Report No. SR2014-08-03

Appendix C:

Pinal County PM10

Nonattainment Area Source 

Apportionment Modeling for 

2008 and 2018 Base

Scenario Design Days

Prepared for:

Arizona Dept. of Environmental 

Quality

August 2014

Prepared by:

Sierra Research, Inc.

1801 J Street

Sacramento, California 95811

(916) 444-6666

Revised by:

Arizona Department of Environmental Quality

December, 2015
Report No. SR2014-08-03

Pinal County PM10 Nonattainment Area Source Apportionment 

Modeling for 2008 and 2018 Base Scenario Design Days

prepared for:

Arizona Dept. of Environmental Quality

August 2014

Principal authors:

Robert G. Dulla

Wei Liu

Sierra Research, Inc.

1801 J Street

Sacramento, CA 95811

(916) 444-6666

Earl Withycombe

Consultant

Revised December, 2015

Arizona Department of Environmental Quality
i

Pinal County PM10 Nonattainment Area

Source Apportionment Modeling for 

2008 and 2018 Base Scenario Design Days

Table of Contents

Page

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

2. Stagnation Day Modeling................................................................................................4

2.1 AERMOD Inputs.....................................................................................................4

2.2 Post-Processing Methodology ...............................................................................10

2.3 Results....................................................................................................................11

3. High Wind Day Modeling.............................................................................................27

3.1 Methodology..........................................................................................................27

3.2 Non-Anthropogenic Background...........................................................................28

3.3 Results....................................................................................................................29

Exhibit CI High Wind Design Day Example Calculation....................................... CI-1
ii

List of Figures

Figure Page

Figure 2-1. Design Day Modeling Domains in the Nonattainment Area ............................8

Figure 2-2. Modeled vs Monitored Stagnation Day PM10 Concentrations (μg/m3) at 

Cowtown (CWT) 10/30/2008 Design Day ..................................................................14

Figure 2-3. Modeled vs Monitored Stagnation Day PM10 Concentrations (μg/m3) at 

Pinal County Housing (PCH) 10/29/2008 Design Day ...............................................16

Figure 2-4. Modeled vs Monitored Stagnation Day PM10 Concentrations (μg/m3) at 

Stanfield (STF) 10/29/2008 Design Day .....................................................................18

Figure 2-5. 2008 Stagnation Design Days Source Contributions......................................19

Figure 2-6. 2018 Modeled vs. 2008 Monitored Stagnation Day Concentrations 

(μg/m3) at Cowtown (CWT) 10/30/2008 Design Day.................................................21

Figure 2-7. 2018 Modeled vs. 2008 Monitored Stagnation Day Concentrations 

(μg/m3) at Pinal County Housing (PCH) 10/29/2008 Design Day..............................23

Figure 2-8. 2018 Modeled vs. 2008 Monitored Stagnation Day Concentrations 

(μg/m3) at Stanfield (STF) 10/29/2008 Design Day....................................................25

Figure 2-9. Projected 2018 Stagnation Design Day Source Contributions .......................26

Figure 3-1. Distance-Weighted Emissions for Pinal County Housing (PCH) 

1/1/2008 High Wind Design Day ................................................................................32

Figure 3-2. Distance-Weighted Emissions for Cowtown (CWT) 4/27/2008 High 

Wind Design Day.........................................................................................................34

Figure 3-3. Distance-Weighted Emissions for Maricopa 10/27/2008 High Wind 

Design Day...................................................................................................................36

Figure 3-4. Distance-Weighted Emissions for Stanfield (STF) 11/21/2008 High 

Wind Design Day.........................................................................................................38

Figure 3-5. 2008 High Wind Design Day Source Contributions.......................................39

Figure 3-6. Forecast of 2018 Distance-Weighted Emissions for Pinal County 

Housing (PCH) 1/1/2008 High Wind Design Day ......................................................41

Figure 3-7. Forecast of 2018 Distance-Weighted Emissions for Cowtown (CWT) 

4/27/2008 High Wind Design Day ..............................................................................43

