22 342.4 286.6 107.4 34.3



### 3.4.4 Publicly owned treatme nt works (POTWs)

Emissions from publicly owned treatment works (POTWs) were calculated by multiplying per

capita emission factors (Battye et al., 1994) by population estimates and per

- capita wastewater

usage estimates of 100 gallons per day per person (Tch obanoglous, 1979), as shown in Table

3.4

– 8. Typical daily emissions were calculated by dividing annual emission s by 36 6 day s, as

activity is assumed to occur uniformly throughout the year.

Table 3.4

– 8. NH 3 emissions from publicly

- owned treatment works (P OTWs)

.

Geographic area 2008

Population NH 3 emission factor

(lbs/10 6 gals treated) Annual NH 3

emissions

(tons/yr) Typical daily NH 3

emissions

(lbs/day)

Maricopa County 4,279,760 19.0 1,48 8 .0 7 8,131.5

PM 10 NAA 4,297,140 19.0 1,49 4.12 8,164.6



### 3.4.5 O ther 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. Typica l daily

emissions were calcula ted 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 indust rial waste disposal are located

inside the PM 10 

### non attainment area, therefore emissions for Maricopa County and the PM 10 

### NAA are equal.

Table 3.4

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

Annual emissions (tons/yr) Typi cal daily emissions (lbs/day)

Geographic area PM 10 PM 2.5 NO

x SO

x PM 10 PM 2.5 NO

x SO

x Maricopa County 32.78 16.93 18.39 50.62 224.1 110.9 101.0 278. 1

PM 10 NAA 32.78 16.93 18.39 50.62 224.1 110. 9 101.0 278. 12008 Maricopa Co. PM 10 Emission Inventory 53 June 2011 

### 3.4.6 Summary of all area

- source waste disposa l

Tables 3.4

– 10 and 3.4

– 11 provide a summary of annual and typical daily em issions from all

waste disposal activity, for Maricopa County and the PM 10 

### nonattainment area, respectively.

Table 3.4

– 10. Annual and typical daily emissions from all area

- source w aste disposal for Maricopa County.

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

Category PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 1,48 8.07 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 1,48 8.07 1,613.0 1,438.8 515.3 320.0 8,131.5

Table 3.4

– 1 1. Annual and typical daily emissions from all area

- source waste disposal for the PM 10 NAA.

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

Category PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 1,49 4.12 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 1,49 4.12 799.8 630.5 309.9 312.6 8,164.6



### 3.5 Miscellaneous area sources

3.5.1 Other combustio n

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 i ncorporated 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 20 08 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 Coordi

nation Group (GeoMAC) Wildland Fire Support database 1

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 Summar y

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, 2008 a ; USGS, 2008). Two of these fires were included in the ASLD data, one

http://www.geomac.gov/

.2008 Maricopa Co. PM 10 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 6,6 6 0 acres.

The DFBLS coo rdinates 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 thes e 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 i nclusion 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 data

set because it may have been a du plicate 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 occurrenc e 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 emission s 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 f uel 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 departm ent used the NFDRS Fuel Model map in ArcGIS

to identify NFDRS fuel types for fires wi th latitude and longitude data.2008 Maricopa Co. PM 10 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 T otal Acreage Fuel Loading Factor

(tons/acre)

Agriculture* 33 744.05 4.5

California chaparral 1 0.01 19.5

Barren* 2 0.4 0 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

— * “Agricul ture” 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 (a nnual) 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 f uel loading factor. Table 3.5

– 3 shows the number of wildfires

and acres burne d within both Maricopa County and the PM 10 

### nonattainment area during 2008 , as

well as estimate s 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

PM 10 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 Invento ry (WGA/WRAP, 2005).

Table 3.5

– 4

. Summary of emiss ion factors for prescribed fire

.

PM 10 PM 2.5 NO

x SO

x NH 3

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 fro m wildfires for each geographic area we re calculated as follows :

Annual PM 10 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 PM 10 /ton

2,000 lbs/ton

= 470.38 tons PM 10 /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 occur red within the PM 10 

### nonattainment area, resulting

in nearly 6,700 acres burned. The largest fire within the PM 10 

### nonattainment area was the Eth an

fire which occurred in July 2008 and resulted in more than 6,600 acres burned.

Annual emissions from wildfires within the nonattainment area were calcula ted in the same

method as Maricopa County annual emissions.2008 Maricopa Co. PM 10 Emission Inventory 56 June 2011 Table 3.5

– 5

. Annual emissions from wildfires in Maricopa County and the PM 10 NAA

.



### Average daily emissions we re estimated by d ividing annual emissions by the number of burn

days in 2008. There were 150 burn days in Maricopa County and 90 burn days in the PM 10 

### nonattainment area in 2008; thus:

Average daily PM 10 emissions from

= 470.39 tons PM 10 /yr × 2,000 lbs/ton

wildfires in Maricopa County 150 days/yr

= 6,271.8 lbs PM 10 /day

Table 3.5

– 6

. Average daily emissions from wildfires in Maricopa County and the PM 10 NAA

. Number of

Burn Days Average daily emissions (lbs/day)

Geographic Area PM 10 PM 2.5 NO

x SO

x NH 3 Maricopa Coun ty 150 6,271.8 5,379.0 1,383.8 379.4 290.2

PM 10 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 PM 10 

### nonattain ment

area. Because all 2008 prescribed fires were piled fuels, material burned was derived by

multiplying the number o f 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 u sed to estimate emissions from prescribed fires.

Burn Date Burn

Number Burn

Location Acres

Treated Tons o f

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 Y es

04/04/2008 TNF03 02 T3N,R7E,S34 2 5 10 Y es

04/09/2008 TNF0302 T3N,R8E,S28 5 5 25 N o

09/25/2008 TNF0302 T3N,R8E,S31 10 5 50 N o

11/06/2008 TNF0302 T2N,R7E,S18 6 5 30 Y es

29 24 127



### Prescribed fire emission factors for “piled fuels” were obtained from the Western Re gional 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)

PM 10 PM 2.5 NO

x SO

x N H 3 Prescribed fire (piled fuels) 8.0 8.0 6.2 1.7 0.5 Annual emissions (tons/yr)

Geographic Area PM 10 PM 2.5 NO

x SO

x NH 3 Maricopa County 470.39 403.43 103.79 28.46 21.76

PM 10 NAA 423.56 363.27 93.46 25.62 19.602008 Maricopa Co. PM 10 Emission Inventory 57 June 2011 

### Annual emissions from prescribed fires in Maricopa County were calculated as follows.

Annual PM 10 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 PM 10 /yr



### It was assumed that each prescribed fire lasted one day. Thus, daily emissions from prescribed

fires were determined by dividing the annual emissions (conver ted 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 PM 10 emissions

= annual PM 10 emissions (lbs) from prescribed fires

Number of burn days

= 1,016 lbs PM 10

6 burn days

= 169.3 lbs PM 10 /day



### Since t he 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

tw enty

- 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 PM 10 NAA.

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

Geographic Area PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

Mari copa County 0.51 0.51 0.39 0.11 0.03 169.3 169.3 131.2 36.0 10.6

PM 10 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 ; DF BLS, 2009). The DFBLS coordinates reporting to the National Fire Incident

Report ing System (NFIRS) for Arizona fire department s

. 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 depart

ments 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 in cluded data reported by twenty

one 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 use d to scale up the number of structure fires (ADC, 2008).

Seven open burn permits were issued in 2008 for fire training; these were i ncluded 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. PM 10 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 percent age of structural loss and content loss (US EPA, 2001 c ). 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

. M aterial burned, emiss ion and fuel loading factors for structure fires.

Estimated number

of structure fires Fuel loading

factor (tons/fire) Material burned

(tons) Emission factors (lbs/ton)

PM 10 PM 2.5 * NO

x SO

x NH 3 2,422 1.15 2,785 10.8 10.8 1.4 n/a n/a

* All PM 10 is assum ed to be PM 2.5

.



### 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, 2001 c ), as follows:

Annual PM 10 emissions from

= Quantity of material burned × emission facto r × unit conversion factor

structure fires in Maricopa County

= 2,785 tons × 10.8 lbs/ ton × (1 ton/2,000 lbs)

= 15.04 tons PM 10 /yr



### Annual emissions for the PM 10 

### nonattainment area were derived by multiplying Maricopa

County annual emissions by the perc entage of total residential population within the PM 10 

### non

attainment area (100.41%), as shown in the example below. See Section 1.5.2 for a discussion of

the population data used.

Annual PM 10 emissions

= A nnual PM 10 emissions × P ercentage residential po pulation within the NAA

within the PM 10 NAA for Maricopa County

= 15.04 tons/yr × 100.41%

= 15.10 tons PM 10 /yr



### Typical daily emissions for both Maricopa County and the PM 10 

### nonattainment area we re cal

culated by dividing annual emissions by 36 6 , as a ctivity is assumed to take place 7 days a week.

Typical daily emissions for Maricopa County were derived using the following formula:

Typical daily PM 10 emissions

=

from structure fires 366 day s /yr annual PM 10 emissions (lbs)

=

366 30, 08 0 lbs

= 8 2

. 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 PM 10 PM 2.5 NO

x PM 10 PM 2.5 NO

x Maricopa County 15.04 15.04 1.95 82. 2 82. 2 10.7

PM 10 NAA 15.10 15.10 1.96 8 2

. 5 8 2

. 5 10.72008 Maricopa Co. PM 10 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 Incide nt

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 Count y, 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 v ehicle fires occurred in Maricopa County in 2008.

Annual emissions from vehicle fires were calcula ted 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 PM 10 emissions

= annual number × fue l 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 PM 10 /yr

Table 3.5

– 12

. Estimated material burned, fuel loading factors, and em ission factors for vehicle fires.

Vehicle fires

reported Fuel loading

factor (tons/fire) Material

burned (tons) Emission factors (lbs/ton)

PM 10 PM 2.5 * NO

x SO

x NH 3 2,403 0.25 600.75 100 100 4 n/a n/a

* All PM10 is assumed to be PM2.5.



### Annual emissio ns for the PM 10 

### nonattainment area were derived by multiplying Maricopa

County annual emissions by the percentage of total residential population within the PM 10 

### non

attainment area (100.41%). See Section 1.5.1 for a discussion of the population data used

.

Annual PM 10 emissions

= annual PM 10 emissions × percentage of total residential population

from vehicle fires in the for Maricopa County within the PM 10 NAA

PM 10 NAA

= 30.04 tons/yr × 100.41%

= 30.16 tons/yr



### It is assumed that vehicle fires occur e venly throughout the year. Thus, typical daily emissions

were derived by dividing the Maricopa County and nonattainment area annual emissions by 36 6

days/year. The results are shown in Table 3.5

– 1 3 below.

Table 3.5

– 1 3

. Annual and typical daily emissions from vehicle fires.

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

Geographic area PM 10 PM 2.5 NO

x PM 10 PM 2.5 NO

x Maricopa County 30.04 30.04 1.20 164. 1 164. 1 6.6

PM 10 NAA 30.16 30.16 1.21 16 4

. 8 164

. 8 6.62008 Maricopa Co. PM 10 Emission Inventory 60 June 2011 

### 3.5.1.5 Engine testing

Annual e missions 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. T ypical daily emissions

were calculated based on operating schedule information provided in the facilities’ annual emis

sion reports.

Since all facilities considered in this section are located within the PM 10 

### nonattainment area, total

emission values for the county and the PM 10 

### NAA are equal. Results are shown in Table 3.5

– 1 4

.

Table 3.5

– 1 4

. Annual and typical daily emissions from engine testing.

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

Geographic area PM 10 PM 2.5 NO

x SO

x PM 10 PM 2.5 N O

x SO

x Maricopa County 0.18 0.17 6.74 2.49 1.3 1.2 50.5 19.0

PM 10 NAA 0.18 0.17 6.74 2.49 1.3 1.2 50.5 19.0



### 3.5.2 Agricultural a ctivities

3.5.2.1 Tilling

Tillage emissions were estimated using the tillage emission factor equation and Maricopa County

s pecific 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 Agri

cultural Statistics Service for 2008 (USDA, 2008 b ) and vegetables and citrus acreage were

obtained from the 2007 Census of Agriculture (USDA, 2007 a ). Crop

- specific annual land prepar

ation operations data were obtained from the Technical Support Document for Quantification of

Agricultural Best Management Practices (URS and ERG, 2001). The agricultural tillage emis

sion factor was calculated as follows:

EF = k (4.8) s 0.6



### where:

EF

= Agricultural emission tillage factor (lbs PM 10 

### / acre

- pa ss)

k

= Particle size multiplier (value of 0.15 for PM 10 

### )

s = Silt content of soil ( % ) = 35.2% (URS and ERG, 2001)

Thus: EF

= 0.15 **×** 4.8 **×** (35.2) 0.6



### = 6.10 lbs PM 10 

### / acre

- pass2008 Maricopa Co. PM 10 Emission Inventory 61 June 2011 

### Annual PM 10 

### emissions from agricultural tillage were calculated for ea ch crop category using the

following equation (URS and ERG, 2001; Pollack et al. , 2003):

Tillage Crop = EF **×** AP Crop **×** A Crop



### where:

Tillage Crop = Annual PM 10 emissions from tilling each crop type (lbs )

EF

= Tillage emission factor (lbs PM 10 /acre

- pass)

AP Crop = Number of tilla ge passes per crop (passes)

A Crop = Total number of tilled acres for each crop type (acres)



### For example, annual PM 10 

### emissions from cotton tilling were calculated using:

EF

= 6.10 lbs PM 10 /acre

- pass

A P

cotton = 8.8 tillage pass es for a cotton crop

AP

cotton = 19,300 acres cotton



### Thus:

Tillage

cotton = 6.10 **×** 8.8 **×** 19, 300

= 1, 036,024 lbs/yr

= 5 18.01 tons/y r



### Table 3.5

– 1 5 lists crop types and acreage; typical number of land preparation operations and

acre

- passes; and annual uncontrolled PM 10 

### emissions from agricultural tillage for Maricopa

County.

Table 3.5

– 1 5

. 2008 crop acreage , activity, and annual uncontrolled PM 10 emissions in Maricopa County.

Crop Acres

Planted No. of land

preparation

operations /yr Acre

- passes Annual un controlled

PM 10 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 45.1 6

Sorghum for grain 16,500 3.1 50,575 154.25

Vegetables 2 16,072 14.0 224,888 685.91

Citrus 3 425 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 approxi mately 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

repor ted harvested acreage.



### In November 2007, the agricultural PM 10 

### 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 o nly applied to the Maricopa County

PM 10 

### NAA. The agricultural PM 10 

### 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 PM 10 

### emissions gen erated 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 by2008 Maricopa Co. PM 10 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 con trol 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% (fr om 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

. ( R ule effectiveness

calculations for agricultural activities are included a s 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 t he 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

tillage Crop emissions PM 10 emissions control efficiency

crop ) in th e Area A

Controlled annual

= 518.01 tons PM 10 /yr × (100%

– 22.8%) × 63.09%

tillage Cotton emissions

= 252.30 tons PM 10 /yr



### The uncontrolled portion of tillage emissions from agricultural operations taking place outside

Area A but within Maricopa County we re estimated by multiplying the uncontrolled annual

P M 10 

### emissions by the percen tage of agricultural land located within Maricopa County but

outside of Area A (100%

– 63.09%) as follows:

Uncontrolled annual

= Uncontrolled annual × 36.91%

tillage Crop emiss ions PM 10 emissions

= 518.01 tons PM 10 /yr × 36.91%

= 191.20 tons PM 10 /yr



### Controlled and uncontrolled emissions were then summed to estimate total annual PM 10 

### emis

sions from agricultural tillage in Maricopa County. Annual PM 2.5 

### emissions from agricult ural

tillage were calculated by multiplying the annual PM 10 

### emissions by a conversion factor of 0.15

(WRAP, 2006b). Annual PM 10 

### and PM 2.5 

### emissions from agricultural tillage in Maricopa

County and Area A are shown in Table 3.5

– 1 6

.2008 Maricopa Co. PM 10 Emission Inventory 63 June 2011 Table 3.5

– 1 6

. 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 (%) PM 10 PM 2.5 PM 10 PM 10 PM 2.5

Cotton 22.8% 252.36 37.85 19 1.35 443.72 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

Total s: 1,190.63 178.59 868.37 2,059.00 308.85

*Includes melons, excludes potatoes.



### Annual PM 10 

### e missions from agricultural tillage in the PM 10 

### NAA were calculated in the same

manner as the annual PM 10 

### emissions for the Ma ricopa County portion of Area A; t he only dif

ference being the percent of agricultural land located within the Maricopa County PM 1 0 

### NAA is

4 4

. 14 % (rather than 63.09% for Area A). Results are shown in Table 3.5

– 1 7

.

Table 3.5

– 1 7

. Annual emissions from agricultural tillage in the PM 10 NAA (tons/yr).

Net Control

Efficiency Fraction of

Ag Land in PM 10 NAA

annual emissions

Crop (%) P M 10 NAA PM 10 PM 2.5

Cotton 22.8% 4 4

. 14 % 1 76

. 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 grai n 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 PM 10 

### 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

– 1 8 . The calendar of tillage operations did not

include months of tillage operations for citrus, thus, a conservative estimate of three (3) mo nths

per year was assumed.2008 Maricopa Co. PM 10 Emission Inventory 64 June 2011 Table 3.5

– 1 8

. Controlled typical daily emissions from tillage (in lbs/day )

. Tillage

operations 1

(months/yr) Tillage

operations

(days/yr) Maricopa County Area A PM 10 NAA

Crop PM 10 PM 2.5 PM 10 PM 2.5 PM 10 PM 2.5

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

Total s: 22,9 32.4 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, 2008 b ) and vegetables and citrus were obtained from the

2007 Census of Agriculture (USDA, 2007 a ). Table 3.5

– 1 9 lists the crop types, acres harvested

and associated PM 10 

### emission factors used to calculate emissions from agricultural harvesting.

Table 3.5

– 1 9

. Maricopa County harvested acres and emission factors.

Crop PM 10 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 PM 10 

### emissions from agricultural harvesting were calculated using the following

equation:

Uncontroll ed annual = E F

crop **×** A Crop **×** ton / 2,000 lb

harvest Crop emissions

where:

harvest Crop = harvest emissions for each crop type (tons PM 10 /yr)

EF Crop = harvest emission factor (lbs PM 10 /acre)

A Crop = number of harvested acres for each crop type per year

E

xample:

EF Cotton = 3.4 lbs PM 10 /acre for cotton2008 Maricopa Co. PM 10 Emission Inventory 65 June 2011 A Cotton = 18,800 acres of cotton

Uncontrolled annual = 3.4 lbs PM 10 /acre **×** 18,800 acres **×** 1 ton/2,000 lbs

Harvest Cotton Emissions = 31.96 tons PM 10 /yr



### In November 2007, the agricultural PM 10 

### general per mit 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 PM 10 

### NAA. ) The agricultur al PM 10 

### 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 PM 10 

### 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 Agricultu ral 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 guid ance (US

EPA, 2005) which eliminates use of the 80% default rule effectiveness value

. ( R ule effectiveness

calculations for agricultural activities are included as Appendix 3 ). To estimate controlled

harvest emissions from agricultural operations taking p lace 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 foll ows:

Controlled annual

= annual uncontrolled × (100%

– mid

- point net × % agricultural land

harvest Crop emissions PM 10 emissions control efficiency

crop ) in the Maricopa Co.

portion of Area A

Controlled annual

harvest Cotton emissions

from within t he Maricopa = 31.96 tons PM 10 /yr **×** (100%

– 25.6%) × 63.09%

Co. portion of Area A

= 15.01 tons PM 10 /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 PM 10 

### 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 PM 10 × 36.91%

Harvest Cotton emissi on emissions

from outside the Maricopa

Co. portion of Area A

= 31.96 tons PM 10 /yr × 36.91%

= 11.80 tons PM 10 /yr



### The total controlled and uncontrolled annual emissions were then summed to estimate total

annual PM 10 

### emissions from agricultural harvesting in Maricopa County as follows:2008 Maricopa Co. PM 10 Emission Inventory 66 June 2011 Total annual harvest Cotton = Uncontrolled annual + Controlled annual

emissions for Maricopa harvest Cotton emissions harvest Cotton emissions

County from outside Area A from within the Maricopa Co. portion of Area A

= 11.80 + 15.01

= 26.81 tons PM 10 /yr



### Annual PM 2.5 

### emissions from agricultural harvesting were calculated by multiplying the annual

PM 10 

### emissions by a conversion factor of 0.15 (WRAP, 2006c). Annual PM 10 

### and PM 2.5 

### emissions from harvesting in Maricopa C o. and Area A are shown in Table 3.5

– 20

.