Figure 3-8. Forecast of 2018 Distance-Weighted Emissions for Maricopa 

10/27/2008 High Wind Design Day ............................................................................45

Figure 3-9. Forecast of 2018 Distance-Weighted Emissions for Stanfield (STF) 

11/21/2008 High Wind Design Day ............................................................................47

Figure 3-10. Projected 2018 High Wind Design Day Source Contributions.....................48
iii

List of Tables

Table Page

Table 2-1. AERMET Stage 3 Meteorological Processing Parameters for the 

Cowtown Monitoring Site in October............................................................................6

Table 2-2. AERMET Stage 3 Meteorological Processing Parameters for the Pinal 

County Housing Monitoring Site in October.................................................................6

Table 2-3. AERMET Stage 3 Meteorological Processing Parameters for the 

Stanfield Monitoring Site in October.............................................................................6

Table 2-4. Particle Parameters for Modeling Concentrated Animal Feeding 

Operations......................................................................................................................7

Table 2-5. Particle Size Distributions Collected from Dust Jars for 2007 MAG Five 

Percent Plan ...................................................................................................................7

Table 2-6. Particle Size Distributions Collected by Aerodynamic Particle Sizer 

Spectrometer at Casa Grande Airport in July 2008 .......................................................7

Table 2-7. Particle Parameters Used for Modeling Non-CAFO Source Categories............7

Table 2-8. Stagnation Day Modeling Performance at Cowtown (CWT) on 

10/30/2008 Design Day, AERMOD Simulation of Monitored Concentrations 

(μg/m3).........................................................................................................................13

Table 2-9. Stagnation Day Modeling Performance at Pinal County Housing (PCH) 

on 10/29/2008 Design Day, AERMOD Simulation of Monitored Concentrations 

(μg/m3).........................................................................................................................15

Table 2-10. Stagnation Day Modeling Performance at Stanfield (STF) on 

10/29/2008 Design Day, AERMOD Simulation of Monitored Concentrations 

(μg/m3).........................................................................................................................17

Table 2-11. Projected 2018 Stagnation Day Modeling Performance at Cowtown 

(CWT) on 10/30/2008, AERMOD Simulation of Monitored Concentrations 

(μg/m3).........................................................................................................................20

Table 2-12. Projected 2018 Stagnation Day Modeling Performance at Pinal County 

Housing (PCH) on 10/29/2008, AERMOD Simulation of Monitored 

Concentrations (μg/m3)................................................................................................22

Table 2-13. Projected 2018 Stagnation Day Modeling Performance at Stanfield 

(STF) on 10/29/2008, AERMOD Simulation of Monitored Concentrations 

(μg/m3).........................................................................................................................24

Table 3-1. Distance-Weighted Emissions (lbs/mile) for the High Wind Modeling 

Domain at Pinal County Housing (PCH) on 1/1/2008 Design Day.............................31

Table 3-2. Distance-Weighted Emissions (lbs/mile) for the High Wind Modeling 

Domain at Cowtown (CWT) on 4/27/2008 Design Day .............................................33

Table 3-3. Distance-Weighted Emissions (lbs/mile) for the High Wind Modeling 

Domain at Maricopa on 10/27/2008 Design Day ........................................................35
iv

Table 3-4. Distance-Weighted Emissions (lbs/mile) for the High Wind Modeling 

Domain at Stanfield (STF) on 11/21/2008 Design Day...............................................37

Table 3-5. Projected 2018 Distance-Weighted Emissions (lbs/mile) for the High 

Wind Modeling Domain at PCH on 1/1/2008 Design Day .........................................40

Table 3-6. Projected 2018 Distance-Weighted Emissions (lbs/mile) for the High 

Wind Modeling Domain at CWT on 4/27/2008 Design Day ......................................42

Table 3-7. Projected 2018 Distance-Weighted Emissions (lbs/mile) for the High 

Wind Modeling Domain at Maricopa on 10/27/2008 Design Day..............................44

Table 3-8. Projected 2018 Distance-Weighted Emissions (lbs/mile) for the High 

Wind Modeling Domain at STF on 11/21/2008 Design Day ......................................46