Table 3.5

– 20

. Annual emissions from harvesting in Maricopa Co unty and Area A ( in tons/yr).

Crop Net

control

efficiency Maricopa

Co.

Uncontrolled Area A

(controlled) Outside Area

A

(uncontrolled) Maricopa Co. (Are a

A + outside Area A)

(%) PM 10 PM 10 PM 2.5 PM 10 PM 10 PM 2.5

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 2 3.5% 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 PM 10 

### emissions fro m agricultural harvesting in the PM 10 

### NAA were calculated in the

same manner as the annual PM 10 

### emissions for the Maricopa County portion of Area A. The

only difference being the percent of agricultural land located within the Maricopa County PM 10



### 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 PM 10 NAA (tons/yr).

Crop Net control

efficiency Fraction of

Ag land in PM 10 NAA

(controlled)

(%) PM 10 NAA PM 10 PM 2.5

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. PM 10 Emission Inventory 67 June 2011 

### Typical daily e missions for Maricopa County, Area A, and the PM 10 

### 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

in dividual 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

– 2 2

.

Table 3.5

– 2 2

. Typical daily emissions from harvest ing , by crop ( in lbs/day).

Crop Harvest

days/yr Maricopa County Area A PM 10 NAA

PM 10 PM 2.5 PM 10 PM 2.5 PM 10 PM 2.5

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 PM 10 

### 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:

Unp aved 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 (PM 10 constant ; US EPA, 2006b)

a = 0.9 (PM 10 constant ; US EPA, 2006b )

b

= 0.45 (PM 10 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:

Dai ly uncontrolled PM 10 = unpaved road EF × VMT/1000 acres × 2008 harvested acres2008 Maricopa Co. PM 10 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 PM 10 

### general permit (Arizona Admini strative Code s 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 PM 10 

### NAA.

The agricultural PM 10 

### general permit revisions also re sulted in the requirement for commercial

farmers to implement six agricultural best management practices (BMP) (up from 3 BMPs) to

control PM 10 

### emissions generated from tillage and harvest, non

- cropland, and cropland. Because

no data is available on the a dditional 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

cro ps. 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 eliminate s use of the

80% default rule effectiveness value

. ( R ule 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 PM 10 

### emissions

as follows:

Controlled daily = Daily uncontrolled × (100%

- mid

- point net × % agri cultural land

unpaved ag road PM 10 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 Maric opa

County portion of Area A but within Maricopa County were estimated by multiplying uncon

trolled daily PM 10 

### emissions by the percent of agricultural land located within Maricopa County

but outside of Area A (100%

– 63.09%) as follows:

Uncontrolled dail y unpaved ag = Uncontrolled PM 10 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 PM 10



### emissions from t ravel 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 Ar ea A

= 4,453 + 6,6982008 Maricopa Co. PM 10 Emission Inventory 69 June 2011 = 11,151 lbs PM 10 /day



### Daily PM 10 

### emissions from unpaved agricultural roads in the PM 10 

### NAA were calculated in the

same manner as the daily PM 10 

### emissions for the Maricopa County portion of Area A. The only

difference being the percent of agricultural land located within the Maricopa County PM 10 

### NAA

is 4 4

. 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 PM 10 

### NAA were calculated by multi

plying dail y emission estimates by 312 (

= 6 days per week × 52 weeks per year).

Annual and daily PM 2.5 

### emission from travel on unpaved agricultural roads were calculated by

multiplying the annual and daily PM 10 

### emissions by a conversion factor of 0.10 (WRAP, 2006c).

Annual and daily PM 10 

### and PM 2.5 

### emissions from unpaved agricultural roads are shown in Table

3.5

– 2 3

.

Table 3.5

– 2 3

. Annual and typical daily emissions from travel on unpaved agricultural roads.

Annual emissions

(tons/yr) Typical daily emissions

(lbs/day)

Geographic area PM 10 PM 2.5 PM 10 PM 2.5

Maricopa County (Area A + outside Area A) 1,739.52 173.95 11,150.8 1,115.1

Area A (controlled) 1,044.9 2 104.49 6,698.2 669.8

PM 10 NAA (controlled) 731.03 73.10 4,686.1 468.6



### 3.5.2.4 Cotton ginning

Annual emissi ons from cotton ginning were derived from annual emission reports from all

per mitted cotton gins in the county

. Typical daily emissions were calcula ted based on the

operating schedule data reported by surveyed facilities. Annual and typical daily emissio ns for

the PM 10 

### nonattainment area were derived based on the location data of the individual facilities.

Table 3.5

– 2 4 summarizes annual and typical daily emissions from cotton gins in both Maricopa

County and the PM 10 

### nonattainment area.

Table 3.5

– 2 4

. An nual and typical daily emissions from area

- source cotton ginning.

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

Geographic area PM 10 PM 2.5 PM 10 PM 2.5 Maricopa County 17.90 5.11 103.8 29.7

PM 10 NAA 4.86 1.39 26.7 7.6



### 3.5.2.5 Fertiliz er application

Annual NH 3 

### 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 M odel v.3.6 to calculate NH 3 

### emissions from

synthetic nit rogen 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 monthly2008 Maricopa Co. PM 10 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

NH 3 

### emissions. EPA, however, obtained county

- level fertilizer consumpt ion 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 NH 3 

### emissions. Typical daily NH 3 

### emissions were derived by divi ding annual emissions by 366 days/year. Annual and typical

daily emissions for the PM 10 

### nonattainment area were derived by multiplying the county annual

and typical daily emissions by the percentage of agricultural land located in the PM 10 

### NAA

(44.1%). Se e Section 1.5.2 for a discussion of the land use data used. Annual and typical daily

NH 3 

### emissions from fertilizer application are shown in Table 3.5

– 25

.

Table 3.5

– 25. Annnual and typical daily NH 3 emissions from fertilizer application

.

Maricopa County PM 10 NAA

Fertilizer Category Annual

E missions

(tons/year) Daily NH 3

Emissions

(lbs/day) Annual NH 3

Emissions

(tons/year) Daily NH 3

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 49 6.42 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 2,2 76.43 12,439.5 1,004.82 5,490.8



### 3.5.3 Livestock

PM 10 

### and PM 2.5 

### emissions estimates were derived using Maricopa County cattle inventory

estimates for 2008 from Arizona Agricultural Statistics Bulletin (AASS, 2009) and emission

factor for PM 10 

### for dairy ca ttle, and feedlot cattle from the California Air Resources Board

(CARB, 2004). PM 2.5 

### was presumed to be 11% of PM 10 

### per WRAP Fugitive Dust Handbook

(WRAP, 2006d).

The number of “cattle on feed” was not available from the Arizona Agricultural Statistics

B ulletin (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 PM 10 

### and PM 2.5 

### emission estimates for livestock.2008 Maricopa Co. PM 10 Emission Inventory 71 June 2011 

### The 2008 Maricopa County cattle invent ory and applicable PM emission factors are contained in

Table 3.5

– 2 6

.

Table 3.5

– 2 6

. Maricopa County cattle populations and PM emission factors.

Animal type No. of

Head PM 10 Emission Factor

(lb/1000 head/day ) PM 2.5 : PM 10 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 PM 10 

### emissions from livestock in Maricopa County were calculated using the

following formula:

Typical daily emissions = milk cow inventory (1,000 head) × emi ssion factor (lbs PM 10 /1,000 head/day)

(lbs/day) from dairy cattle = 100 × 6.7

= 670.0 lbs PM 10 /day



### It was assumed that livestock emissions occur evenly throughout the year. Annual PM 10 

### and

PM 2.5 

### emissions were derived by multiplying typical daily e missions by 366 days/year.

NH 3 

### emissions from livestock in Maricopa County were estimated by growing the 2005 NH 3 

### emissions by the percentage change in Maricopa County cattle and calve numbers from 2002 to

2008 (AASS, 2003; AASS, 2009) 2 

### . The cattle and c alf populations declined 8.11% from 2002 to

2008; as shown in Table 3.5

– 2 7 below. The estimated 2005 and 2008 NH 3 

### emissions from

livestock emissions are shown in Table 3.5

– 2 8

.

Table 3.5

– 2 7

. Maricopa County cattle inventory for 2002 and 2008.

Maricopa C o. Percentage

2002 2008 Change

All cattle & calves 185,000 170,000

- 8.1%

Table 3.5

– 2 8

. Annual and typical daily NH 3 emissions from livestock in Maricopa County.

Annual e missions

(tons/year) Typical d aily

e missions (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) loca

tions and animal numbers in Maricopa County that 57.3% of CAFO a nimals 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 e missions from livestock for Maricopa

County and the PM 10 

### nonattainment area.

2 The 2005 NH 3 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 us ing the percentage

change in cattle and calve numbers from 2002 to 2008.2008 Maricopa Co. PM 10 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 PM 10 PM 2.5 NH 3 PM 10 PM 2.5 NH 3 Maricopa County 45 5

. 80 50. 14 9,583.89 2,490.7 274.0 52,514.5

PM 10 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 inve n tory

reports f rom all crematories located within the county. Typical daily emissions were calcula ted

based on the operating schedule data reported by surveyed facilities. Annual and typical daily

emissions for the PM 10 

### nonattainment area were derived based on the loca tion data of the indiv

idual facilities.

Table 3.5

– 30 summarizes annual and typical daily emissions from crematories in both Maricopa

County and the PM 10 

### nonattainment area.

Table 3.5

– 3 0

. Annual and typical daily emissions from crematories.

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

Geographic area PM 10 PM 2.5 NO

x SO

x PM 10 PM 2.5 NO

x SO

x Maricopa County 0.93 0.62 12.39 1.58 7.0 4.7 93.1 11.9

PM 10 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. Da ta from

these two source s documented the release of 0.01 tons of PM 10 

### and 0.06 tons of NO

x 

### for the year

2008. To be conservative, PM 2.5 

### amounts are assumed to be equal to PM 10 

### amounts

. (No

accidental releases of SO

x 

### or NH 3 

### were reported).

Typical daily e missions were calcula ted by summing reported releases and dividing the total by

36 6 days. Emissions in the PM 10 

### nonattainment area were calcula ted 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 PM 10 PM 2.5 * NO

x PM 10 PM 2.5 * NO

x Maricopa County 0.01 0.01 0.06 0.1 0.1 0.3

PM 10 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) recommend ed using a per

- capita emission factor

developed for the National Acid Precipitation Assessmen t Program (NAPAP) inventory in 1985.

This factor was applied to MAG population estimates for the county and PM 10 

### nonattainment2008 Maricopa Co. PM 10 Emission Inventory 73 June 2011 

### areas (see section 1.5 for population information). Daily emissions were calculated by dividing

annual values by 366

. The resu lting estimates are shown in Table 3

- 5

– 32.

Table 3.5

– 32

. Annual and typical daily NH 3 emissions from human activity.

Geographic Area Population Emission factor

(lbs/ person

- yr) Annual NH 3

emissions (tons/yr) Typical daily NH 3 emissions (lbs/day)

Maricop a County 4,279,760 0.55 1,176.93 6,431.3

PM 10 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. Exhau st emissions from gasoline

- powered leaf blowers are

covered under the Nonroad M obile S ources section of this report ( C hapter 4). Fugitive dust

emission estimates are deve loped with the use of three sources: EPA’s NONROAD model,

California Air Resources Bo ard 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 2008 NONROAD model was used to esti mate 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

estimate d that 60% of all leaf blowers sold are electric. Thus a ssuming the remaining 40% are

gasoline

- p owered, the total population wa s estimated as:

Total leaf blower population

= G as

- powered leaf blower population ÷ 40%

= 109,787 ÷ 0 .4

= 274,468 units



### The remaining 164,681 unit s [= 274,468

– 109,787] are thus assumed to be electric

- powered.

Fitz et al. ( 2005) developed emission factors for PM 10 

### and PM 2.5 

### 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

– 3 3 lists the equipment population

numbers, activity estimates and emission factors for leaf blowers in Maricopa County.

Table 3.5

– 3 3

. Leaf blower equipment populations, activity levels and emission factors for Maricopa County.

Leaf blower description Population A nnual a ctivity

(hrs/yr) PM 10 e mission

factors (mg/m 2 ) PM 2.5 Emission

factors (mg/m 2 )

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/a2008 Maricopa Co. PM 10 Emission Inventory 74 June 2011 

### CARB (2000) estimates that approximately 1600m 2 

### of surface can be cleared in one hour of leaf

blower operation. Therefore, annual emission estimates were calcula ted by using the followin g

formula, as in this example for electric leaf blowers:

Annual PM 10 emissions

= population × a ctivity × e mis sion factor × area covered

from electric leaf blowers (hrs/yr) ( m g/m 2 ) (m 2 /hr )

= 164,681 × 10 hrs/yr × 130 m g/m 2 × 1600 m 2 /hr

= 342,536 ,480 ,000 m g/yr

= 377.24 tons PM 10 /yr



### The activity hours associated with leaf blowers can occur at any time during the year in Mari

copa County due to the temperate climate, with no substantial seasonal variation

. Therefore,

t ypical daily emissions we re estimated by dividing annual totals by 366 days per year. Emis

sions for the PM 10 

### non attainment area are allocated bas ed on the ratio of population in the

County to the nonattainment area (see S ection 1.5 for information on population). Table 3.5

– 34

li sts annual and daily fugitive emission s from leaf blowers for Maricopa County and the PM 10



### nonattainment area.

Table 3.5

– 3 4

. Annual and typical daily emissions from leaf blower fugitive dust.

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

Geographic area PM 10 PM 2.5 PM 10 PM 2.5 Maricopa County 891.36 336.41 4,870.8 1,838.3

PM 10 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 recreationa l vehicles.

These emissions are included in the nonroad emissions category of the 2008 particulate emis

sions inventory. Particulate emissions are also generated by recreational vehicles traveling on

unpaved surfaces. For the 2008 periodic inventory, th ese 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 emis

sions from offroad recreational vehicle s 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

– 3 5.

To be consistent with the 2005 Periodic Emissions Inventory for PM 10 

### (MCAQD, 2007), it was

assumed that 75 percent of the annual travel by offroad re creational 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 vehicl es, and 75 percent produces the annual vehicle miles

traveled (VMT) on unpaved surfaces, shown in Table 3.5

– 3 5 . Dividing annual VMT totals by

366 produces a daily estimated offroad recreational vehicle travel on unpa ved surfaces in

Maricopa County in 2008

.2008 Maricopa Co. PM 10 Emission Inventory 75 June 2011 Table 3.5

– 3 5

. 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 (N on

- 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, 2006 b ), assuming a silt content of 11.9 percent and an average vehicle weight of one

half of a ton. The resultant PM 10 

### emission factor for ATVs and SVCs is 0.594 pounds per vehi

cle 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. A pplying the AP

- 42 equa

tion results in a PM 2.5 

### emission factor for ATVs and SVCs of 0.059 pounds per mile, while the

comparable PM 2.5 

### 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

– 3 7

.

The emissions for the PM 10 

### nonattainment area were derived by applying geographic information

systems (GIS) to MAG 2009 land use data 1 

### to obtain the acreage of passive open space in the

PM 10 

### nonattainment area and Maricopa County. Passive open space includes open desert, moun

tains and washes. The detailed calculations for deriving the PM 10 

### nonat tainment area emissions

are shown below:

Passive Open Space in the PM 10 nonattainment area (NAA) = 262

, 662 acres

Passive Open Space in Maricopa County = 1

, 476

, 922 acres

Ratio of Passive Open Space in PM 10 NAA vs. Maricopa County = 1 7.8 %

PM 10 NAA Emissions = 0.1 78 × Maricopa County Emissions



### Application of the ratio above to Maricopa County emissions produces the uncontrolled annual

and typical daily PM 10 

### NAA emissions shown in Table 3.5

– 3 6 . The PM 10 

### and PM 2.5 

### emissions

for all offroad recreational vehicl e 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 com

mitted measures in the MAG 2007 Five Percent Plan.

Table 3.5

– 3 6

. 2008 uncontrolled emissions from offroad recreational vehicles.

Annual emissions (tons/yr) Typical Daily Emissions (lbs/day)

Geographic Area PM 10 PM 2.5 PM 10 PM 2.5 Maricopa County 12,248.11 1,216.56 66,929.6 6,647.9

PM 10 NAA 2

, 180.16 216.55 11

, 913.5 1,183.3



### Two committed measures tha t reduce emissions from offroad recreational vehicles were quanti

fied in the MAG 2007 Five Percent Plan for PM 10 

### (MAG, 2007). The benefit taken in 2008 for

these measures in the Five Percent Plan is shown in Table 3.5

– 3 7

.

1. Draft, as of March 24, 2010

.2008 Maricopa Co. PM 10 Emission Inventory 76 June 2011 Table 3.5

– 3 7

. Benefits of mea sures that reduce offroad recreational vehicle emissions.

2008 PM 10 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 us e on high pollution days (Measure 23) 25.7 140.6

Total 2008 PM 10 emission reductions for offroad recreational vehicles 166.0 907.0



### The emission benefits in Table 3.5

– 37 were subtracted from the uncontrolled PM 10 

### emissions in

Table 3.5

– 3 6 . The 2008 PM 10 

### emission reduction of 166.0 tons per year represents 7.6% of the

uncontrolled emissions in the PM 10 

### NAA of 2,180.16 tons per year. This percent reduction was

applied to the uncontrolled PM 2.5 

### emissions in the PM 10 

### NAA; then the absolu te reduction in

PM 2.5 

### emissions due to the control measures was applied to the uncontrolled PM 2.5 

### emissions in

Maricopa County. The annual and daily controlled emission estimates are shown in Table 3.5

–

38 below

.

Table 3.5

– 3 8

. 2008 controlled emissions fr om offroad recreational vehicles.