Table CI-1. Values used for Example Windblown Dust Calculation............................ CI-2
1

1. INTRODUCTION

The goal of this effort was to structure a U.S. Environmental Protection Agency (EPA) 

approved plume dispersion model to compute PM10 air quality impacts from arrays of 

significant emissions sources near existing permanent monitoring stations for use in 

improving base-year emission inventories and assessing the benefits of alternative control 

strategies in the Western Pinal County PM10 Nonattainment Area (Pinal County). From 

previous review of U.S. EPA guidance and discussions with EPA Region 9 staff, the 

Arizona Department of Environmental Quality (ADEQ) team preparing the Pinal County 

attainment plan (State Implementation Plan or SIP) chose 2008 as the base-year for 

planning purposes.1 

The dual goals of this modeling effort were critical to the integrity of the completed plan. 

Separate emission inventories had been prepared for the areas surrounding and impacting 

four Pinal County Air Quality Control District (PCAQCD) monitoring stations in 

nonattainment status, and the predominance of area source emissions in these inventories 

required the use of dispersion modeling for stagnation meteorological conditions and 

distance-weighted approach for high wind conditions, to overcome the significant 

uncertainties in inventory accuracy that are inherent to these highly variable source 

categories. Also, because of the spatial distribution patterns of area sources surrounding 

the monitors, dispersion modeling was critical to the assessment of benefits of emission 

control measures that will differentially reduce emissions impacts at different monitors. 

The need for a comprehensive modeling effort in support of attainment planning was

further underscored by a prior determination that PM10 exceedances were caused at three 

of the four monitoring sites by two different sets of meteorological conditions. In late fall 

and winter months, the presence of regional high pressure cells combined with the absence 

of storm fronts passing through central Arizona produces stagnation (or low wind) 

conditions that reduce nocturnal mixing heights to tens of meters above the ground and 

concentrate emitted pollutants at ground-level. In the spring and summer, high wind 

conditions are periodically generated by monsoonal thunderstorms or strong eddy currents 

associated with the retreating circumpolar vortex. Because these two types of events are 

not typically accompanied by precipitation over Pinal County, both cause significant 

increases in windblown emissions sufficient to produce exceedances of PM10 standards.

Air quality modeling combines information on meteorological conditions (e.g., wind 

speed, wind direction, mixing height, etc.) with emission estimates to calculate downwind 

pollutant concentrations at selected locations. For this planning process, AERMOD and 

 

1 See Appendix A of this SIP submittal, “Pinal County PM Inventory Preparation Plan,” prepared for the 

Arizona Department of Environmental Quality, Sierra Research, December 2012.
2

an EPA-approved modified weighted rollback approach for high wind conditions were

selected to estimate hourly PM10 concentrations at monitoring stations produced by 

emissions of area, point, and mobile sources located within specified modeling domains 

surrounding the monitoring stations. Because the PM10 ambient air quality standard 

exceeded in Pinal County is designed to limit short-term acute exposures and is measured 

over 24-hour averaging periods, the attainment demonstrations are required by EPA policy 

to show how PM10 concentrations would be reduced from levels recorded on exceedance 

days in the base year experiencing the strongest stagnation or high wind meteorological 

conditions. The selection of these “design days” is discussed in Appendix B of this SIP 

submittal2.

Different approaches were used to estimate emission impacts at monitors on low wind and 

high wind design days. On low wind days, AERMOD was run with meteorological data 

recorded at the subject monitor and emissions rates for each source within the modeling 

domain were calculated from reported activity data and best-representative emissions 

factors. For both high wind hours (>12 mph) and low wind hours (≤12 mph) on high wind 

days, a weighted rollback method was used to assess the relative contribution of each 

upwind source area to the hourly monitored PM10 contribution under assumptions of (1) 

emission factor uniformity within “disturbed” and “undisturbed” states of surface soil 

conditions and (2) an inverse relationship between the source’s distance from the monitor 

and the emission impact at that monitor.

The weighted rollback method for high wind day analysis is based on modeling experiences 

related to development of the Maricopa Association of Government’s (MAG) Five Percent 

Plan. Through experience gained in the preparation of PM10 SIPs, and in consultation with 

EPA, MAG determined that neither AERMOD nor photochemical grid models performed 

well in quantifying discrete area source contributions at downwind monitors under high 

wind conditions, and that attainment demonstrations relying on use of these models were 

not reliable. For this reason, MAG developed an alternate but more reliable approach that

weights the contribution of each upwind source’s emissions by the reciprocal of its distance 

to the monitor and assumes that each source’s fractional contribution to the sum of 

weighted emissions is equal to that source’s fractional contribution to the hourly PM10

concentration measured at the downwind monitor (i.e., that the impacts of emissions from 

nearby sources are proportionally greater than the impacts from remote sources, assuming 

equivalent emissions rates among sources). Individual source contributions, using this 

approach, can be determined through review of hourly and daily estimates of weighted 

emissions rates.

Under each of these methodologies, the degree of emissions reductions needed to achieve 

attainment of the 24-hour PM10 standard at designated monitors on respective stagnation 

and high wind design days—both in overall terms or by individual area source—can be 

quantified. Evaluation and selection of suites of control measures capable of demonstrating 

attainment at all monitors on all design days involve many different factors and are the 

subject of Appendix D of this SIP submittal3.

 

2

“Pinal County PM10 Nonattainment Area Emissions Inventories for 2008 and 2018 Base Years and 

Design Days,” Sierra Research, prepared August 2014 and revised October 2015.

3

“Pinal County PM10 Nonattainment Area 2018 Attainment Demonstration and Controlled Emission 

Inventories,” ADEQ, prepared August 2015 and revised October 2015.
3

The remainder of this report discusses the data sources, analyses, and the modeling 

methodologies used in the Pinal County PM10 plan for control strategy evaluation and 

attainment demonstration. Section 2 summarizes the development of an assessment 

methodology addressing stagnation design days, and Section 3 reviews the methodology 

developed to evaluate solutions for high wind design days. At the conclusion of each 

section, the methodologies are used to calculate design day impacts at each monitor, on the 

basis of PM10 emission inventories,

4

for comparison to hourly PM10 concentrations 

recorded at the stations on these design days in the 2008 base year and the projected year

2018; a brief summary of significant changes in emissions and related source 

apportionment shifts is also provided.

 

4

“Pinal County PM10 Nonattainment Area Emissions Inventories for 2008 and 2018 Base Years and 

Design Days,” Sierra Research, prepared August 2014 and revised October 2015.
4

2. STAGNATION DAY MODELING

A review of EPA guidelines and related fugitive dust modeling employed in attainment 

demonstrations prepared for Maricopa County determined that AERMOD is the most 

suitable model for evaluating hourly source contributions to PM10 exceedances recorded at 

Pinal County monitors on stagnation design days. AERMOD is a steady-state Gaussian 

plume dispersion model that assesses pollutant concentrations from a variety of source

types. Adopted by EPA as a regulatory model on December 9, 2005, AERMOD contains 

improved algorithms for addressing low wind speed (near-calm conditions) and provides

estimates for conditions when wind speeds are less than 1 m/sec,

5,6 which was often the 

case on the selected stagnation design days. ADEQ’s analysis employed the AERMOD 

version dated 14134 (May 14, 2014), and the AERMET (see below) version bearing the 

same date.

2.1 AERMOD Inputs

Key inputs required for the successful use of AERMOD are summarized below.

 Emission Inventory7– Hourly estimates of emissions were prepared using land 

parcel data provided by ADEQ and PCAQCD, activity data collected through field 

surveys, contacts with stakeholders, etc., and cited fugitive dust emission factors. 

 AERMET-formatted Meteorological Data – AERMET is a preprocessor that 

converts raw meteorological measurements into formatted meteorological input 

files for AERMOD. Outlined below are the data sources used to configure 

AERMET to produce these input files.

- The on-site meteorological data collected at the Cowtown, Pinal County 

Housing, and Stanfield monitoring stations were used, with parameters of wind 

direction, wind speed, and temperature. A wind speed threshold of 0.5 

meters/second was specified for the upper limit of calm conditions.