Annual E missions (tons/yr) Typical Daily Emissions (lbs/day)

Geographic Area PM 10 PM 2.5 PM 10 PM 2.5 Maricopa County 12,082.12 1,200.11 66,022.5 6,558.0

PM 10 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, 2006 b ). The methodology, assumptions and

calcu lations 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 PM 10 

### 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 thi rty percent to ten percent) to mirror a 67 percent decline in

total permitted construction acreage in the PM 10 

### NAA between 2005 and 2008. GIS was applied

to 2009 MAG land use data 2 

### to estimate that there are 1 71

, 785 acres of vacant land in the core

urbani zed area and 64,519 acres of land under development in the PM 10 

### 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 dev elopment



### 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 PM 10 

### NAA. In estimating fugitive dust

emissions from u npaved parking lots, the MAG Serious Area PM 10 

### Plan assumed that 24 percent

2

. Ibid

.2008 Maricopa Co. PM 10 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 acre s of unpaved

parking lots in the PM 10 

### NAA.

The MAG Serious Area PM 10 

### 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 travel s 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 PM 10 

### NAA.

The emission factors for unpaved parking lots were derived from the AP

- 42 equation for

unpaved industrial roads ( US EPA, 2006 b ), 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 PM 10 

### and 0.137 pounds per mile for PM 2.5



### .

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 PM 10 

### NAA are shown in Table 3.5

– 40

.

To estimate emissions for Maricopa County, GIS was applied to 2009 MAG land use data 3 

### to

obtain 2,227,981 acres of vacant land in Maricopa County. Removing the vacant land in the

Maricopa County portion of the PM 10 

### NAA (i.e., 466,553 acres) results in 1,761,428 vacant acres

located inside Maricopa County, but outside the PM 10 

### NAA.

Assuming one percent of the vacant land outside the PM 10 

### 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 PM 10 

### 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 PM 10 

### NAA of 11,539.7 pounds per day of PM 10 

### and 1,158.2 pounds per day of PM 2.5



### .

The final step in estimating Maricopa County emissions requires removing the Pinal County

portion of the PM 10 

### NAA. The unpaved parking lot emissions in the Pinal County portion of the

PM 10 

### NAA are assumed to be proportional to the acres of vacant land. These were derived using

GIS and 2009 MAG land use data 4 

### , with the results shown below:

Vacant land in the Pinal County portion of the PM 10 NAA = 6,2 78 acres

Vacant land in the PM 10 NAA = 472,831 acres

Ratio = 6,2 78 / 472,831 = 1. 3 %; Pinal County portion = 1. 3 % × PM 10 NAA em issions

Pinal County portion of PM 10 emissions = 1. 3 % × 1 3

, 232.3 = 172

. 0 pounds per day

Pinal County portion of PM 2.5 emissions = 1. 3 % × 1, 158.2 = 17

. 3 pounds/ day



### Adding the emissions inside and outside the PM 10 

### NAA and subtracting the Pinal County portio n

produces total Maricopa County emissions attributable to vehicles traveling on unpaved parking

3

. Ibid

.

4

. Ibid

.2008 Maricopa Co. PM 10 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 Mar icopa County are shown in

Table 3.5

– 39 . Uncontrolled emissions do not include the 2008 emission reductions attributed to

the com mitted measure in the MAG 2007 Five Percent Plan.

Table 3.5

– 39

. 2008 uncontrolled emissions from vehicles traveling on unpave d parking lots.

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

Geographic area PM 10 PM 2.5 PM 10 PM 2.5 Maricopa County 4,501.80 451.83 24,600.0 2,469.0

PM 10 NAA 2,421.51 243.04 13,232.3 1,328.1



### One committed measure that reduces emiss ions from unpaved parking lots was quantified in the

MAG 2007 Five Percent Plan for PM 10 

### (MAG, 2007). The benefit taken in 2008 for this

measure in the Five Percent Plan is shown in Table 3.5

– 4 0

.

Table 3.5

– 4 0

. Benefits of measure that reduces unpaved par king lot emissions.

2008 PM 10 emission

reduction

Committed Measure in Fiv e 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 uncontroll ed PM 10 

### emissions in

Table 3.5

– 39 . The 2008 PM 10 

### emission reduction of 56.4 tons per year represents 2.3% of the

uncontrolled emissions in the PM 10 

### NAA of 2,421.51 tons per year. This percent reduction was

applied to the uncontrolled PM 2.5 

### emissions in th e PM 10 

### NAA; then the absolute reduction in

PM 2.5 

### emissions due to the control measure was applied to the uncontrolled PM 2.5 

### emissions in

Maricopa County. The annual and daily controlled emission estimates are shown in Table 3.5

–

41 be low.

Table 3.5

– 4 1

. Annual and typical daily controlled emissions from unpaved parking lots.

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

Geographic area PM 10 PM 2.5 PM 10 PM 2.5 Maricopa County 4,445.36 446.24 24,291.6 2,438.5

PM 10 NAA 2,365.07 237.45 12,923.9 1,297.52008 Maricopa Co. PM 10 Emission Inventory 79 June 2011 

### 3.5.10 Windblown dust

Windblown dust emissions were calcula ted using a combination of local meteorology conditions,

land use and vertical flux emission rates. A full description of the methodology can be found in

App endix 4

. Table s 3.5

– 4 2 and 3.5

– 4 3 summarize annual and typical daily emissions from wind

blown dust by major land use category for Maricopa County and the PM 10 

### nonattainment area.

Table 3.5

– 4 2

. Annual and typical daily emissions from fugitive windblown du st for Maricopa County

. Annual Emissions (tons/yr) Avg. Daily Emissions (lb/day)

Land Use Category PM 10 PM 2.5 PM 10 PM 2.5 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

– 4 3

. Annual and typical daily emissions from fugitive windblown dust for the PM 10 NAA.

Annual Emissions (tons/yr) Avg. Daily Emissions (lb/day)

Land Use Category PM 10 PM 2 .5 PM 10 PM 2.5 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 3 4.6 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 3,946.62008 Maricopa Co. PM 10 Emission Inventory 80 June 2011 

### 3.5.11 Summary of all miscellaneous area sources

Tables 3.5

– 4 4 and 3.5

– 4 5 provide a summary of annual and typical daily emissions from all

miscellaneous area sources, for Maricopa County and the PM 10 

### nonattainment area, respectively.

Table 3.5

– 4 4

. Annual and typical daily emissions from al l miscellaneous area sources for Maricopa County.

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

Source Category PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 2,05 9.00 308.85 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

Liv estock 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 4,87 0.8 1,838.3

Offroad re c. 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

– 4 5

. Annual and typical daily emissions from all miscellaneous area sources for the PM 10 NAA.

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

Source Category PM 10 PM 2.5 NO

x S O

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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

Co tton 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

Windblo wn 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 61,982.02008 Maricopa Co. PM 10 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 PM 10 

### 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) Typi cal daily emissions (lbs/day)

Source Category PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 2 6.25 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 9,3 70.0 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 4 86.1 425.4 132.9 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 8,131.52008 Maricopa Co. PM 10 Emission Inventory 82 June 2011 Table 3.6

– 1

. Summary of ann ual and typical daily emissions from all area sources in Maricopa County.

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

Category PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 te sting 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 2 9.7

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 park ing l ots 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 PM 10 NAA.

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

Category PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

Fuel Combustion

Industri al 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

Residen tial 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 1,44 2.0 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 14 2.7 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 const ruction 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 11,034.42008 Maricopa Co. PM 10 Emission Inventory 83 June 2011 Table 3.6

– 2 (cont’d). Summary o f annual and typical daily emissions from all area sources in the PM 10 NAA.

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

Category PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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

Prescrib ed 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 l ots 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 7,6 93.04 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

inven tory 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 t he latest Emission

Inventory Improvement Program (EIIP) guidance available. EPA’s guidance for area source

cate gories included in the draft 2002 National Emission Inventory (NEI) was also evaluated, as

area source emissions from this inventory will be su bmitted to EPA for the 200 8 NEI. The list of

area source categories developed based on these guidance documents was modified to fit the

charac teristics of Maricopa County, with some area source categories determined to be insignifi

cant (such as industri al 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

f

or 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 nonatt ainment area. When local data was not2008 Maricopa Co. PM 10 Emission Inventory 84 June 2011 

### available, state data from Arizona State agencies (such as the Arizona Department of Transport

ation) and regional bodies (such as the Western Regional Air Partnership, WRAP) were used.

National

- level data (such as t hose 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 calcu

l ations.

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 p ossible 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, AP

42, 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

determi ne 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

emis sions 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 sour ce

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 s ent to the Arizona Department of Environ

mental 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 200 8 NEI.

The QA/QC activities described here have produced hig h 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. PM 10 Emission Inventory 85 June 2011 

### 3.8 References

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Service, September 2003.

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econinfo/FILES/20 08AZestimates.pdf

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ASLD, 200 9

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Land Department, Re: 2008 wildland fire data for Maricopa County, e

- mail message, April

2 0, 2009

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Am monia Emission Factors, p. 6

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### State Implementation P lan for Clark County (Nevada), Appendix B:

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and L ife Safety (DFBLS) , R e : data request

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message, May 4, 2009. .

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3, 2004.

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### Emission Inventory for the Maricopa

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### for

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, Appendices Volume One. Maricopa Association

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### for t he Maricopa

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- mail message, February13, 2009.

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for PM 10 

### for the Maricopa County, Arizona, Nonattainment Area, May 2007, Available at:

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t.aspx

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– Universe: Occupied

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.2008 Maricopa Co. PM 10 Emission Inventory 87 June 2011 

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21)

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.2008 Maricopa Co. PM 10 Emission Inventory 88 June 2011 

### US EPA, 2001 b . Residential Wood Combustion. Emission Inventory Improvement Program

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– Fugitive Dust. Emission Inventory Improvement

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- mail message, Ju ly 28, 2009.

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– Phase II. Project

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address: .

http://wrapair.org/forums/dejf/fdh/index.html

WRA P 2006d. Fugitive Dust Handbook. Chapter 13.0 Livestock Husbandry, September 2006.

Internet address: .

http://wrapair.org/forums/dejf/fdh/index.html

.2008 Maricopa Co. PM 10 Emission Inventory 89 June 2011 

## 4. Nonroad Mobile Sources

4.1 Introduction

N onroad 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 equip ment, 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 equ ipment, 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 equipmen t, 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 sw itching and line haul trains.

Emission calculations for most nonroad mobile source categories except aircraft, airport ground

support equipment (GSE) and locomotives we re derived using EPA’s N ONROAD model , ver

. 2008.1.0 (Core version 2008, April 2009 ). A ircraft and airport GSE emission estimates were

made using the Federal Aviation Administration’s EDMS (Emissions Dispersion Modeling

System) model, v er. 5.1.1. Locomotive emission calculations we re 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 NON

ROAD model. Monthly temperature and fuel data were provided by the Ariz ona Department of

Weights and Measures. The following table lists the local county inputs used:2008 Maricopa Co. PM 10 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) Et hanol (EtOH) Blend

E t OH

(Vol %) Market

Share ( % ) Total Oxygen

(wt%) Max. Min. Average

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 me asurements we re not available, the average of June, July, August and September data wa s used.

† Since measurements w ere not available, the average of October, November, January, February, March and April data wa s used.



### EPA recommends adjusting default NONROAD model values (such as equipment population,

activity levels of equipment, growth factors, etc.) where local dat a 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

equip ment were adjus ted 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 NH 3 

### . Ammonia emiss ion calcu

lations for the NONROAD model were derived by using a multiplier of NO

x 

### emissions

developed by ENVIRON (2003).

Spatial allocation factors were developed (based on EPA guidance documents) to apportion non

road emis sions to the PM 10 

### nonattainment area. The approaches used are described in each

se ction of this chapter.

Temporal allocations (used to calculate PM 10 

### average

- day emissions) for nonroad equipment

cate gories modeled in the NONROAD model come from EPA recommendations on week day

and weekend day activity levels for each nonroad equipment c ategory (US EPA, 1999). Table

4.1

– 2 lists the weighted activity level allocation fractions for each equipment class for week days

and weekend days. For this report, the most conservative (highest) allocation fraction in each

nonroad equipment class was u sed to calculate average

- day emissions.2008 Maricopa Co. PM 10 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 0.166 6667 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 0.350000 0

Railway maintenance 0.1800000 0.0500000

Recreational 0.1111111 0.2222222



### 4.2 Agricultural equipment

Annual emissions from agricultural equipment in Maricopa County were c alculated using EPA’s

NONROAD model as discussed above. County

- wide results ar e shown in Table 4.2

– 1.

Table 4.2

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

PM 10 PM 2.5 NO

x SO

x NH 3

34.27 33.24 365.55 0.14 0.67



### Annual emissions for the PM 10 

### nonattainment area were calculated based on EIIP guidance (US

EPA, 2002) which recom mends using the ratio of agricultural land inside the nonattain ment area

to agricultural land in side the county . See Section 1.5.2 for a discussion of land use data used.

PM 10 NAA emissions from

= Total County PM 10 emissions × Agricultural land use allocation factor

agricultural equipment from agricultural equipment

= 34.27 tons × 44.14 %

= 15.13 tons PM 10 /yr

Table 4.2

– 2. Annual emissions (tons/yr) from agricultural equipment in the PM 10 NAA.

PM 10 PM 2.5 NO

x SO

x NH 3

15. 13 1 4 .67 16 1.35 0.06 0.3 0



### County average

- day emissions were calculated by multiplying annual emissi ons (generated by

the NONROAD model) by the most conservative weekday/weekend day activity allocation fac

tor 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 PM 10 = Annual PM 10 × daily activity allocation factor × 2000 ÷ 52

daily emissions emissions for agricultural equipment ( lbs/ton ) (w ks /yr )

(lb s/day) (tons/y r) (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.

PM 10 PM 2.5 NO

x SO

x NH 3

219.7 213.1 2,343.3 0.9 4.32008 Maricopa Co. PM 10 Emission Inventory 92 June 2011 

### PM 10 

### nonattainment area average

- day emissions were calculated by multiplying County average

day emissions by the agricultural land use allocation factor:

PM 10 NAA average

- = Maricopa County PM 10 × Agricultural land use allocation factor

day emissions average

- day emissions

= 21 9.7 lbs/day × 44.14 %

= 100.4 lbs/day

Table 4.2

– 4. Typical daily emissions (lbs/day) from agricultural equipment in the PM 10 nonattainment area.

PM 10 PM 2.5 NO

x SO

x NH 3

97.0 9 4.0 1,0 34.3 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 Emis sions Dispersion Modeling

System (EDMS, v. 5.1.1) from the U.S. Federal Aviation Admini stratio n (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 popu

lations and activity patterns. In most cases, a ctivity data on 2008 aircraft operations and GSE /

APU usage was obtained from individual airport surveys issued by MAG and/or MCAQD.

Where survey response s were incomplete or information was otherwise unavail able, activity data

was estimated using comm ercially avail able data, and EDMS default assump tions where appro

priate. Further details concerning the modeling input data and results are presented in Section

4.11 of this report.

For Luke Air Force Base ( AFB ) , e missions estimates for ground support equipment were o b

tained from a recent base

- wide mobile source emissions inventory for calendar year 2008 that

h a d recently been completed for the US Air Force (Weston, 2010). Using d ata on the frequency

and intensity of usage for each type of equipment, annual emissions were calculated as in the

following example for a light car t equipped with a diesel engine:

E pol = ELHP × OT × LF × EF / CF

w here:

E pol = Annual e missions 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 NO

x 

### emissions all similar pieces of this type of GSE was calculated as:

E N O x = 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 tpy2008 Maricopa Co. PM 10 Emission Inventory 93 June 2011 

### GSE emissions from the Luke AFB study wer e 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 throug hout the week and year; thus daily emissions were esti mated 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 PM 10 

### nonattainment are a , 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 PM 10 nonattainment area

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

GSE 14.92 14.39 497.97 13.62 * 14.72 14.21 490.28 13.42 *

APUs 12.29 12.29 88. 76 12.8 2 * 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 emiss ions from aircraft operations.

Table 4.3

– 2. Typical daily emission s (lb) from airport GSE and APU usage

. Maricopa County PM 10 nonattainment area

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

GSE 81.5 78.7 2,721.1 74.4 * 80.4 77.7 2,679.1 73.3 *

APU s 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 fro m commercial equipment in Maricopa County were c alculated using EPA’s

NONROAD model, as described in Section 4.1. Annual emissions for the PM 10 

### nonattain ment

area for this category were derived by applying the ratio of industrial employment in the non

at tain ment area to Maricopa County

- level totals, as data on the number of wholesale establish

ments 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. Annu al emissions (tons/ y r) from commercial equipment usage.

Maricopa County PM 10 nonattainment area

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 calculat ed by multiplying Maricopa County annual emis

sions (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). PM 10 

### nonattain

ment 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 Co unty PM 10 nonattainment area

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

756.2 724.2 8,943.8 15.4 135.4 754.2 722.4 8,920.6 15.3 135.02008 Maricopa Co. PM 10 Emission Inventory 94 June 2011 

### 4.5 Construction and mining equipment

Annual emissions from construction and mining equipment in Maricopa County w ere c alculated

using EPA’s NONROAD model as described in Section 4.1. Annual emissions for the PM 10



### non attainment area for this category were derived by applying the ratio of construction employ

ment in the nonattainment area to Maricopa County

- level tot als 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 fo r a discussion of the employment data used.

Table 4.5

– 1. Annual emissions (tons/yr) from c onstruction and mining equipment usage.

Maricopa County PM 10 nonattainment area

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 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 emis

si ons (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 numb er of weeks (52) in the year (US EPA, 1999). PM 10 

### 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.

Maricop a County PM 10 nonattainment area

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 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 c alculat ed using EPA’s

NONROAD model, as described in Section 4.1. Annual emissions for the PM 10 

### nonattain ment

area for this category were derived by applying the ratio of industrial employment in the non

attainment area to Maricopa County

- level totals as a cons ervative estimate, as the number of

employees in manufacturing recommended by EIIP guidance (US EPA, 2002) was un available.

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 PM 10 nonattainment area

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 emis

si ons (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). PM 10 

### nonattain ment 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 PM 10 nonattainment area

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

651.8 634.4 16,622.7 20.6 360.5 650.1 632.7 16,579.4 20.6 359.52008 Maricopa Co. PM 10 Emission Inventory 95 June 2011 

### 4.7 Lawn and garden equipment

Annual emissions from lawn and garden equipment in Maricopa County were ca lculated using

EPA’s NON ROAD model, as described i n 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

PM 10 

### non attainment area for this category were derived by applying the ratio of population in the

non attain ment area t o Maricopa County

- level totals ( since data on housing units was unavail able,

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 PM 10 nonattainment area

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

182.2 8 168.79 798.14 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 emis

si ons (generated by the NONROAD model) by the most conservative weekday/weekend day

activity allocation fac tor for lawn and garden equipment (0.1600000 for the commercial seg

ment, 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). PM 10 

### nonattainment area average

- day emissions

were ca lculated 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 PM 10 nonattainment area

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 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 ca lculated using

EPA’s NON ROAD model, as described in Section 4.1. Annual emissions for the PM 10 

### n on

attainment area for this category were derived by applying the ratio of water surface area in the

nonattainment area to Maricopa County

- level totals, as recom mended by EIIP guidance (US

EPA, 2002). See Section 1.5.2 for a discussion of the land use da ta used.

Table 4.8

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

Maricopa County PM 10 nonattainment area

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 emis

si ons (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 numb er of weeks (52) in the year (US EPA, 1999). PM 10 

### 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 PM 10 nonattainment area

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

124.5 114.9 1,046.5 11.4 23.3 94.5 87.3 794.6 8.6 17.72008 Maricopa Co. PM 10 Emission Inventory 96 June 2011 

### 4.9 Railway maintenance equipment

Annual emissions from railway maintenance equipment in Maricopa County were ca lculated

using EPA’s NON ROAD model, as described in Section 4.1. Annual emissions for the PM 10 

### nonattainment area for this categ ory were derived by applying the ratio of population in the

nonattainment area to Maricopa County

- level totals, as recommended by EIIP guidance (U S

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 PM 10 nonattainment area

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 emis

si ons (generated by the NONROAD model) by the most conservative weekday/weekend day

activity allocation factor for railway maint enance 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). PM 10 

### non

attainment 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 PM 10 nonattainment area

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 fro m recreational equipment in Maricopa County were c alculated using EPA’s

NONROAD model, as described in Section 4.1. Annual emissions for the PM 10 

### nonattain ment

area for this category were derived by applying the ratio of passive open space and vacant lan d

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 C ounty PM 10 nonattainment area

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

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 emis

si ons (generated by the NONROAD mo del) 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). PM 10 

### nonattain

ment area average

- da y emissions were calculated based on land use as described above.

Table 4.10

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

Maricopa County PM 10 nonattainment area

PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3

389.6 358.8 545.3 3.6 18 .0 65.7 60.5 91.9 0.6 3.02008 Maricopa Co. PM 10 Emission Inventory 97 June 2011 

### 4.11 Aircraft

Emissions from aircraft operations at the largest civilian airports in Maricopa County were esti

mated using the Federal Aviation Administration’s Emis sions and Dispersion Model (EDMS,

v. 5.1.1). The EDMS mod el combines specified aircraft type and activit y levels with default

emission factors in order to estimate annual emissions inventories for a specific airport. The

model cal culates emissions of sulfur oxides (SOx), oxides of nitrogen (NOx), carbon monoxi de

(CO), and volatile organic compounds (VO C) , and, for a small subset of aircraft and engine

types), PM 10 

### and PM 2.5 

### as well. The model also estimate s emissions from affiliated ground sup

port equip ment (GSE) and auxiliary power units (APUs); these emiss ions are reported separately

and are summar ized 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. S pecifically

, the number of landing and takeoff

cy cles ( LTO’s) or touch and go operations (TGOs), along with i nformation 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 data bases, such as the FAA ’s Air Traffic Activity System

(ATADS) and Enhanced Traffic Manage ment 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 a s

part of a base

- wide 2008 mo bile source emissions inven tory 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 eng ine testing

– considered a “mobile source” emission category.

As with all other airports includ ed 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 t he area,

Luk e reported two additional, type s 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 distinct ive

combination of the times in mode (TIM); (e.g., ap proach, taxi in/out, takeoff and climb out.)

Luke AFB ’s emissions are not based on the number of LTOs, but rather the aggregate annual

o perational time in modes (TIMs) for all aircraft of similar type. For the F

- 16, an LTO cycle

include s five modes of op eration : idle (taxi in/out), intermediate, approach, military and after

burner. 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 source s for eac h 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, air

craft emissions were estimated for four aircraft categories:

**•** 

### Air carriers (abbreviated “AC”): Larg er 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. PM 10 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

Source 1 Fleet Mix Data

Source 2 Aircraft

Type 2008

Operations

Buckeye Municipal BXK airnav.com Generic GA profile GA 26,535

Chandl er 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 GE U 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 SD L 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 pr ofile 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,

ht tp:// 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 opera

tions at this airport in 2008, further information on the aircraft types co mprising this activity was2008 Maricopa Co. PM 10 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 d atabase on general aviation activity at CHD in 2008 comprises 152 different air

craft types, totaling 3,589 operations

, (See Table 4.11

– 2). To simplify modeling input require

ments, this aircraft

- specific activity data was ranked in order of decreasing fr equency and

activity data for the most frequently reported aircraft was then grown to represent all general

aviation (“ GA ”) activity, a s shown in Table 4.11

– 2 below.

Table 4.11

– 2. Example showing how most common aircraft

- specific activity was grown for E DMS modeling.

Rank Aircraft Type ETMSC

reported

o perations % of total

r eported

o perations Cumulative

Percent “Grown”

o perations 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 Cher okee 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 Marine r 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

1 4 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 sub

set 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 PM 10 

### emissions only for a relatively small number of

aircraft/e n gine types, all model outp ut files were reviewed for missing data. For those aircraft/

engine combinations for which the EDMS model indicated zero PM 10 

### 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 d efault PM 10 emission factors for aircraft , by activity type

.

Activity type PM 10 Emission Factor ( lb/LTO)

Air Carrier , Air Taxi, Military 0.60333

General Aviation 0.23672008 Maricopa Co. PM 10 Emission Inventory 100 June 2011 

### Following EPA guidance (US EPA, 2003) , PM 2.5 

### emissions were estimated to be 92% of PM 10



### levels. Fo r ease in modeling computation and the assessment of emissions, all activity was

ass umed to occur evenly through out the year. Thus, average daily emis sions were calculated by

dividing annual totals b y 366 ( = days per year in 2008 ) . Table s 4.11

– 4 and 4.11

– 5 list the total

annual emissions and average daily emissions of each airport and aircraft type , and for airport s

within and outside the PM 10 

### NAA, respectively

.

Table 4.11

– 4

. Annual and average daily emissions, by airport and aircraft type

, from airports with in the

PM 10 NAA

.

Cate

gory Annual emissions (tons/yr) Typical daily emi ssions (lbs/day)

Airport PM 10 PM 2.5 NO

x SO

x PM 10 PM 2.5 NO

x SO

x 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 M unicipal 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

Phoe nix 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

PM 10 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 r eported in Weston (2010): (1) aircraft stationed at Luke AFB, (2) transient aircraft , and

(3) on

- wing aircraft engine testing.2008 Maricopa Co. PM 10 Emission Inventory 101 June 2011 Table 4.11

– 5. Annual and average daily emissions, by aircraft type, from airports outside the PM 10 NAA.

Facility Cate

gory A nnual emissions (tons/yr) Average daily emissions (l bs/day )

PM 10 PM 2.5 NO

x SO

x PM 10 PM 2.5 NO

x SO

x Buckeye Municipal GA 3.14 2.89 2.70 0.97 17.2 15.8 14.8 5.3

Gila Bend Mun icipal GA 0.21 0.19 0 .18 0.06 1.1 1.1 1.0 0.3

Wickenburg Municipal GA 0.77 0.7 3 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

Bur ling ton Northern/Santa Fe Railway (BNSF), Union Pacific Railway (UP) and Amtrak.

Railway opera tions 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

multip lying 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)

PM 10 PM 2.5 NO

x SO

x NH 3

Class I haul line 0.015 0.014 0.394 0.004 0.00 01

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.

PM 10 emissions from

= Diesel use ( gals/yr ) × PM 10 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

= 5 8

. 35 tons PM 10 /yr

Table 4.12

– 2. Total diesel use and annual emissions from locomotives in Maricop a County.

Locomotive type Diesel use

( gals/yr ) Annual emissions (tons/yr)

PM 10 PM 2.5 NO

x SO

x NH 3

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



### PM 10 

### nonattainment area emissions were calculated by multiplying Marico pa County emissions

by the percentage of track miles within the PM 10 

### nonattainment area, determined by GIS

mapping. Results are shown in Table 4.12

– 3.

PM 10 nonattainment area emissions

= County PM 10 emissions × Percentage of track miles within

from UP Class I haul lines (tons/yr) (tons/yr) the PM 10 nonattainment area

= 5 8

. 35 tons PM 10 /yr × 44.27%

= 25.83 tons PM 10 /yr2008 Maricopa Co. PM 10 Emission Inventory 102 June 2011 Table 4.12

– 3. Annual emissions (in tons/yr) from locomotives in the PM 10 NAA.

Locomotive type Track in

nonattain ment

area (%) Ann ual emissions (tons/yr)

PM 10 PM 2.5 NO

x SO

x NH 3

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



### PM 10 

### typical daily emissions for both the county (shown in Table 4.12

– 4) and the PM 10 

### non

attainment area (Table 4.12

– 5) were calculated by dividing annual totals by 36 6 days ( since 2008

was a leap year) , as locomotive activity is assumed to be uniform throughout the year.

PM 10 typical daily

= Annual PM 10 emissions (tons) × 2000 lbs/ton ÷ 36 6 days

emissions from haul lines

= 58.35 tons PM 10 /yr × 200 0 lbs/ton ÷ 36 6 days

= 31 8.9 lbs PM 10 /day

Table 4.12

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

Locomotive type PM 10 PM 2.5 NO

x SO

x NH 3

BNSF Class I haul line 30.7 28.7 807.5 8.2 1.9

UP Class I haul line 318.9 297.6 8,3 75.5 85. 0 20. 2

BNSF yard/switch operations 16.4 15.3 46 0.1 4.4 1.0

UP yard/switch operations 15.5 14.5 43 5.0 4.1 1.0

Amtrak 2. 1 2.0 56. 4 0.6 0.1

Totals: 38 3.6 35 8.1 10, 134.5 102. 3 24. 3

Table 4.12

– 5. Typical daily emissions (in lbs/day) from locomotiv es in the PM 10 nonattainment area.

Locomotive type PM 10 PM 2.5 NO

x SO

x NH 3

BNSF Class I haul line 13.6 12.7 35 7.5 3.6 0.9

UP Class I haul line 141. 2 13 1.8 3,7 07.8 37. 6 8.9

BNSF yard/switch operations 16.4 15.3 46 0.1 4.4 1.0

UP yard/switch operations 15. 5 14.5 43 5.0 4.1 1.0

Amtrak 0.0 0.0 0.0 0.0 0.0

Totals: 18 6.7 174. 2 4,9 60.4 49. 8 11. 82008 Maricopa Co. PM 10 Emission Inventory 103 June 2011 

### 4.13 Summary of all nonroad mobile source emissions

Table 4.13

– 1 summarizes annual and daily emissions of PM 10 

### , PM 2.5 

### , NO

x 

### , SO

x 

### and NH 3 

### from

nonroad mobile sources in Maricopa County . Table 4.13

– 2 shows annual and typical daily emis

sions for these pollutants for the PM 10 

### 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 PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 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 117.97 112.9 8 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

Tab le 4.13

– 2. Annual and typical daily emissions from nonroad mobile sources in the PM 10 NAA.

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

Category PM 10 PM 2.5 NO

x SO

x NH 3 PM 10 PM 2.5 NO

x SO

x NH 3 Agricultural 15.13 14.67 161.35 0.06 0.30 9 7.0 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 maintenan ce 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 spread

sheets 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 rev iewed 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 Envi ronmental 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. PM 10 Emission Inventory 104 June 2011 

### US EP A, 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.

Availabl e 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. E PA4 20

- 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 Ba se Years 1970

– 2001. Rept. p repared 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 EP A, 20 10 . 2008 National Emissions Inventory, Nonpoint : Fertilizer Application, May

2010. Internet address: .

http://www.epa.gov/ttn/chief/net/2008inventory.html

. US EPA, 2009. Emission Facto rs 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 M obile Source Air Emissions Inventory for Luke Air Force

Base. Rept. prepared for Air Education and Training Command (AETC)

, US Air Force,

Randolph AFB, TX. J une 2010. .2008 Maricopa Co. PM 10 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: PM 10 

### , PM 2.5 

### , nitrogen oxides (NO

x 

### )

, sulfur dioxides (SO 2 

### ), and ammonia (NH 3 

### ). PM 10 

### refers to all particles less than or equal to 10

micrometers in diameter and PM 2.5 

### refers to particles less than or equal to 2.5 micrometers in

diameter.

Onroad mobile source emissions were estimated for t he PM 10 

### 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 b y 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 est imate emissions from exh aust, tire wear, and brake wear

.

The MOVES2010a modeling accounted for the oxygenated fuel and the Arizona Vehicle Inspec

tion/Maintenance (I/M) programs applied in Maricopa County in 2008. The fuel use assump

tions, including oxy gen 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) e stimates by facility type and road type were derived from the 2008 Highway Perform

ance 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 re gistration

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 th e 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 PM 10 Non

attainment Area (MAG, 2007) were applied to estimate 2008 paved road particulate emis sions

for the PE I.

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. PM 10 Emission Inventory 106 June 2011 

### The main references for preparing the onroad mobile source por tion 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

• M otor Vehicle Emission Simulator (MOVES)

- User Guide for MOVES2010a, (EPA,

2010c).

5.2 Exhaust, tire wear, and brake wear emissions

Vehicle exhaust emission factors for PM 10 

### , PM 2.5 

### , NO

x 

### , SO 2 

### , and NH 3 

### , as well as tire wear and

brake wear emission factors f or PM 10 

### a nd PM 2.5 

### , were calculated using MOVES2010a. The

exhaust PM 10 

### a nd PM 2.5 

### 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 esti mates is Ieesuck Jung (602

- 254

- 6300).

5.2.1 MOVES2010a model

The emissions not related to fugitive dust w ere 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 inpu t data for each month of the year and each geographical area (Maricopa County

and the PM 10 

### NAA). Each scenario was created using the County Domain/Scale and the Inven

tory 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 VM T, 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 f uel 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 PM 10 

### NAA. The specific

MOVES tables for f uel data are presented in Appendix 5.2008 Maricopa Co. PM 10 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 ins pection. 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 impor

tant to note that participation in the I/M program is required for all vehicl es registered in the

PM 10 

### 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 PM 10 

### NAA and Maricopa County

participate in the I/M program and the remaining 8.4 p ercent 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 Nonattain

ment 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 PM 10 

### 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 PM 10 

### 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 sourc e emission category called off

- network emissions. In MOVES2010a, these off

network 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 sou rce types

using the match

- up table (Table A.1) in the EPA’s technical guidance (EPA, 2010a). The

vehicle population in the PM 10 

### 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 PM 10 

### 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. PM 10 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 cre ated 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 PM 10 

### NAA. The specific MOVES table for source

type age dis tribution 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 estim ates 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 PM 10 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 787Urban 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 functiona l

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 typ e 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 previ ous 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 distr ibution is presented in Appendix 5.2008 Maricopa Co. PM 10 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 V MT. 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 [MonthV MTFraction], [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 accum ulated

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 method ology was applied to develop the

speed estimates for the PM 10 

### NAA. The specific MOVES table [AvgSpeedDistribution] for the

average speed distribution is presented in Appendix 5.

5.2.2.10 Ramp fraction

MOVES2010a requires the ramp fraction, which represen ts 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 VHT s 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 wit h the RunSpec files described in Appendix 5 to obtain exhaust,

tire wear, and brake wear emissions for PM 10 

### , PM 2.5 

### , NO

x 

### , SO 2 

### , and NH 3 

### . These values were

obtained for the following twelve vehicle classes: light duty gasoline vehicles (LDGV), light

duty gas oline 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 vehi cles 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 type s: rural interstate, rural principal

arterial, rural minor arterial, rural major collector, rural minor collector, rural local, urban inter

state, urban freeway/expressway, urban principal arterial, urban minor arterial, urban collector,

urban local, and o ff

- network, which was newly added in MOVES2010a; by weekdays and week

end days; by month.2008 Maricopa Co. PM 10 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 on

road 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 emiss ions, 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 calc ulated annual and average daily PM 10 

### , PM 2.5 

### , NO

x 

### , SO 2 

### , and NH 3 

### emissions by facility type and vehicle class in the PM 10 

### NAA and Maricopa County,

respectively. Emission estimates for PM 10 

### and PM 2.5 

### in these tables represent exhaust, tire wear,

and brake we ar emissions.

Table 5.2

– 2. Annual and average daily onroad mobile source emissions by facility type and vehicle class in

the PM 10 NAA.

Facility

Type Vehicle

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

PM 10 PM 2. 5 NO

x SO 2 N H 3 PM 10 PM 2. 5 NO

x SO 2 NH 3

Rural

Interstate LDGV 2201001110 4.03 2.36 113.80 1.39 8.47 PM 10 PM 2. 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 1 6.5 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 0.0 0 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 0.22008 Maricopa Co. PM 10 Emission Inventory 111 June 2011 Table 5.2

– 2. Annual and average daily onroad mobile source emissions by fa cility type and vehicle class

in the PM 10 N AA (continued).

Facility

Type Vehicle

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

PM 10 PM 2. 5 NO

x SO 2 NH 3 PM 10 PM 2. 5 NO

x SO 2 NH 3

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 2201 080150 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 8 1.8 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 0.0 4 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 0.12008 Maricopa Co. PM 10 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 PM 10 NAA (continued).

Facility

Type Vehic le

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

PM 10 PM 2. 5 NO

x SO 2 NH 3 PM 10 PM 2. 5 NO

x SO 2 NH 3

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 2,1 59.31 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

LDD T 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 1,89 8.68 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 10.35 725.6 3 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

2BHDD V 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 4,0 55.08 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 1.42008 Maricopa Co. PM 10 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 PM 10 NAA (continued).

Facility

Type Vehicle

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

PM 10 P M 2. 5 NO

x SO 2 NH 3 PM 10 PM 2. 5 NO

x SO 2 NH 3

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 0.1 3 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

Of

f

Network 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

2BHDD V 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 1 68.2 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 0.02008 Maricopa Co. PM 10 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 em issions (tons/year) Average daily emissions (lbs/day)

PM 10 PM 2. 5 NO

x SO 2 NH 3 PM 10 PM 2. 5 NO

x SO 2 NH 3

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 1.4 0 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 22010801 30 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 223 0072130 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 10 7.1 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 22 01070150 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

2BHDD V 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 22300741 70 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 0.02008 Maricopa Co. PM 10 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)

PM 10 PM 2. 5 NO

x SO 2 NH 3 PM 10 PM 2. 5 NO

x SO 2 NH 3

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 11.7 7 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 3.82008 Maricopa Co. PM 10 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)

PM 10 PM 2. 5 NO

x SO 2 NH 3 PM 10 PM 2. 5 NO

x SO 2 NH 3

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

L DGT2 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

A rterial 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 96 3.0 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 14 1.59 121.06 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 2230 001310 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 93 7.13 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 3.7 0 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 1.32008 Maricopa Co. PM 10 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

Cla ss SCC Annual emissions (tons/year) Average daily emissions (lbs/day)

PM 10 PM 2. 5 NO

x SO 2 NH 3 PM 10 PM 2. 5 NO

x SO 2 NH 3

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

MH DDV 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 MOVES

2010a 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 Emissi on

Factors, AP

- 42 (EPA, 2006). The new AP

- 42 equation published by EPA in January 2011 has

bee n applied to estimate the PM 10 

### and PM 2.5 

### 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 free

ways, high

- traffic a rterials, 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 classi

fied as low

- traffic; all other roads that are not freeways are classified a s 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 pro

vided by the Arizona Department of Transportation. The fugitive dust emission factors for

paved roads were deri ved by applying the following AP

- 42 equation:

E = k × sL 0

. 91 

### × W 1

. 02 

### × ( 1

− P 4 N ⁄ )

where: E

= annual average particulate emission factor (g/mile),

k

= particle size multiplier for particl e size range (1.0 g/mile for PM 10 

### and 0.25 g/mile

for PM 2.5 

### ),

sL

= road surface silt loading (0.02 g/m 2 

### for freeways, 0.067 g/m 2 

### for high

- traffic

arterials, and 0.23 g/m 2 

### 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. PM 10 Emission Inventory 118 June 2011 

### P

= annual number of “wet” days with at least 0.254 m m (0.01 in) of precipitation (39

days 3



### N

= annual number of days (366 days in 2008). in 2008), and

The annual average PM 10 

### and PM 2.5 

### emission factors for paved roads derived from the AP

- 42

equation are presented in Table 5.3

– 1.