- Upper air meteorological data were derived from Tucson 2008 twice-daily 

soundings by the National Weather Service (NWS).

- Cloud cover meteorological data were obtained from the records of the Phoenix 

NWS meteorological station at Sky Harbor Airport.

8

 

5

“Revisions to the Guideline on Air Quality Models: Adoption of Preferred General Purpose (Flat and 

Complex Terrain) Dispersion Model and Other Revisions,” U.S. Environmental Protection Agency, Federal 

Register, Vol. 70, No. 216, p. 68218, November 9, 2005 (Attachment IV).

6 U.S. EPA, User’s Guide for AERMET, EPA-454/B-03-002, November 2004.

7

“Pinal County PM10 Nonattainment Area Emissions Inventories for 2008 and 2018 Base Years and 

Design Days,” ibid.

8 Cloud cover data were obtained for both Casa Grande airport and Phoenix Sky Harbor airport for 2008.
5

 The surface characteristics of albedo, Bowen Ratio and surface roughness 

appropriate to the areas surrounding the Cowtown, Pinal County Housing, and 

Stanfield monitoring stations were obtained from AERSURFACE.

9 Albedo is the 

portion of sunlight that is reflected from the surface of the ground, Bowen ratio is 

a measure of moisture available for evaporation, and surface roughness is a measure 

of the depth of the thin boundary layer at the ground surface that is protected from 

influences of wind-generated frictional drag by the small variability in ground 

surface elevation.10,11 These parameters are functions of ground cover (land use) 

and affect the concentration calculations. The monthly average values of these 

parameters were calculated by AERSURFACE for each of the Cowtown, Pinal 

County Housing, and Stanfield monitoring sites and are listed below in Tables 2-1, 

2-2, and 2-3, respectively. Only data from October were used to represent the 

stagnation design day conditions.

- The wind measurement height12 for each monitor was input as the onsite 

instrument height parameter to AERMET. AERMOD adjusts the wind speed 

at these measurement heights to other heights based on the AERMOD profile 

equation for wind speed.13

 

 After processing the data through AERMET, the missing data percentage was lower for the Phoenix 

Sky Harbor airport data: 10.76% compared to 13.97% for the Casa Grande data.

 According to http://www.faa.gov/air_traffic/weather/asos/?state=AZ , Casa Grande airport is an 

Automated Weather Observing System (AWOS III) station, and Phoenix Sky Harbor airport is an 

Automated Surface Observing System (ASOS) station. The AWOS systems are among the oldest 

automated weather stations in the United States, and many of them predate ASOS

http://en.wikipedia.org/wiki/Automated_airport_weather_station. The Phoenix Sky Harbor airport 

most likely has a better observation system.

 AERMOD was used to assess the impact of the Sky Harbor and Casa Grande data. The results show 

there is less than 5% difference in terms of modeling impacts between the two AERMET data sets.

Considering all of the factors above, Phoenix sky harbor airport data were chosen because of the better data 

quality and better observation system.

9 U.S. EPA, AERSURFACE User’s Guide, 

http://www.epa.gov/scram001/7thconf/aermod/aersurface_userguide.pdf.

10 Appendix W to Part 51—Guideline on air Quality Models, §8.3.c.

11 U.S. EPA. AERMOD Implementation Guide, March 19, 2009.

12 Reported by PCAQCD to be 3.3 meters, 3.5 meters, and 9.2 meters at the PCH, Cowtown, and Stanfield 

monitoring stations, respectively. 