The 2008 VMTs by silt loa ding category were used to estimate paved road fugitive dust emis

sions. Daily VMTs by silt loading category for the PM 10 

### NAA and Maricop a County are shown

in Table 5.3

– 2. The VMTs were derived by applying geographic information systems (GIS) to a

2008 t raffic assignment output by the MAG travel demand model, TransCAD. The 2008 week

day traffic volumes output by TransCAD were normalized to 2008 HPMS VMTs for the PM 10 

### NAA and Maricopa County to produce the VMTs by silt load ing 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)

PM 10 PM 2.5

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 loadi ng category for paved roads.

Daily VMT

Silt Loading Category PM 10 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

PM 10 

### NAA and Mari copa 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 PM 10 NAA (lbs/day) Maricopa County (lbs/day)

P M 10 PM 2.5 PM 10 PM 2.5

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 PM 10 

### NAA. Five committed measures that reduce paved road

particulate emissions were quantified in the MAG 200 7 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 loca l climatological data at Phoenix Sky Harbor Airport.2008 Maricopa Co. PM 10 Emission Inventory 119 June 2011 

### status in 2008. In addition, Table 5.3

– 4 includes emission reduction credit for 97 PM 10



### - certified

street sweepers purchased by December 31, 2007 with FY 2001

– 2006 MAG Congest ion

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 benefit s in Table 5.3

– 4 were subtracted from the uncontrolled PM 10 

### emissions in

Table 5.3

– 3. The total 2008 PM 10 

### emission reduction of 11,851.1 pounds per day in the PM 10 

### NAA represents 24.5 percent of the uncontrolled PM 10 

### emissions of 48,431.6 pounds per day.

This percent reduction was applied to the uncontrolled PM 2.5 

### emissions in the PM 10 

### NAA; then

the absolute reduction in PM 2.5 

### emissions due to the control measures was applied to the uncon

trolled PM 2.5 

### 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 pav ed road fugitive dust in the PM 10 NAA 4

Committed Measures in the MAG 2007 Five Percent Plan .

PM 10 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 PM 10 - certified sweepers (Measure 24) 166.9 911.9

4. Pave or stabilize ex isting 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 PM 10 - certified sweepers purchased with FY 2001

– 2006 CMAQ funds: 1,172.8 6,408.6

Total 2008 PM 10 e mission reduction s 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)

PM 10 PM 2.5 PM 10 PM 2.5

PM 10 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 particulat e 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. PM 10 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 PM 10 

### and 0.18 lb/mile

for PM 2.5 

### ),

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 PM 10 

### and 0.00036 lb/mile for PM 2.5 

### ),

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 PM 10 

### and 0.1453 pounds per mile for PM 2.5 

### . The unpaved alley emission factors are 0.9203

pounds per mile for PM 10 

### and 0.0918 pounds per mile for PM 2.5



### .

The 2008 daily VMTs on unpaved roads and alleys in the PM 10 

### NAA and Maricopa County are

shown in Table 5.3

– 6. The 2008 VMT for unpaved roads in the PM 10 

### NAA was derived from

the MAG 2009 Unpaved Road Inventory (MAG, 2010). The 2008 VMT f or 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 PM 10 

### NA A

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 PM 10 

### 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

PM 10 NAA 47,984 5,915

Maricopa County 50,239 6,1932008 Maricopa Co. PM 10 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 PM 10 NAA

PM 10 NAA 87,153 1.000

Maricopa County 91,257 1.047



### Multiplying the unpaved road emissio n factors by the VMTs in Table 5.3

– 6 results in the uncon

troll ed 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 PM 10



### .

Ta ble 5.3

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

Geographic Area PM 10 (lbs/day) PM 2.5 (lbs/day)

Unpaved Roads Unpaved Alleys Unpaved Roads Unpaved Alleys

PM 10 NAA 69,835.9 5,443.6 6,972.1 543.0

Maricopa County 73,117.8 5,69 9.4 7,299.7 568.5



### The MAG 2007 Five Percent Plan contains a number of committed measures that reduce un

paved road and alley fugitive dust emissions in the PM 10 

### NAA (MAG, 2007). Four committed

measures that reduce unpaved road and alley PM 10 

### e missions w ere 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 Measu res in the MAG 2007 Five Percent Plan PM 10 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 PM 10 emission reductions for unpaved roads: 2,065.4 11,286.4



### The r eductions in Table 5.3

– 9 were subtracted from the uncontrolled PM 10 

### emissions in Table

5.3

– 8. The total 2008 PM 10 

### emission reduction of 11,286.4 pounds per day represents 15.0 per

cent of the total uncontrolled unpaved road and alley PM 10 

### emissions of 75, 279.5 pounds per day

in the PM 10 

### NAA. This percent reduction was applied to the uncontrolled PM 2.5 

### emissions in the

PM 10 

### NAA; then the absolute reduction in PM 2.5 

### emissions due to the control measures was

applied to the uncontrolled PM 2.5 

### emissions in Mar icopa 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)

PM 10 PM 2.5 PM 10 PM 2.5

PM 10 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 projec ts that paved unpaved roads in 2008.2008 Maricopa Co. PM 10 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 aver age daily emissions for PM 10 

### , PM 2.5 

### , NO

x 

### , SO 2 

### , and NH 3 

### from all onroad mobile sources in Maricopa County in 2008. Similar data

for the PM 10 

### NAA are presented in Table 5.4

– 2.

Table 5.4

– 1. Annual and average daily emissions from all onroad mobile sources i n Maricopa County.

Emission

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

PM 10 PM 2.5 NO

x SO 2 NH 3 PM 10 PM 2.5 NO

x SO 2 NH 3 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)

PM 10 PM 2.5 NO

x SO 2 NH 3 PM 10 PM 2.5 NO

x SO 2 NH 3

Exhau st, 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 che cks, were

conducted by MAG in developing the 2008 TransCAD traffic assignment network used to gener

ate 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 PM 10 

### emissions inventory was

reviewed using published EPA quality rev iew 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. PM 10 Emission Inventory 123 June 2011 

### 5.6 References

MAG, 2000. Revised MAG 1999 Serious Area Particulate Plan for PM 10 for the Maricopa

County Nonattainment Area, 2000.

MAG, 2007. MAG 2007 Five Percent Plan for PM 10 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 Requirement s for Ozone State Implementation Plans, EPA

450/4

- 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 Emi ssion Inventories, EPA

454/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 Emissi on 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

- D

07

- 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. PM 10 Emission Inventory 1 24 June 2011 

### This page intentionally blank.2008 Maricopa Co. PM 10 Emission Inventory 125 June 2011 

## 6. Biogenic Sources

6.1 Introduction

Biogenic emissions have been estimated for the 2008 Periodic Emissions Inventory for particu

late matte r in Maricopa County (9,223 square miles) and the PM 10 

### 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 emis

sions model developed by the National Center for Atmospheric Research (NCAR). Some impor

tant 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 PM 10 

### NAA. Among the

chemical species included in MEGAN, only nitric oxide (NO) is attributable to particulate matter

formation. Therefore, only NO

x 

### emissions are included in the inventory. The MEGAN runs

were executed by the Maricopa Association of Govern ments. 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 an d outpu ts are given in user

- defined two

- dimen

sional 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 Marico pa Nonattainment Area (MAG, 2007 and 2009), were employed for

the PM 10 

### NAA and Maricopa County, respectively. The definitions of these two domains in the

Universal Transverse Mercator (UTM) coordinate system are pre sented in Table 6 .2

– 1. Since

MEGAN est imates biogenic emissions for entire modeling domains rather than specific areas,

additional input files, masking areas covered by the PM 10 

### 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 tar get area. As shown in Figure 6. 3

– 1, biogenic

emissions for the PM 10 

### 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 UT M coordinate system.

Grid Horizontal

Resolution Grid Size Domain Range (km) Target Area

4

- km 50 × 29 (297,3652) to (497,3768) PM 10 NAA

12

- km 111 × 84 ( 275, 3188) to (1

, 057,4196) Maricopa County



### 6.3 Input data

To calculate biogenic emissions using M EGAN, the following gridded input files for land cover

and meteorological data were prepared:

1. EFMAP_LAI file: This file provides emission factors (EF) f or 20 MEGAN species

including NO, and monthly average leaf index (LAI) for 12 months for each grid cell

.2008 Maricopa Co. PM 10 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 meteorolog ical parameters including temperature,

short wave radiation, wind speed, humidity and soil moisture for each grid.

Figure 6.3

– 1

. Mask of the PM 10 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 502008 Maricopa Co. PM 10 Emission Inventory 127 June 2011 

### at a base resolu tion of 30 seconds latitude by 30 seconds longitude (~ 1× km 2 

### ) 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 data

sets, 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 dat a from nation

- wide stations, one of which is located in

no rthern 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 temper ature, wind

speed, humidi ty 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 MEG AN inputs.

Figure 6. 3

– 2

. Boundaries of the PM 10 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 com pared to other

state s with higher precipitation. Only moisture delivery by Arizona monsoons leads to precipi

tation during the summer. This precipitation, in turn, increases soil moisture and humidity.

According to weather records at the Phoenix Sky Harbor International Air port, the precipitation2008 Maricopa Co. PM 10 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 dayTemperature (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 dayDownward short wave radiation (W/m2) 

### in the Phoenix area was 0.0 and 2.15 inches in June and July 2008, respect ively. Therefore,

maxi mum monthly NO emissions occurred in July 2008. In general, how ever, NO emissions in

the Maricopa County area are temperature and r adiation dominated during the year. Figure 6.3

–

3 shows annual mean diurnal cycles of temperature and radiation. T he 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 occ urs 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 temp erature

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 f or 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 emis

sions 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. PM 10 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, 2008Total NOx emissions (tonnes/month) NA_NOx

MC_NOx Table 6. 4

– 1

. Daily mean biogenic emissions of NO

x in the PM 10 NAA and Maricopa County , by month

.

PM 10 NAA Maricopa County

Month kg/day lbs/day kg/day lbs/day

Jan uary 127.2 280.4 355.2 783.1

Feb ruary 168.0 370.4 480.9 1,060.2

Mar ch 413.3 911.2 1,131.0 2,493.4

Apr il 601.7 1,326.5 1,658.8 3,657.0

May 721.0 1,589.5 1,923.1 4,239.7

Jun e 1,818.8 4,009.8 4,729 .4 10,426.5

Jul y 1,878.7 4,141.8 4,930.0 10,868.8

Aug ust 1,702.0 3,752.3 4,485.1 9,888.0

Sep tember 1,331.9 2,936.3 3,784.7 8,343.8

Oct ober 651.1 1,435.4 1,839.9 4,056.3

Nov ember 328.5 724.2 910.8 2,008.0

Dec ember 138.6 305.6 388.0 855.4



### Monthly mea n emissions for Maricopa County and the PM 10 

### NAA are illustrated in Figure 6.4

–

1 . Monthly emission v alues are presented in Table 6.4

– 2 . It can be seen that the monthly NO

x 

### emis sions 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 p recipitation. As discussed in S ection

6.3, there were 2.15 inches of precipitatio n in July, but no precipitation in June, 2008. There is

also one more day in July than June; therefore, the total NO

x 

### monthly emissions in July are

higher than in June.

Figure 6.4

– 1. Monthly emissions of NO

x in Maricopa County (pi nk solid line, abbreviated as “MC”) and the

PM 10 NAA (blue solid line, abbreviated as “NA”).2008 Maricopa Co. PM 10 Emission Inventory 130 June 2011 Table 6.4

– 2. Monthly biogenic emissions of NO

x in the PM 10 NAA and Maricopa County

.

PM 10 NAA Maricopa County

Month Metric tons/mo Tons/mo Metric tons/mo Tons/m o

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 NO

x 

### emissions for Maricopa County and the PM 10 

### 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 improv ements 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 PM 10 

### NAA.

Table 6.5

– 1. Daily mean and annual total NO

x emissions from biogenic sources.

Geographic Area Daily mean Annual total

kg/day lbs/day Metric tons /yr T ons/yr

Maricopa County 2,218.1 4,890.0 813.08 896.27

PM 10 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 MEGA N

- 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 Documentatio n

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 PM 10 

### for the Maricopa County PM 10



### Nonattainment Area

. The document is now available for an informal 30

- day public

review period. The PM 10 

### emissions inventory includes emissions estimates for PM 10



### and PM 2.5 

### as well as three particulate matter precursors: nitrogen oxides (NO

x 

### ), sulfur

oxides (SO

x 

### ) and ammonia (NH 3 

### ).

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 manufact uring 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 sour ces (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 d epartment’s

website at:

http://www.maricopa.gov/aq/divisions/planning_analysis/emissio ns_inventory/Defau

lt.aspx

The Air Quality Department will hold a public workshop to discuss the draft 2008

Periodic Emissions Inventory for PM 10 

### . 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

1 001 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 Emission s



# INSTRUCTIONS

FOR REPORTING 200 8

ANNUAL AIR POLLUTION EMISSIONS

January 200 9

Emissions Inventory Unit

1001 North Central Avenue, Suite 595

Phoenix, Arizona 85004

(602) 506

- 6790

(602) 506

- 6 17 9 (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 t o Complete You r 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 Ce rtification Form (for NON

- Title V sources)

................................ ................................ ........ 21

How to Calculate an Emission Fee ( for Title V s ources ONLY )

................................ ...................... 22

Data Certification/Fee Calculation Form (for Title V sources ONLY )

................................ ............ 2 3

### Maricopa County Emissions Inventory Unit 1 Instructions for Reporting 2008 Emissions 

# WHAT'S NEW FOR 2008 ?

Reporting forms :

**•** Some prepr inted information on your report may be different from last year ’s version . Please

revi ew the enclosed forms carefully, and verify all prepr inted 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 con form to the current information

requirements and FORMAT as supplied on our preprinted forms. “Homemade” reporting forms that

vary significant ly from the preprinted forms sent to you will not b e accepted.

**•** Please VERIFY that your reporting forms match the preprinted forms.

Miscellaneous :

**•** If this is the first emission s 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 Perm it. 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 typ e of business. For most permitted sources , the packet you received from

us contains the necessary prepr inted forms based on your site’s most recent emissions inventory.

1. Business Form : Contains general co ntact 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, NO

x 

### , PM

10 

### , or SO

x 

### ). 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 p age 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 

# } Either or both will be required for all businesses. 5. Evaporative Process Form :

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. Da ta 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 C ertification/Fee C alculation F orm . All other sources use the Data C erti fication F orm.

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 inf ormation on how to complete the most common forms is

inc luded 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 documentat ion for at least FIVE YEARS at the location where

pollution is being emitted.

STEP 4 : Make sure the Data Certificati on 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 corres

pondence and applicable check s 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. 44 th 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

NO

x 

### = Nitrogen oxides

PM 10 

### = Particulate matter less than 10 microns

SO

x 

### = Sulfur oxides

VOC

= Volatile organic compounds *

HAP&NON

= Hazardous Air Pollutant (HAP) that is also NOT a volatile organic compound (VOC) **

NH

x 

### = Ammonia and ammonium compounds

Pb

= Lead

* A volatil e organic compound (VOC) is defined as any compound of carbon that participates in atmos

pheric photochemical reactions. This definition excludes : carbon monoxide, carbon dioxide, acetone,

carbonic acid, metallic carbides or carbonates, and ammonium carbo nate, 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 200.69 b states:

“The following compound(s) are VOC for purposes of all recordkeeping, emissions reportin g, 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).”

T herefore, 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 contin ue 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 m ust be used. The hierar chy listed below outlines the preferred methods for c alculating emission

estimates ( taken from County Rule 280, Section 305.1 ). :

(1) Whenever avai lable, emissions estimates should be calculated from continuous emissions

monitors certified under 40 CFR Part 75, Sub part 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 avai lable,

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 describe d in paragraph s 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 usin g 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 i n paragraphs 1 through 4 is not

available, emissions estimates sh ould 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 SEC RETS

- 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 wi thout 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, specificall y 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 An y 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. Prov ides 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 whi ch 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 inc orrect or blank, please provide

correct information. Making a change on the Business Form will NOT transfer the permit ownership or

location. You must contact th e 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 I D 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 g als. 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 inter nal combustion engines less than 600 h p 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 simila r 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 the se 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. 09 d 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 ASSIST ANCE :

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 proces ses.

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 pol lutant . 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 boot h**  Lat: N 33. 5276

Long: W 1 1 2. 26 2

6

**2 V**  **14** ft **200** o F **19,186 40**  **thermal oxidizer , Bldg. 2** 

Lat: N

3

3

. 52 59 Long: W 1 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 L ength and inside

Width in inches

.



### 7 Stack Name/Description and Lat/Long Coordinates : Provide a brie f 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 whi ch 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 de vice.

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 requir ed if the Stack Form is used for your site

(see page 9 ) and the control device is vent ed through that identified stack. This is the ID number shown

in column 1 of the Stack F orm . The Stack ID can be entered on this form after t he 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 PM

10 

### is emitted by processing rock products, processing materials such as wood or cotton, and driving

on unpave d areas.

Data fields: (See sample forms on pages 1 3 and 1 4 .)

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 calc ulated 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 C ontent (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. 0 5 % (= 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 wi th 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

p age 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)

1 5 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 provid e details of your calculations i n an attachment.

1 7 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 facto r, 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

emissi on rates before controls. A “NO” response requires the use of Formula B (see # 25 below).

1 9 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 fa ctor. 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 spec ific 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 2 4 : 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.

2 1 Primary Control Device ID : If this pollutant is being contro lled in this process, enter the Control

Device ID number which represents the first control device affecting the pollutant.

2 2 Secondary Control Device ID : If this pollutant is being controlled sequentially by 2 devices, enter

the Control Device ID numbe r which represents the second control device; otherwise leave this field

blank.

2 3 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 affec ted. If you report control device

efficiency, you must also show capture efficiency in column 20

.

2 4 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.

2 5 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 emissio n factor :

Column 2 5 = line 11 **×** line 1 4 **×** column 1 6

B. Emissions after control :

Column 2 5 = line 11 **×** line 1 4 **×** column 1 6 **×** (1

– [column 20 **×** column 2 3 ])

Use the decimal equivalent for columns 20 and 2 3 . 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) **V 99999** 



### Place an X in any gray cell to mark data requested to be held confidential. See p age 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

1 4

- 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

1 5 1 6 1 7 1 8 1 9 20 2 1 2 2 2 3 2 4 2 5

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) **V 99999** 



### Place an X in any gray cell to mark data requested to be held confidential. See p age 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)



### ______________ **%**

1 3

- Unit of Measure: (for example: tons, gallons, million cu ft, acres, units produced, etc.) 

### VMT

1 4

- Unit Conversion Factor (if needed to convert Unit of Measure to correlate with emission factor units)



### Emission Factor (EF) Information Control Device Information

1 5 1 6 1 7 1 8 1 9 20 2 1 2 2 2 3 2 4 2 5

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. 2**  **5 are calculated as follows:**  **(line 11 ×**  **col. 1 6**  **) ×**  **(1**

**– [col.**  **20 ×**  **col. 2 3**  **])**

* 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 storag e

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 sa mple forms on pages 1 7 and 1 8 .)

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 Decembe r 2008 . The t otal 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 represen ts 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 p age

6 of these instructions for more exp lanation 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.

Exa mples 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 y ear. 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 NH

X 

### (see definitions on

page 3 ). When one process (or material) has more th an 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 o n the quantity of material used in a process. Emission factors can be obtained from your supplier

(usually provided on a Mat e 

### rial 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) al l prepr inted 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 se nt 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/Disp osal 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 blan k 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 fo rm.

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 Recycl ing/Disposal Form. Round to the nearest pound. If the

answer is 0, give a decimal answer to the first significant digit. Column 1 5 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) **V 99999** 



### 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 Schedu le: 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**  **L acquer** 

**6455**

**- 06**  **95 gl**  **VOC 4.7**  **gal** % % **447**

**801 1**  **lacq thinner 120**  **gl VOC**  **7.1 gal**  % % **852**

**802 1**  **P aint**  **red**

**4039**

**- 03**  **940 gl**  **VOC 4.2**  **gal** % % **3,948**

**803 1**  **p ain**  **t 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 prepr inted 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 recy cling/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) **V 99999** 



### 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** Ho urs/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 prepr inted 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) **V 99999** 

**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 busi ness location. A waste stream is the waste from one

or more processes mixed together t o 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# 0 1 for first waste stream

. Make copies of a blank Off

- Site Recycling/Disposal form a nd use 0 2 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 th e average pollutant content of the waste stream? NOTE: Report in the s ame units ( pounds or gal lons ) as us ed

in line 2

.

VOC **4.25** lbs/ unit HAP&NON lbs/ unit NHx lbs/ unit

**NOTE: W**  **aste 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 a nd 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 L ine 2) **×** (pollutant content, from L ine 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 co ntributed to the waste stream**  **(e.g.**

**, Process ID #6 contribu**  **ted 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 t otal for each pollutant type reported on line 4. The quantities

you report below for each pollutant and process mu st 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, et c.



## Emission Factor Calculation

Process ID **201** Permit number **V99999**

**Emission factors derived from source test performed 12**  **/ 2**  **/ 0**  **0 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 li sting 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: 23,23 1**  **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 Off**

  ** site Recycling / Disposal Form example.**

**This process can also be used to find the weighted average emission factor for**

**similar mate rials 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 =**  **5.67**

**lb/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**

NH

x 

### 0 **0 0** 

Lead **0 0**  **0**

HAP&NON 

### 0 **0 0** 

VOC 

### 24,220 **0 24,220** 

NO

x 

### 9,815 **0 9,815** 

SO

x 

### 645 **0 645** 

PM 10 

### 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. 44 th Street, Suite 200 , Phoenix, AZ 8500 8

- 6538 . Keep a copy of all forms for your records.



### CONFIDENTIALITY STATEMENT:

This annual emissions report contains requ ests 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 penalt y 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 c alcula te 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 PM 10 

### should be reported on line 5 of the Data Certific ation/Fee

Calculation form

, “ [f]ugitive emissions of PM 10 

### from activities other than crushing, belt tr ansfers, screening,

or stacking ” (County Rule 280, § 305.2d) are NOT subject to annual emission fees. The most common

occurrences of these PM 10



### - producing activities that are NON

- billable are listed below :

SCC codes and description of PM 10 

### - 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. D ivide 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 **V 99999** 

For EACH pollutant listed, total up all emissions recorded on your General Process and Evaporative Process Forms. Enter thes e

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 Dep artment ) 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. 44 th Street, Suite 200 , Phoenix, AZ 8500 8

- 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 Certifi cation 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 he rein

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**

NH

x 

### 0 **0 0** 

Lead **0 0**  **0**

PM 10 

### (non

- billable; see page 2 2 ) **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 NO

x 

### 9,815 **0 9,815** 

4 SO

x 

### 645 **0 645** 

5 PM 10 

### (billable; see page 2 2 ) **6 91**  **0 6**  **91**

6 Add “TOTAL” column from lines 1 through 5 ONLY: 

### 35

**, 371**  lbs.

7 D ivide 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. PM 10 Emission Inventory A3

– 1 June 201 1 

## Appendix 3

. Rule Effectiveness (RE) Studi es

3.1 Introduction

Rule effectiveness (RE) studies are designed to assess the success of regulatory rules at control

ling 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% com pliance with

those requirements. Given this reality, the US EPA recommends the use of rule effe ctiveness

studies to improve the quality of emission estimates presented in emission inven tories.

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 esti mates 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:

Uncontroll ed Emissions × [1

– (Control Efficiency)] = Emissions with Control

100 tons × [ 1

– (0.90) ] = 10.0 tons



### Emissions including the application of rule effectiveness:

Uncontroll ed 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 guidan ce:

...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 con

clude that a control device that operates in conjunction with a continuous emis

sions monitor, or is equipped with an automatic shut down 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 cat egories of control devices routinely operate at

effic iencies 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 ex ample, a process with a control device of 99.9% efficiency may report

controlled emis sions 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 evalu ated the affected processes on a case

- by

- case basis to determine the

appropriateness of applying an RE adjustment.2008 Maricopa Co. PM 10 Emission Inventory A3

– 2 June 201 1 

### 3.2 Calculating Rule Effectiveness Rates for Rules 310, 310.01, and 316

Rule effectiveness studies adjust the emissions from subject facilities and source categ ories to

account for times of non

- compliance and control device equipment failure. Of particular import

ance to the Maricopa County Air Quality Department (MCAQD) are those rules that control

particulate matter release, since parts of the county have been desi gnated as non attainment areas

in regard to US EPA PM 10 

### standards. Consequently, the rule effectiveness studies presented here

deal with the control of criteria pollutant PM 10



### .

S ource

- specific rule effectiveness studies were undertaken as part of this proj ect to adjust the

emissions from subject facilities and source categ ories 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 s ource

- specific studies use data from inspections con ducted from July 2008

through June 2009 to determin e the rat e of compliance of sub ject facilities and source categories

with R ule 310 ( F ugitive D ust fro m D ust

- G enerating O perations), R ule 310.01 ( F ugitive D ust

from N on

- T raditio nal S ources of F ugitive D ust), and R ule 316 ( N onmetallic M ineral P rocessing)

with final RE rates listed in Table A3

– 1 below. R ule effectiveness rates were calculated sepa

rately 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 A 3

– 1. R ule 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 inven

tory 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

o f rule effectiveness studies (U S 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 o r 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 ef fectiveness 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 previ

ous r ule 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 r ate at which inspection staff is ob serving 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 sou rces 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 t he fact that these studies not only2008 Maricopa Co. PM 10 Emission Inventory A3

– 3 June 201 1 

### cont ain 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 sou r ces 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 com

pliance” if no violations were issued or an administrative based violation was issued.

A total of six distinct rule effecti veness rates were calculated for use in this emissions inventory:

f

our source

- specific rule effectiveness determinations (R ule 310, Rule 310.01, Rule 316 and

agricultural activities) along with two multi

- rule determinations (Title V and no n

- Title V per

mi tted 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

S ources 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 non

compliance (i.e., “in vi olation”) 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 includ ed 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 inspecti on during the 12

- month period of July 2008

– June 2009. Conversely, o ver 59 % of all issued permits that received

a compliance determination inspection were inspected two or more times, with some sites receiv

ing 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 viola tions noted, 55 0 ( 80 % ) were emissions

related (track

- ou t, visible emissions, recordkeeping, silt content, etc.), with the remaining 137

( 20 % ) violat ing 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 89.9 4 %.2008 Maricopa Co. PM 10 Emission Inventory A3

– 4 June 201 1 

### 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 ba sed upon vacant lot

inspection compliance rate s

.

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 compli

ance. Conversely, if the lot’s surface is deemed to be unstable , then a v iolation of Rule 310.01

has occurred. As with Rule 310, a compliance rate is determined i ndividually 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 5 92 violations noted by inspectors were emissions

related violations, as all the violations are for unstable soil conditions.

3. 2 .3 Calculating Rule Effectiveness for Sources Subject to Rule 31 6

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

facili ties 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 wa s d etermined in a similar fashion as

for Rules 310 and 310.01 ; i .e., calculated on the basis of the actual observed compliance rate s of

permitted sites

.

Inspection data for the period July 2008 through June 2009 reveal that inspections were con

ducted for 136 issued permits for Rule 316 facilities. All of these facili ties were inspected at

least once during this study period

, with a compliance determination made for each facility.

Ove rall, 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 violat ing permits noted, 47 (54 % ) were emissions

- related , with the remaining 40 ( 4 6 % )

primarily procedural in nature.

3. 3 Calculating Rule Effectiveness Rates for A gricultural A ctivities, Title V Facilit i es, 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 appro

priate violations. There may be instances when a rule violation goe s unnoticed by staff, or2008 Maricopa Co. PM 10 Emission Inventory A3

– 5 June 201 1 

### 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 meas ures that affect overall

rule effectiveness; measures l ike the strength of rule language, depart mental 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 en ough to describe the compliance effect

ive ness 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 effective

ness 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 regula tory agency.

Evalu ating these factors will provide a more complete evaluation of the effective

ness 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 late st guidance (2005) provides a listing of factors that can impact rule

effectiveness rates (e.g., inspector training, frequency of inspections, media outreach, enforce

ment policies, recordkeeping requirements, etc.), grouped into major categories such as m ost

important factors, important factors and other factors. The department used the se 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 account s for 70% of the overall RE

rate, while all other factors account for the re maining 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 implementi ng 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 settlem ent of, observed violations associated with the subject rule or source category. The

complete matrices for each applicable rule or source cate gory for which rule effectiveness was

addressed, are contained in Tables A3

– 3 through A3

– 5

.

The following sectio ns 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 per mitted

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. PM 10 Emission Inventory A3

– 6 June 201 1 

### 3. 3 .1 Calculating Rule Effectiveness for Agricultural Activities

Agricultu ral 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 manage

ment practices were chosen to be used during various operations ( e.g., ha rvesting , tilling). No

compliance rate estimates for this program were noted d uring the study period. ADEQ does

indicate that after a site has been visited, 100% of the sources return to compliance. Since com

pliance with this program is verified only on a complaint

- driven basis, the weight given to com

pliance history was lowered, from 70% to 25%, in t he 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 rat es have been calculated for permitted Title V and non

- Ti tle V facilities. Factor

based matric es have been utilized to develop R E rates for Title V and non

- Title V facilities.

Compliance rate s f or 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 com bi nation 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 com bined compliance rate fo r Title V facilities is 89.14% and 81.00%

for non

- Title V facilities , resulting in RE rates o f 90.94% and 84.27% for Title V and non

- Title

V facilities, respectively , as sho wn in Tables A3

– 4 and A3

– 5 below.

3.4 References

MCAQD, 2007. 2005 Periodic Emissions Inventory for PM 10 

### for the Maricopa County, Arizona,

Nonattainment Area.

US EPA, 1992 . Guidelines f or Estimating and Applying Rule Effectiveness f or 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. PM 10 Emission Inventory A3

– 7 June 201 1 

### 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/

P ercentage 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 exist2008 Maricopa Co. PM 10 Emission Inventory A3

– 8 June 201 1 

### 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. PM 10 Emission Inventory A3

– 9 June 201 1 

### 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. PM 10 Emission Inventory A3

– 10 June 201 1 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 compli

ance certification. 2% 97% 1.94%

87% 93% 90% Source subject to Title V or other type of compli

ance certification.

81% 86% 84% Source not subject to any type of compliance certi

fication.

70% 80% 75% Source not subject to any type of compliance certi

fication.

< 70% 35% Source not subject to any type of compliance certi

fication.

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. PM 10 Emission Inventory A3

– 11 June 201 1 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. PM 10 Emission Inventory A3

– 12 June 201 1 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. PM 10 Emission Inventory A3

– 13 June 201 1 

### 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 re

quired 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. PM 10 Emission Inventory A3

– 14 June 201 1 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% Ins pection 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. PM 10 Emission Inventory A3

– 15 June 201 1 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 th e i mplementing 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 comprehen

sive 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. PM 10 Emission Inventory A3

– 16 June 201 1 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. PM 10 Emission Inventory A4–1 June 2011 

### Introduction

The production of windblown dust o ccurs through an intricate pr ocess where the force of wind

initiates the movement of soil pa rticles. As stated below,

This process has the dis tinct phases of particle en trainment, transport and

deposition. It is a complex process because it is affect ed 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, moistu re, aerodynamic roughness length,

vegetation and non-erodible elements) and land-use practice (e.g., farming,

grazing and mining). During a wind-erosi on 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 PM 10 

### emissions from windblown dust focuses on

quantifying the first phase of wi ndblown dust production: particle entrainment. The phases of

transport and deposition are typi cally 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., “O pen 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 constr ucts of the scheme (e.g., assessment of threshold

wind speeds, the importance of soil properties and land us es, etc.). Publishe d empirical data on

windblown dust emissions varies widely as well, with dust emission rates for a given wind speed

varying from 10 -1 

### to 10 5 

### 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 qual ity of the input data de scribing each of these

controlling factors (e.g., surface roughness lengths, so il 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 eff ects of a controlling fact or. 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 un certain (Alfaro et al., 2004) or could change as atmospheric or

soil conditions ar e altered throughou t 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 lo cal, observed windblown dust events combined

with empirical data from wind tunnel studies pe rformed in the deserts of the southwest U.S.

Supply-Limited Windblown Du st 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. PM 10 Emission Inventory A4–2 June 2011 

### limited, where windblown dust emissions are contro lled solely by the force of wind (Bagnold,

1941; Greeley and Iverson, 1985). Traditional dust emission sche mes perform best in areas

where contiguous desert land w ith little vegeta tion 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 Pass i, 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 part icles blasts and breaks down a ggregated soils to then be

suspended as dust emissions. However, the supp ly-limited soils of the desert southwest have

been shown to emit substantial qua ntities 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 sa ltation dominates dust production (e.g., haboob), the majority of

windblown dust emissions occur during lower intens ity, higher frequency events (e.g., synoptic

scale fronts, dust devils) (Koc h 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 PM 10 

### concentrations at these wind speeds (see further

discussion in section on Threshol d Friction Velocity). This suggest s that significant quantities of

dust emissions are generated primarily through direct aerodynamic entrainment of available

surface material, before saltation occurs. Despit e 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 importan ce 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). C onsequently, the dust scheme

chosen for the supply-limited environment of Ma ricopa County includes the process of direct

aerodynamic entrainment as a major contributor to the production of windblown dust.

Another key limitation of transport-limited scheme s concerns surface dist urbance 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 Fun g, 1995; Belnap and Gillie tte, 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 trans port-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 si ze distribution of the soil is unif orm 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 ha s been shown in relation to saltation (Gillette,

1980), but does not necessarily reflect the th reshold 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 (M acpherson et al., 2008).

Instead of directly addressing su rface disturbance, incorporati on 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 fr iction velocities, in

transport-limited schemes (Marticorena et al., 1997; Alfaro et al., 2004). Surface roughness2008 Maricopa Co. PM 10 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 el ements (e.g., rocks, vegetation, structures)

associated with land cover or la nd uses. This produces wide va riations 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 recentl y to improve the database of available surface

roughness lengths through sate llite data, but in corporation of these data has not readily occurred

and is largely focused on global scale dust emissi ons (Prigent et al., 2005). Because of the

transient nature of surface roughness lengths an d differing methodologies us ed to measure these

lengths, a reliable local database does not exist that can incorporate their effects, especially when

dealing with a large time peri od like an annual inventory (M articorena 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 ca nnot 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 simultane ously increasing friction velocities and saltation

effects, which in turn increase vertical flux emi ssions (Gillette et al., 19 98). Additionally, with

supply-limited soils in particul ar, 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 la rger reservoirs of su rface material available to be entrained as

compared to stable soils. Si nce actual surface roughness lengths of subject soils are largely

unknown and vary over time; and because surface r oughness does not directly address the effects

of disturbed soils, another variable is required to approximate distur bance levels. In this scheme,

disturbance of soils is determined through use of site-specific inspectio n data of specific land

uses gathered by Maricopa C ounty Air Quality Department (M CAQD) personnel (further detail

available in section on Threshol d Friction Velocity).

In addition to the conceptual dust scheme associ ated with supply-limited soils, empirical wind

tunnel data gathered in local supply-limited e nvironments is utilized in the development of

vertical dust fluxes. Three data sets of wind t unnel tests performed in the southwest U.S. (areas

around Barstow, California; Las Vegas, Nevada a nd southern Arizona) present empirical data on

windblown dust emission rates (Nickling and Gilli es, 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 saltati on and that disturbed soils produ ce higher dust emissions than

stable soils. These outcomes ar e expected in supply-limited envi ronments and support the use of

a dust scheme modeled around the characteristics of supply-limite d environments. Specifically,

the wind tunnel tests performed in southern Arizona (Nickling and Gillies, 1989) form the basis

of the vertical fluxes (dust emi ssion rates) used to quantify PM 10 

### emissions from windblown dust

in Maricopa County and the PM 10 

### nonattainment area (see secti on on Vertical Emission Fluxes

for further discussion).

As highlighted in the introduction, there ar e many factors that control the production of

windblown dust beyond wind speed velocities and di sturbance levels that cannot be directly

accounted for in this dust scheme (e.g., soil texture, soil moistu re, topography, land use, etc.).2008 Maricopa Co. PM 10 Emission Inventory A4–4 June 2011 

### Data for these factors can be lim ited, nonexistent or unreliable. It is also unknown what degree

of importance each of these factor s 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 we re standardized to match observed PM 10 

### monitor

concentrations when high winds were present. Th is sensitivity analysis puts the windblown dust

emission estimates in context with other emissi ons sources and provides a reality check on dust

emissions developed using only wind speed velociti es and vertical flux equations. The analysis

of PM 10 

### concentrations under elevated wind speeds estimated that approximately 10% of annual

PM 10 

### emissions are linked to high wind speeds (see Standardized Windblown Dust Emissions

section for more information). As such, windblow n dust emissions have been limited to no more

than 10% of the total annual invent ory for Maricopa County and the PM 10 

### nonattainment area.

Threshold Friction Velocity

An essential factor to any windblown dust sche me involves determining the threshold friction

velocity (represented as u *

t 

### ); the minimum wind speed at wh ich windblown dust emissions are

initiated at ground level. In r eality, the threshold friction velo city will change based upon the

individual properties of the subject soil during a ny given wind event. However, for the purposes

of development of a windblown dus t inventory, it is necessary to identify a minimum wind speed

at which dust production can th eoretically begin. The threshold friction velocity for this

inventory was identified using th e theoretical principles of ae rodynamic entrainment observed on

supply-limited soils (Macpherson et al., 2008) a nd empirical data from regional wind tunnel

tests, local meteorological data, and local PM 10 

### monitoring data.

Many dust schemes set separate threshold velo cities depending upon a measured or assumed set

of soil properties. In the absence of, or augmentation to, lo cal wind tunnel studies, soil texture

and soil roughness lengths are common variables used to determine threshold friction velocities.

In traditional transport-limited schemes, the phys ics of saltation dictate that loose, sandy soils

will have lower threshold friction velocities th an undisturbed clay- or silt-dominated soils

(Gillette, 1999). However, the role of soil textur e is unclear in the pub lished 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 desert s of the southwestern U.S. also show little

connection between soil texture and threshold fr iction 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, sugges ting that soil texture plays no distinguishable

role in setting threshold fricti on velocities. Studies in the de serts around Barstow, California

found that dust emissions were initiated for three di fferent 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 betw een 13 to 30 mph. Roney and White (2004) found

that direct aerodynamic entrainment threshold fr iction velocities are ap proximately 50 to 75%

less than saltation thresholds, suggesting that th e dust emission thresholds for southern Arizona

could be as low as 7 mph. The measured wi nd tunnel data, combined with the conceptual

ambiguity surrounding the role of soil texture, provi de limited empirical rationale to set threshold

friction velocities accordi ng to soil texture alone.2008 Maricopa Co. PM 10 Emission Inventory A4–5 June 2011 

### Large changes in surface roughness lengths have b een clearly shown to affect threshold friction

velocities of soils (Marticorena et al., 1997). However, there is no reliabl e data available to

estimate surface roughness lengths throughout Mari copa County, especially on lands where

frequent human activity is expected (e.g., agri culture, construction site s, urban vacant lots)

(Marticorena et al., 2006). As me ntioned earlier, these values ar e not static and change with

atmospheric and anthropogenic activities. Su rfaces that are known to have uniformly high

surface roughness lengths (e.g., built-out urban ar eas and mountain ranges) have already been

eliminated from the underlying land uses that are selected as possible sour ces of windblown dust.