13 AERMOD Description of Model Formulation, Page 24, 4.1.1 Wind Speed Profiling.

http://www.epa.gov/ttn/scram/7thconf/aermod/aermod_mfd.pdf.
6

Table 2-1. AERMET Stage 3 Meteorological Processing Parameters for the 

Cowtown Monitoring Site in October

Sector Sector Definition Albedo Bowen Ratio Roughness Length (m)

1 0° - 30° (NNE) 0.19 1.37 0.7

2 30° - 60° (NE) 0.19 1.37 0.659

3 60° - 90° (ENE) 0.19 1.37 0.7

4 90° - 120° (ESE) 0.19 1.37 0.406

5 120° - 150° (SE) 0.19 1.37 0.309

6 150° - 180° (SSE) 0.19 1.37 0.295

7 180° - 210° (SSW) 0.19 1.37 0.301

8 210° - 240° (SW) 0.19 1.37 0.272

9 240° - 270° (WSW) 0.19 1.37 0.276

10 270° - 300° (WNW) 0.19 1.37 0.683

11 300° - 330° (NW) 0.19 1.37 0.47

12 330° - 360° (NNW) 0.19 1.37 0.583

Table 2-2. AERMET Stage 3 Meteorological Processing Parameters for the Pinal 

County Housing Monitoring Site in October

Sector Sector Definition Albedo Bowen Ratio Roughness Length (m)

1 0° - 30° (NNE) 0.19 1.37 0.07

2 30° - 60° (NE) 0.19 1.37 0.069

3 60° - 90° (ENE) 0.19 1.37 0.07

4 90° - 120° (ESE) 0.19 1.37 0.063

5 120° - 150° (SE) 0.19 1.37 0.083

6 150° - 180° (SSE) 0.19 1.37 0.092

7 180° - 210° (SSW) 0.19 1.37 0.08

8 210° - 240° (SW) 0.19 1.37 0.074

9 240° - 270° (WSW) 0.19 1.37 0.053

10 270° - 300° (WNW) 0.19 1.37 0.07

11 300° - 330° (NW) 0.19 1.37 0.061

12 330° - 360° (NNW) 0.19 1.37 0.066

Table 2-3. AERMET Stage 3 Meteorological Processing Parameters for the 

Stanfield Monitoring Site in October

Sector Sector Definition Albedo Bowen Ratio Roughness Length (m)

1 0° - 30° (NNE) 0.19 1.37 0.07

2 30° - 60° (NE) 0.19 1.37 0.069

3 60° - 90° (ENE) 0.19 1.37 0.07

4 90° - 120° (ESE) 0.19 1.37 0.063

5 120° - 150° (SE) 0.19 1.37 0.083

6 150° - 180° (SSE) 0.19 1.37 0.092

7 180° - 210° (SSW) 0.19 1.37 0.08

8 210° - 240° (SW) 0.19 1.37 0.074

9 240° - 270° (WSW) 0.19 1.37 0.053

10 270° - 300° (WNW) 0.19 1.37 0.07

11 300° - 330° (NW) 0.19 1.37 0.061

12 330° - 360° (NNW) 0.19 1.37 0.066
7

 AERMOD Particle Deposition Algorithm was activated to simulate the impacts of 

particle deposition on calculated PM10 concentrations. Table 2-4 summarizes the 

particle parameters for modeling the Concentrated Animal Feeding Operations

(CAFOs).

14

 For all other source categories, two sources of particle size data were 

available: (1) the particle size data collected by dust jar at Durango Complex and 

West 43rd Avenue monitors in 2008 detailed in the MAG Five Percent Plan, as 

listed in Table 2-5; and (2) the particle size data collected by the Aerodynamic 

Particle Sizer (APS) Spectrometer at Casa Grande Airport in July 2008, as listed in 

Table 2-6.

Table 2-4. Particle Parameters for Modeling Concentrated Animal Feeding Operations

Particle size (μm) 0 - 1.8 1.8 - 3.1 3.1 - 6.2 6.2 - 9.9

Mass Fraction 0.14 0.07 0.27 0.52

Particle Density (mg/m3) 2.5 2.5 2.5 2.5

Table 2-5. Particle Size Distributions Collected from Dust Jars

for 2007 MAG Five Percent Plan

Particle size (μm) 0 - 2.5 2.5 - 5.0 5.0 - 7.5 7.5 – 10.0

Mass Fraction 0.14 0.18 0.28 0.4

Table 2-6. Particle Size Distributions Collected by Aerodynamic Particle Sizer

Spectrometer at Casa Grande Airport in July 2008

Particle size (μm) 0 - 1.84 1.84 - 3.28 3.28 - 6.26 6.26 – 9.65

Mass Fraction 0.027 0.134 0.281 0.558

While the results from both of these studies are similar, the land use surrounding the

Durango Complex and West 43rd Avenue monitors more closely represents areas adjacent 

to the Cowtown, Pinal County Housing, and Stanfield monitors. Therefore, the particle 

parameters used in the MAG Five Percent Plan, as shown in Table 2-7, were used in Pinal 

modeling.