The land uses that remain (e.g., open and vacant ar eas, 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 viab le option.

Examination of local PM 10 

### concentration and me teorological monitoring data in Maricopa

County show that when wind speeds reach a pproximately 12 mph (measured as a 5-minute

average), average PM 10 

### concentrations are consis tently higher than concen trations at lower wind

speeds. Also, as wind speeds exceed 12 mph, average PM 10 

### concentrations uniformly increase

with increasing wind speeds. Th ese monitoring stations are surr ounded by a wide variety of land

uses and differing surface roughness lengths, yet they all consistently display similar

relationships between wind speeds and PM 10 

### concentrations. Figure A4–1 displays the annual

average relationship between wind speed and PM 10 

### concentrations from f our distinct monitoring

locations which represent a variety of land uses , soil types and geogra phic conditions within

Maricopa County. Although not shown in Figure A4 -1, the remaining four monitoring stations

that collected 5-minute PM 10 

### concentration data in 2008 (Cen tral Phoenix, Durango Complex,

Greenwood and South Phoenix) show similar relationships between PM 10 

### concentrations and

wind speeds. This data, combined with the in formation 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 initiati on of windblown dust in Maricopa County.2008 Maricopa Co. PM 10 Emission Inventory A4–6 June 2011 Figure A4–1. 2008 average 5-minute PM 10 concentration by wind speed at sample Mari copa County

monitoring stations.



### Vertical Emission Fluxes

The rate at which windblown dust emissions are cr eated and suspended in air is described as a

vertical flux. Shao (2008a) describes three pro cesses 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 aggregat es 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 thro ugh an equation that represents these processes,

or empirically with the us e of wind tunnel studies.

The vertical flux rate developed for this in ventory uses wind tunnel studies performed in

southern Arizona (Nickling and Gillies, 1989). These studies were performe d under a variety of

land uses (e.g., native desert, rive rbeds, construction sites, agri cultural 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 activ ity, or having a strong 20 40 60 80 100 120 140 160 180 200

0 2 4 6 8 10 12 14 16 18 202008 Average 5-Minute PM10Concentration

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 202008 Average 5-Minute PM10Concentration

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 202008 Average 5-Minute PM10Concentration

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 202008 Average 5-minute PM10Concentration

Wind Speed (mph) West Phoenix Monitor2008 Maricopa Co. PM 10 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 groupe d by land use and by percent clay content. However, these

grouping are not useful for this inventory given that recent research (A lfaro 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. Fl uxes based upon land use groupings provide limited

information on soil condition and ignore other esse ntial soil characteristic s. Additionally, the

wind tunnel studies performed in Barstow, Califor nia and Las Vegas, Neva da (Wacaser et al.,

2006; Macpherson et al., 2008) show that soil dist urbance 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 ver tical 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 Agricult ure (see Active Agriculture section). Inactive

agricultural land uses th at are either fallow, abandoned or some other use (e.g., dairies) are

represented by the vertical fluxe s developed through the southern Arizona wind tunnel tests, as

these land uses do not have active crop cover.

To create the disturbed soil verti cal flux, a simple scatter plot of the data (frcition velocity

against PM 10 

### emissions) was made of the selected sout hern Arizona wind t unnel data. A power

relationship is then developed from the data to produce the best fit ting curve of the vertical flux.

The assembled data performs reasonably well (R 2 

### of 0.646) in developing a statistically

signifigant vertical flux (4.36 x 10 -15 

### u* 4.3961 

### g cm -2 

### s -1 

### ) for disturbed soils, given the limited

number of test sites and the la ck 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 vert ical flux rates of soils (Houser and Nickling,

2001). Despite this short coming, friction velocity remains the primary va riable 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 de veloped 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, Californi a 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. PM 10 Emission Inventory A4–8 June 2011 Figure A4–2. Vertical fl ux for disturbed soil.



### Since the southern Arizona wind tunnel tests pr ovided limited information on vertical fluxes

from stable soils, a stable soil vertical flux could not be devel oped directly from the wind tunnel

data. As a surrogate, the ratio of stable to disturbed vertical fluxe s found in the wind tunnel

studies performed in Barstow, California (M acpherson et al., 2008) was used to develop the

vertical flux for stable land us es. The Barstow area study contai ned multiple tests done on stable

and disturbed soils at the same te st sites. This allows for a direct comparison of the windblown

dust emission rates between stable and disturbed so ils. Data from all of the Barstow wind tunnel

tests were used except for the tests done on salt-crust ed soils (dry lake beds), as this type of soil

is rare in Maricopa County. The results of th e Barstow studies indicate that the stable soil

vertical flux was found to produce emissions at a ra te 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 di sturbance is not feasible (i.e., soil conditions

are constantly changing) in an area as large as Maricopa County. Activit ies on land uses subject

to windblown dust are regulated by MCAQD rules th at require specific acti vity-related control

measures that stabilize the soil. Compliance an d 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 peri od of July 2008 through June 2009

produced rule effec tiveness rates of 90% for developing land uses (R ule 310), 65% for sand and

1 For disturbed surfaces a flux of 2.35 x 10 -12 u* 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 -12 u* 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 th at can represent emissions from stable southern Arizona soils. y = 4.36×10 -15 u * 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 65PM10Emissions (g cm-2s-1)

Friction Velocity, u * (cm/s) Vertical Flux for Disturbed Soil2008 Maricopa Co. PM 10 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, thes e 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 disturbe d), the Rule 316 rate of 65% se rves 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 an d 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 PM 10 

### emission

estimates, PM 10 

### 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 othe r sections of this

inventory. Selection of a 5-minute average for th e wind speed value was chosen because it is the

shortest duration of wind speed available th at is constantly measured. Windblown dust

production has been shown to be more closely corr elated with gusts than with averaged wind

speeds (Cakmur et al., 2004; Engelstaedter and Wa shington, 2007). However, gusts (usually 1-

second maximums) are not constantly measured wh ich does not allow for their use in calculation

of emissions in an annual invent ory. Thus, the 5-minute average wind speed is selected as the

input wind speed in both vertical fluxes (see Wi nd 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 di sturbed soil

and stable soil emission factor per each wind speed bin. The mi dpoint 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 equation 2



### 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 disturbe d 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 so il and disturbed soil emission fa ctors for each wind speed bin (by

land use category) and the ratio of stable to dist urbed soil emissions observed in the Barstow area

wind tunnel studies.

2 The fluid dynamics Prandtl equation: ܷ ൌ ௨ כ

௞ ݈݊ ௭

௭ ೚ , allows for the calculation of u* at various 10-meter wind

speeds by solving for u* : ( ݑ כ ൌ ܷ ௞

௟௡ ೥

೥ ೚ ), where U is wind speed at 10 meters, k is Von Karman’s constant (0.4), z is

10 meters, and z

o is measured surface roughness va lue. An average value of 0.025cm (as measured during southern

Arizona wind tunnel tests) was assumed for z

o Once u * is calculated for each wind speed bin, that value is then

inserted into the vertical flux rate to de velop the emission factors seen in Table A4-1.2008 Maricopa Co. PM 10 Emission Inventory A4–10 June 2011 Table A4–1. PM 10 emission factors for stable and dist urbed land uses by wind speed bin.

% of

Land

Use

Category PM 10 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 – Calc ulated 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 -15 u * 4.3961 g cm -2 s -1 20.16% 17.33% 14.94% 13.29% 12.06%



### Land Use Data

The Maricopa Association of G overnments (MAG) maintains GIS da ta 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 asse mbles and maintains its GIS database is

included as Attachment I of this Appendix. In addition to data provid ed by MAG, the Arizona

Cotton Research and Protecti on Council (ACRPC) provided supplemental GIS information on

agricultural field crops in portions of Area A in Maricopa C ounty. 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 freque nt disturbance. Other land us es 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 windbl own dust on a consistent basis. Land uses on

steeply sloped rocky terrain we re 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 sour ces 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 PM 10

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 convertin g to built uses

Landfill 2,705 2,705 Community refuse disposal sites

Mining 3,329 2,004 Rock quarries/pits

Passive Open Space/Wash 1,861,49 3 341066 State/National parks, bo mbing range, dry rivers/washes

Sand & Gravel 11,112 10,350 Sand & Gravel processing facilities

Vacant 1,930,606 395,902 Devel opable/unprotected open spaces2008 Maricopa Co. PM 10 Emission Inventory A4–11 June 2011 Figure A4–3. Distribution of land use categorie s capable of producing windblown dust emissions.



### Meteorological Data

Thirty-four meteorological stati ons were used for source data to compile calendar year 2008

wind speed and precipitation for this inventory of windblown dust. Th is includes eleven stations

operated by the Arizona Meteorol ogical Network (AZMET), twenty-t wo stations operated by the

Maricopa County Air Quality Department (MCA QD), 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 collec tion methods that preclude “apples-to-apples”

comparisons with data from the meteorol ogical stations included in this work. 3 

### Figure A4–4

displays the location of the in cluded meteorological stations.

3 National Weather Service (NWS) stations report wind speed s in 2-minute averages at the time of posting, while

AZMET, MCAQD and PCAQCD all report wind speed in hour ly 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 Area2008 Maricopa Co. PM 10 Emission Inventory A4–12 June 2011 Figure A4–4. Location of meteorological stations.



### Wind Speed Data

For this analysis, 5-minute average wind speeds fo rm 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 captur e the effects of gusts while still allowing for

emission estimates to be developed. This ap proach also allows fo r 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 ar e 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 sele cted meteorological stations were uniformly

adjusted to speeds at 10 meters (to account for the differenc e in anemometer heights) through use

of a standard wind profile power-law equation:

ܷ

௭ 

### ൌ ܷ

௥ 

### ሺܼ/ܼ

௥ 

### ሻ ௣



### where U

z 

### is wind speed (in mph) at 10 meters, U

r 

### is wind speed (in mph) at referenced

anemometer height, Z is 10 meters, Z

r 

### 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 Area2008 Maricopa Co. PM 10 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:

ൌ ݌ ln ሺ ܷ ሻ െ lnሺܷ

௥ 

### ሻ

ln ሺ ܼ ሻ െ lnሺܼ

௥ 

### ሻ

The stations used in comparis on were all assumed to have similar surface roughness lengths to

each other as the stations were between 1–3 mile s 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 we ll 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 valu es 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-mi nute 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, 2 5–30 mph, and 30–35 mph; a nd (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 assigne d 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 record ed 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 an d grown 5-minute average wind speed s 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 r ecord 5-minute average wind speeds 4 

### , regression equations were

developed (based upon those MCAQD stations that do report 5-mi nute 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. PM 10 Emission Inventory A4–14 June 2011 

### majority of wind speed counts exist in the lo wer 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% c onfidence 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 mete orological stations in this study are shown in Table A4–5.

Table A4–4. Regression equation, p -value, and R 2 for interpolating 5-minute ave rage wind speeds, by bin.

5-minute average

wind speed bin Regression equation p -value

(probability) R 2

12-15 mph y = 827.00 + 19.80 x 0.00007056 77.55%

15–20 mph y = 150.05 + 11.92 x 0.00000006 93.77%

20–25 mph y = –8.34 + 1.39 x 0.00000021 92.09%

25–30 mph y = –4.20 + 0.31 x 0.00009300 76.42%

30–35 mph y = –0.99 + 0.07 x 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 82008 Maricopa Co. PM 10 Emission Inventory A4–15 June 2011 

### Because wind speeds vary dramatically between di fferent 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 subj ect to windblown dust. This is accomplished by

assigning the wind speed counts in Table A4–5 in GI S (spatial joining) to the land uses nearest

each meteorological station through a series of Thiessen polygons 5 

### (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 dus t, as opposed to “smearing” averaged wind

speed counts across all of Maricopa County and the PM 10 

### 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 depict ion displaying the number of values for the 15–20 mph wind speed bin.



### Precipitation Data

During days with precipitation, windblown dust emissions are severel y, if not completely,

limited. Precipitation also increases overall so il moisture which acts as a control on the

production of windblown dust afte r 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 road s 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 Polygon2008 Maricopa Co. PM 10 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 Windbl own 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 PM 10



### are calculated for both the PM 10 

### nonattainment area and Maric opa County. These emission

estimates represent the maximum potential emissi ons from each land use category since they are

a product of only local wind speeds and emission fact ors developed from soils expected to emit

high levels of dust. These em issions will be standardized (adjusted to match observed PM 10 

### concentration under high winds) in the next secti on to account for a range of controlling factors

(e.g., surface roughness leng ths, soil moisture, vegetation, suppl y-limitation, etc. ) where either

adequate quantitative data does not exist or cannot be represente d as a unique variable in an

emission estimate equation (see section on Standa rdized Windblown Dust Emissions). Figure

A4–6 contains a flow chart showing the steps involved in calculating PM 10 

### emissions from

windblown dust.

Figure A4–6. Flow chart of steps involved in developing PM 10 emissions from windblown dust.



### Calculation of pre-standardized emission estimates begins thr ough 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 categor y polygon with associated

wind speed bin counts. The land use and wind speed specific emission fact ors 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% di sturbed). Base data

and emissions from a sample vacant land use polygon are shown in Table A4–6. All prestandardized emissions from land use categories ex cept 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 PM 10

concentrations2008 Maricopa Co. PM 10 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 Emissions 3 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 windbl own dust production, windblown dust from active

agricultural areas (fields or orch ards 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 virtua lly eliminate the possibility of windblown dust

from these types of fields. T hus, windblown dust from active agricu ltural fields is calculated

using a soil erodibility formula developed by the U.S. Department of Agriculture (in US EPA,

1974):

E

s 

### = a I C K L’ V’

where E

s 

### equals suspended PM in tons/acre-year, a is a constant (0.0125) representing the portion

of PM as PM 10 

### , 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 harveste d for 2008 is available through

the Arizona Agricultural Statistics Bulletin and the U.S. Department of Agriculture National

(USDA) Agricultural Statistics Se rvice for 2008 (USDA, 2008; AASS, 2009). Data for the other

variables in the equation is taken from the 1999 Serious Area PM-10 Pl an (MAG, 2000). Table

A4–7 lists the crop-specific values for each variable.2008 Maricopa Co. PM 10 Emission Inventory A4–18 June 2011 Table A4–7. Active Marico pa County agricultural acreage and defaul t values for USDA equation variables,

by crop type.

Crop 2008

Acreage a I C K L' V' E

s 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 form ula to develop annual PM 10 

### emissions from active agricultural fields is

achieved by multiplying crop type E

s 

### by the number of acres in each crop type. In addition to

applying the USDA formula, a co ntrol factor of 72.28% (1 – 27.72%) was applied to active

agricultural emission estimates to reflect the e ffectiveness of the agricultural BMP program.

This control factor is a combination of the ru le effectiveness of the BMP program (55.33%; see

Appendix 3) and the estimated control e ffectiveness of the BMP program (50.10%) 6 

### , for an overall effectiveness of 27.72%. Em issions are allocated to the PM 10 

### nonattainment area based upon

the percentage (41.35%) of agricult ural land use acres located with the nonattainment area.

Summary of Pre-standardized Windbl own 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 a nd the effects of soil moisture content.

Annual pre-standardized PM 10 

### emissions from active agricultural areas and all other land uses are

listed in table A4–8 for Maricopa County and the PM 10 

### nonattainment area.

Table A4–8. Annual pre-standardized PM 10 emissions from windblown dust in Maricopa County and the

PM 10 nonattainment area.

Land use category Annual emissions (tons/yr)

Maricopa County PM 10 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. PM 10 Emission Inventory A4–19 June 2011 

### Standardized Windblown Dust Emissions

Pre-standardized windblown dust emission calcu lations represent maximum windblown dust

emission rates from land uses that have the capa bility to emit windblown dus t. 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 (Nickl ing 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 la nd 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 t hose areas disturbed by anth ropogenic activities, the

role of active contro ls (e.g., applying water) is not represented in the vertical fluxes. The vertical

fluxes also do not take into account the supply-limite d nature of desert soils in Maricopa County,

because the wind tunnel tests were only perfor med 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 represen ted in the wind tunnel test s, they need to be a ccounted for outside the

vertical flux equations. To account for this on an annual basis, a sensitivity analysis was

performed by comparing windblown PM 10 

### emission estimates against observed PM 10 

### concentrations under high wind conditions.

In 2008, there were eight MCAQD PM 10 

### monitors that recorded PM 10 

### concentrations and

associated wind speed in 5-minute averages. A simple test to see the impact of PM 10 

### concentrations under high winds is to compare the measured PM 10 

### mass associated with wind

speeds below 12 mph (threshold friction velocity for windblown dust ge neration) against the

mass associated with wind speeds at 12 mph or greater. While PM 10 

### concentrations are not an

exact surrogate for emissions since high wind PM 10 

### 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 PM 10 

### emissions in the area around the

monitoring site. Table A4–9 shows the percentage of PM 10 

### mass associated with wind speeds at

or above 12 mph for eight MCAQD monitors with 5-minute data.

T able A4–9. Percentage of PM 10 mass associated with wind speeds at or above 12 mph for eight MCAQD

monitors in calendar year 2008.

Monitor Sum of 5-min PM 10 mass

when 5-min winds ≥ 12mph

(μg/m 3 ) Sum of all 5-min

PM 10 mass

(μg/m 3 ) Percent PM 10 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. PM 10 Emission Inventory A4–20 June 2011 

### The analysis in Table A4–9 shows that as a weighted average, about 7.6% of annual PM 10 

### 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 ma ss associated with winds ≥ 12 mph than do more urban monitors

(e.g., Greenwood) where land us es have limited opportunity to produce windblown dust. A

simple statistical analysis of the eight monito rs produces a mean of about 7% and a standard

deviation of 4%. Given that th e monitors do not capture all emissions associated with high

winds and that the limited numbers of monitors covering a large geogra phic area like Maricopa

County do not represent all land us e mixes, it is assumed that up to 10% (within one standard

deviation of the monito r concentrations) of PM 10 

### in an annual inventory of Maricopa County and

the PM 10 

### nonattainment area is windblown dust.

Annual PM 10 

### emissions from sources other than windblown dust total 61,282.27 tons for

Maricopa County and 43,333.20 tons for the PM 10 

### nonattainment area. If windblown dust

emissions are to represent 10% of an annual inventory, than PM 10 

### emissions for the

nonattainment area and Maricopa County shoul d be standardized to 4,814.80 tons and 6,809.13

tons, respectively. 7



### Initial evaluation of the 10% standardized emissi on targets raises some questions. Despite the

presence of significantly more acreage subject to windblown dust in the areas of Maricopa

County outside the PM 10 

### nonattainment area than within, the st andardized emissions suggest that

these areas emit at a lower rate than the PM 10 

### 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 impor tant to point out initially that when high magnitude dust events

do occur (wind speeds above saltatio n thresholds) the areas outside of the nonattainment area are

going to be the dominant contribut or of windblown dust during the event. This is because as

saltation occurs, supply-limitati on concerns are less important, a nd 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 genera ted on an annual basis occurs during higher

frequency/lower intensity wind speeds where supply-limitations cont rol 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, an d thus lower dust emissions rates. First, the rates of soil

disturbance are developed larg ely upon MCAQD inspections done only within the nonattainment

area; it is very likely that areas outside th e nonattainment area experience significantly fewer

disturbances due to their isol ation (e.g., Tonto National Forest , Goldwater Bombing Range).

Second, vegetation in vacant areas outside the n onattainment 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, signifi cantly 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 te mporary (March 2010 – February 2011) PM 10 

### monitor

located near Arlington, Arizona (approximately tw elve miles west of the nonattainment border)

indicated that appr oximately 8% of PM 10 

### concentration are associated with wind speeds ≥ 12

mph. This is the only PM 10 

### monitor that operated any significant distance outside the PM 10

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. PM 10 Emission Inventory A4–21 June 2011 

### nonattainment area. 8 

### As such, PM 10 

### concentrations associated with high winds in other areas of

Maricopa County outside the nonattainment area ar e assumed to be similar to the Arlington

monitor given the lack of mon itoring data available. Given these observations, it is not

unreasonable to assume that on an annual basis, ar eas 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 deposi tion. 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; VanCur en and Cahill, 2002). There are clearly

sources of windblown dust immediately surroundi ng 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 entrai nment, transport and deposition; while the purpose

of this inventory is to quantif y particle entrainment from sour ces within Maricopa County and

the PM 10 

### nonattainment area.

Functionally, pre-standardized emi ssions are scaled down to the sta ndardized target emissions in

two steps to account for the different emissi ons rates between Maricopa County and the

nonattainment area. The first step simply ta kes 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 ca tegories. The second step

assumes that the balance of emissions betw een the nonattainment area and the county

standardized emissi on targets, 1,994.33 tons 9 

### , 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 th e methods described in previous sections; then st andardized to

the target of 1,994.33 tons, a 99.62% re duction of pre-standardized emissions.

Summary of Standardized Wi ndblown Dust Emissions

Using the emission methodologies liste d above, annual, standardized PM 10 

### emissions for

Maricopa County and the PM 10 

### nonattainment area are calculated. PM 2.5 

### emissions are assumed

to be 15% of PM 10 

### emissions (WGA, 2006). Daily emissi ons are obtained by dividing annual

emissions by the number of days in calendar y ear 2008 (366). Annual a nd daily standardized

emissions for Maricopa County and the PM 10 

### nonattainment area are shown in Tables A4–10 and

A4–11, respectively.

8 The Buckeye monitor is also located outside the nonattain ment area, however at only a distance of 0.75 miles from

the western border. In 2008 th e Buckeye monitor had 14% of PM 10 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 PM 10 concentrations associated with high winds. However, when high wind PM 10 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 PM 10 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. PM 10 Emission Inventory A4–22 June 2011 Table A4–10. Standardized, annual and daily PM 10 and PM 2.5 emissions from windblown dust in the

Maricopa County, by land use category.

Land use category Annual emissions (tons/yr) Average daily emissions (lbs/day)

PM 10 PM 2.5 PM 10 PM 2.5 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 PM 10 and PM 2.5 emissions from windblown dust in the PM 10 nonattainment area, by land use category.

Land use category Annual emissions (tons/yr) Average daily emissions (lbs/day)

PM 10 PM 2.5 PM 10 PM 2.5 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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topographic, geomorphic a nd hydrologic hypotheses. J. Geophys. Res., 108, 4543–45572008 Maricopa Co. PM 10 Emission Inventory A4–25 June 2011 

### Attachment I

MAG 2009 GIS Existing Land Use Database Information2008 Maricopa Co. PM 10 Emission Inventory A4–26 June 2011 

## The following attachment exists in dr aft 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 creat ed 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. Addi tional 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. PM 10 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. PM 10 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 gismag2008 Maricopa Co. PM 10 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 Info rmation 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. PM 10 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 betw een 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 provi des 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 Count y 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. PM 10 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 ca lculated 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. PM 10 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 parce l’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 most2008 Maricopa Co. PM 10 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 acco mplished 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 ca ses 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. PM 10 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 t he 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 on2008 Maricopa Co. PM 10 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 int egrate 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 betw een 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 provi des 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 ownership2008 Maricopa Co. PM 10 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 the2008 Maricopa Co. PM 10 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 b2008 Maricopa Co. PM 10 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 “problem atic” 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 se rvices), 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 changes2008 Maricopa Co. PM 10 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. PM 10 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 si tes to deliver results and support land use

queries.2008 Maricopa Co. PM 10 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 more2008 Maricopa Co. PM 10 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 Mining2008 Maricopa Co. PM 10 Emission Inventory A4–43 June 2011 

### 575 Solar Generating Stations Solar generation stations not

associated with other power facilities

610 Transportation Freeways/Expressw ays/ 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 Community2008 Maricopa Co. PM 10 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 Unknown2008 Maricopa Co. PM 10 Emission Inventory A5

– 1 June 2011 

## Appendix 5. MO VES2010a Local Input Data and RunSpecs

In order to calculate the 2008 annual and average day onroad source emissions, MOVES2010a

w as executed using local input data for each month of the year and each geographical area

(Maricopa County and the PM 10 

### 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. PM 10 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

Die sel 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 F uel

- 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 Ox ides 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 Exha ust 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

E xtended 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

- Org anic 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

- El emental 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 Exh aust 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)

S tart 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. PM 10 Emission Inventory A5

– 3 June 2011 

### M OVES2010a RunSpec (M aricopa 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" fue ltypedesc="Diesel Fuel" sourcetypeid="32" sourcetypename="Light

Commercial Truck"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetypeid="54" sourcetypename="Motor Home"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="D iesel Fuel" sourcetypeid="11"

sourcetypename="Motorcycle"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetypeid="21" sourcetypename="Passenger

Car"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetyp eid="31" sourcetypename="Passenger

Truck"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetypeid="51" sourcetypename="Refuse

Truck"/>

<onroadvehicleselection fueltypeid="2" fueltypedesc="Diesel Fuel" sourcetypeid="43" sourcety pename="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="Combina tion

Long

- haul Truck"/>

<onroadvehicleselection fueltypeid="1" fueltypedesc="Gasoline" sourcetypeid="61" sourcetypename="Combination

Short

- haul Truck"/>

<onroadvehicleselection fueltypeid="1" fueltypedesc="Gasoline" sourcetypeid="41" sourcetypename="In tercity

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 fuel typeid="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>

</offroa dvehicleselections>

<offroadvehiclesccs>

</offroadvehiclesccs>

<roadtypes>

<roadtype roadtypeid="1" roadtypename="Off

- Network"/>

<roadtype roadtypeid="2" roadtypename="Rural Restricted Access"/>

<roadtype roadtypeid="3" roadtypename="Rural Unrestr icted Access"/>

<roadtype roadtypeid="4" roadtypename="Urban Restricted Access"/>

<roadtype roadtypeid="5" roadtypename="Urban Unrestricted Access"/>

</roadtypes>

<pollutantprocessassociations>

<pollutantprocessassociation pollutantkey="30" polluta ntname="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. PM 10 Emission Inventory A5

– 4 June 2011 processname="Extended Idle Exhaust"/>

<pollutan tprocessassociation 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"

p rocessname="Crankcase Start Exhaust"/>

<pollutantprocessassociation pollutantkey="3" pollutantname="Oxides of Nitrogen (NOx)" processkey="17"

processname="Crankcase Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="3" pollutantname="O xides of Nitrogen (NOx)" processkey="90"

processname="Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="100" pollutantname="Primary Exhaust PM10

- Total" processkey="1"

processname="Running Exhaust"/>

<pollutantprocessassociation pol lutantkey="100" pollutantname="Primary Exhaust PM10

- Total" processkey="2"

processname="Start Exhaust"/>

<pollutantprocessassociation pollutantkey="100" pollutantname="Primary Exhaust PM10

- Total" processkey="15"

processname="Crankcase Running Exhaus t"/>

<pollutantprocessassociation pollutantkey="100" pollutantname="Primary Exhaust PM10

- Total" processkey="16"

processname="Crankcase Start Exhaust"/>

<pollutantprocessassociation pollutantkey="100" pollutantname="Primary Exhaust PM10

- Total" pro cesskey="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"/>

<pollutantproce ssassociation 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"

process name="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"/>

<pollutantprocessassoci ation pollutantkey="102" pollutantname="Primary PM10

- Elemental Carbon" processkey="1"

processname="Running Exhaust"/>

<pollutantprocessassociation pollutantkey="102" pollutantname="Primary PM10

- Elemental Carbon" processkey="2"

processname="Start Exha ust"/>

<pollutantprocessassociation pollutantkey="102" pollutantname="Primary PM10

- Elemental Carbon" processkey="15"

processname="Crankcase Running Exhaust"/>

<pollutantprocessassociation pollutantkey="102" pollutantname="Primary PM10

- Elemental Car bon" 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 Exh aust"/>

<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" polluta ntname="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" pollutantnam e="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 Particul ate"

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="Cr ankcase Start Exhaust"/>

<pollutantprocessassociation pollutantkey="112" pollutantname="Primary PM2.5

- Elemental Carbon" processkey="17"

processname="Crankcase Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="112" pollutantname="Pri mary PM2.5

- Elemental Carbon" processkey="90"

processname="Extended Idle Exhaust"/>

<pollutantprocessassociation pollutantkey="111" pollutantname="Primary PM2.5

- Organic Carbon" processkey="1"

processname="Running Exhaust"/>

<pollutantprocessassociat ion pollutantkey="111" pollutantname="Primary PM2.5

- Organic Carbon" processkey="2"

processname="Start Exhaust"/>2008 Maricopa Co. PM 10 Emission Inventory A5

– 5 June 2011 <pollutantprocessassociation pollutantkey="111" pollutantname="Primary PM2.5

- Organic Carbon" processkey="15"

processname="Crankcase Runni ng 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 po llutantkey="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 Exha ust"/>

<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"/>

<pollutantprocessas sociation 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" pr ocessname="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 (S O2)" 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"/>

<pollutantprocessassoc iation 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"><![C DATA

[

useParameters No

]]></internalcontrolstrategy>

</internalcontrolstrategies>

<inputdatabase servername="" databasename="" de scription=""/>

<uncertaintyparameters uncertaintymodeenabled="false" numberofrunspersimulation="0" numberofsimulations="0"/>

<geographicoutputdetail description="COUNTY"/>

<outputemissionsbreakdownselection>

<modelyear selected="false"/>

<fueltype s elected="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>

<outputdat abase 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"/>

<distance factors selected="true" units="Miles"/>

<massfactors selected="true" units="Grams" energyunits="Joules"/>

</outputfactors>

<savedata>

</savedata>

<donotexecute>

</donotexecute>

<generatordatabase shouldsave="false" servername="" databasename="" d escription=""/>

<donotperformfinalaggregation selected="false"/>

<lookuptableflags scenarioid="" truncateoutput="true" truncateactivity="true"/>

</runspec>2008 Maricopa Co. PM 10 Emission Inventory A5

– 6 June 2011 

### M OVES2010a Local Input Data (Maricopa County , July 2008 )

[ FuelFormulation ]

F uel

Formulation F uel

Subtype RVP S ulfur

Level ETOH

Volume MTBE

Volume ETBE

Volume TAME

Volume A romatic

Content O lefin

Content B enzene

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

[ S ourceTypeYear ]

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 11,5042008 Maricopa Co. PM 10 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 0.0312002008 Maricopa Co. PM 10 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 0.0070992008 Maricopa Co. PM 10 Emission Inventory A5

– 9 June 2011 [ IMCoverage ]

polProcess

ID S tate

ID C ounty

ID yearID sourceTypeID fuelTypeID IMProgramID B eg

ModelYearID E nd

ModelYearID inspectFreq T est

StandardsID useIMyn C ompliance

Factor

1 01 4 4013 2008 21 1 103 1967 1980 1 13 Y 57.62

1 01 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

1 01 4 4013 2008 31 1 103 1967 1980 1 13 Y 57.62

1 01 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

1 01 4 4013 2008 32 1 103 1967 1980 1 13 Y 57.62

1 01 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

1 01 4 4013 2008 52 1 103 1967 2004 1 13 Y 87.20

1 02 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

1 02 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

1 02 4 4013 2008 31 1 106 1981 1995 2 31 Y 64.12

1 02 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

1 02 4 4013 2008 32 1 106 1981 1995 2 31 Y 64.12

1 02 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

1 12 4 4013 2008 21 1 108 1996 2004 2 43 Y 83.81

1 12 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

1 12 4 4013 2008 31 1 109 1981 1995 2 44 Y 64.12

1 12 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

1 12 4 4013 2008 52 1 107 1981 2004 1 41 Y 86.29

1 13 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

1 13 4 4013 2008 31 1 108 1996 2004 2 43 Y 83.81

1 13 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

1 13 4 4013 2008 32 1 109 1981 1995 2 44 Y 64.12

1 13 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

2 01 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

2 01 4 4013 2008 31 1 106 1981 1995 2 31 Y 64.12

2 01 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

2 01 4 4013 2008 32 1 106 1981 1995 2 31 Y 64.12

2 01 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

2 02 4 4013 2008 21 1 103 1967 1980 1 13 Y 57.62

2 02 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

2 02 4 4013 2008 31 1 103 1967 1980 1 13 Y 57.62

2 02 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

2 02 4 4013 2008 32 1 103 1967 1980 1 13 Y 57.62

2 02 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

2 02 4 4013 2008 52 1 103 1967 2004 1 13 Y 87.20

3 01 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

3 01 4 4013 2008 21 1 110 1996 2004 2 51 Y 90.04

3 01 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

3 01 4 4013 2008 31 1 110 1996 2004 2 51 Y 90.04

3 01 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

3 01 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

3 02 4 4013 2008 21 1 106 1981 1995 2 31 Y 64.12

3 02 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

3 02 4 4013 2008 31 1 106 1981 1995 2 31 Y 64.12

3 02 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

3 02 4 4013 2008 32 1 106 1981 1995 2 31 Y 64.12

3 02 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 87.202008 Maricopa Co. PM 10 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 0.367592008 Maricopa Co. PM 10 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 ]

S ource

TypeID M onth

ID R oad

TypeID dayID D ay

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 S ource

TypeID M onth

ID R oad

TypeID dayID D ay

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 S ource

TypeID M onth

ID R oad

TypeID dayID D ay

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 0.220932008 Maricopa Co. PM 10 Emission Inventory A5

– 12 June 2011 [ HourVMTFraction ] (SourceTypeID 21: Passenger Car)

S ource

TypeID R oad

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 S ource

TypeID R oad

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 S ource

TypeID R oad

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 0.025362008 Maricopa Co. PM 10 Emission Inventory A5

– 13 June 2011 

### [AvgSpeedDistribution] (SourceTypeID 21: Passenger Car and RoadTypeID 2: Rural Restricted Access)

S ource

TypeID R oad

TypeID H our

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 S ource

TypeID R oad

TypeID H our

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 S ource

TypeID R oad

TypeID H our

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

21 2 155 2 0.00000

21 2 155 3 0.00000

21 2 155 4 0.00000

21 2 155 5 0.00000

21 2 155 6 0.00010

21 2 155 7 0.00307

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 0.126182008 Maricopa Co. PM 10 Emission Inventory A5

– 14 June 2011 S ource

TypeID R oad

TypeID H our

DayID avgSpeed

BinID avgSpeed

Fraction

21 2 165 1 0.00000

21 2 165 2 0.00000

21 2 165 3 0.00000

21 2 165 4 0.00000

21 2 165 5 0.00000

21 2 165 6 0.00708

21 2 165 7 0.04834

21 2 165 8 0.06439

21 2 165 9 0.17359

21 2 165 10 0.34525

21 2 165 11 0.05809

21 2 165 12 0.04723

21 2 165 13 0.05493

21 2 165 14 0.07183

21 2 165 15 0.04109

21 2 165 16 0.08819

21 2 175 1 0.00000

21 2 175 2 0.00000

21 2 175 3 0.00000

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

21 2 185 2 0.00000

21 2 185 3 0.00000

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

21 2 195 2 0.00000

21 2 195 3 0.00000

21 2 195 4 0.00000

21 2 195 5 0.00000

21 2 195 6 0.00000

21 2 195 7 0.00360

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

21 2 205 2 0.00000

21 2 205 3 0.00000

21 2 205 4 0.00000

21 2 205 5 0.00000

21 2 205 6 0.00000

21 2 205 7 0.00360

21 2 205 8 0.00000

21 2 205 9 0.00000

21 2 205 10 0.06574

21 2 205 11 0.00073

21 2 205 12 0.01326

21 2 205 13 0.12481

21 2 205 14 0.35321

21 2 205 15 0.19430

21 2 205 16 0.24435

21 2 215 1 0.00000

21 2 215 2 0.00000 S ource

TypeID R oad

TypeID H our

DayID avgSpeed

BinID avgSpeed

Fraction

21 2 215 3 0.00000

21 2 215 4 0.00000

21 2 215 5 0.00000

21 2 215 6 0.00000

21 2 215 7 0.00360

21 2 215 8 0.00000

21 2 215 9 0.00000

21 2 215 10 0.06574

21 2 215 11 0.00073

21 2 215 12 0.01326

21 2 215 13 0.12481

21 2 215 14 0.35321

21 2 215 15 0.19430

21 2 215 16 0.24435

21 2 225 1 0.00000

21 2 225 2 0.00000

21 2 225 3 0.00000

21 2 225 4 0.00000

21 2 225 5 0.00000

21 2 225 6 0.00000

21 2 225 7 0.00360

21 2 225 8 0.00000

21 2 225 9 0.00000

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

21 2 225 16 0.24435

21 2 235 1 0.00000

21 2 235 2 0.00000

21 2 235 3 0.00000

21 2 235 4 0.00000

21 2 235 5 0.00000

21 2 235 6 0.00000

21 2 235 7 0.00360

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

21 2 245 2 0.00000

21 2 245 3 0.00000

21 2 245 4 0.00000

21 2 245 5 0.00000

21 2 245 6 0.00000

21 2 245 7 0.00360

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

21 2 12 2 0.00000

21 2 12 3 0.00000

21 2 12 4 0.00000

21 2 12 5 0.00000

21 2 12 6 0.00000

21 2 12 7 0.00360

21 2 12 8 0.00000

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

21 2 22 2 0.00000

21 2 22 3 0.00000

21 2 22 4 0.00000 S ource

TypeID R oad

TypeID H our

DayID avgSpeed

BinID avgSpeed

Fraction

21 2 22 5 0.00000

21 2 22 6 0.00000

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

21 2 32 2 0.00000

21 2 32 3 0.00000

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

21 2 42 2 0.00000

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

21 2 62 2 0.00000

21 2 62 3 0.00000

21 2 62 4 0.00000

21 2 62 5 0.00000

21 2 62 6 0.00000

21 2 62 7 0.00360

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 0.007902008 Maricopa Co. PM 10 Emission Inventory A5

– 15 June 2011 S ource

TypeID R oad

TypeID H our

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

21 2 112 2 0.00000

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

21 2 122 2 0.00000

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 S ource

TypeID R oad

TypeID H our

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

21 2 132 2 0.00000

21 2 132 3 0.00000

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

21 2 142 2 0.00000

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

21 2 162 2 0.00000

21 2 162 3 0.00000

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 S ource

TypeID R oad

TypeID H our

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

21 2 182 2 0.00000

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 0.013262008 Maricopa Co. PM 10 Emission Inventory A5

– 16 June 2011 S ource

TypeID R oad

TypeID H our

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

21 2 232 2 0.00000

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 S ource

TypeID R oad

TypeID H our

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 S ource

TypeID R oad

TypeID H our

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