Table 2-7. Particle Parameters Used for Modeling Non-CAFO Source Categories

Particle size (μm) 0 - 2.5 2.5 - 5.0 5.0 - 7.5 7.5 – 10.0

Mass Fraction 0.14 0.18 0.28 0.40

Particle Density (mg/m3) 2.5 2.5 2.5 2.5

 

14

“Particulate matter emission rates from beef cattle feedlots in Kansas - Reverse dispersion modeling,”

H.F. Bonifacio et al, Journal of the Air & Waste Management Association (JAWMA) Vol. 63, No. 3, p. 

350-361.
8

 Flag pole receptor heights of 3 meters, 3.5 meters, and 4.8 meters for Pinal County 

Housing, Cowtown, and Stanfield sites, respectively, were used to represent the 

measurement height for each PM10 monitor. The following UTM Coordinates, (in 

NAD 83, zone 12) were assigned to receptor points representing these three PM10

monitors:

- Pinal County Housing: 446631.83 (East), 3639334.80 (North); 

- Cowtown: 409201.93 (East), 3652874.86 (North);

- Stanfield: 409999.82 (East), 3638528.80 (North).

Figure 2-1 shows the relative locations of each monitoring site, as well as the 

extent around each for which emissions sources were modeled. The map also 

shows a fourth monitor, at the Maricopa County Complex site, which was 

modeled only for a high-wind exceedance day.

 Figure 2-1. Design Day Modeling Domains in the Nonattainment Area
9

 Source parameters for select source categories are described below.

- Unpaved Roads: Road links were modeled as area sources with release heights

of 2 meters. The widths of these links were extracted from an ARCGIS shape 

file provided by PCAQCD and expanded by 10 foot mixing zones on each 

side,

15,16 and the lengths of these links were also extracted from the ARCGIS 

shape file provided by PCAQCD. 

- Agriculture: Agricultural parcels were modeled as area sources with release 

heights of 2 meters. The horizontal dimensions of these area sources were 

extracted from the ARCGIS shape file provided by ADEQ. 

- Construction: Construction sites were modeled as area sources with release 

heights of 2 meters. The horizontal dimensions of these area sources were 

extracted from the ARCGIS shape file provided by PCAQCD. The method for 

determining the activity status of construction sites is discussed in Section 3 of 

Appendix B.

- CAFOs and Dairies: Feedlots and commercial dairy operations were modeled 

as area sources with release heights of 2.3 meters, based on recommendations 

contained in a feedlot emission and modeling study conducted in Kansas by 

Bonifacio et al.17 The horizontal dimensions of these facilities were extracted 

from an ARCGIS shape file provided by ADEQ. 

- Industrial facilities: Stack and exhaust parameters for stationary equipment 

were derived from data contained in PCAQCD permit files and from PCAQCD 

surveys. Facility-specific data are presented and discussed in Section 3 of 

Appendix B.

- Paved Roads: Road links were modeled as area sources with release heights of 

2 meters. The widths of these links were extracted from an ARCGIS shape file 

and expanded by 10 foot mixing zones on each side;

18 the lengths of these links 

were also extracted from the PCAQCD ARCGIS shape file. 

- Nonroad: As discussed in Appendix B, the nonroad emissions are so small that 

they were not included in the modeling simulation.19

 

15 Ten foot wide mixing zones extending beyond the roadway outer edges have been found through 

research studies to be impacted by the bow wakes of trucks and cars in a manner that mixes vehicle exhaust 

pollutants and entrained road dust into these near-road areas, producing well mixed, uniform concentrations 

across the mixing zones and roadway surface prior to upward and downwind dispersion.

http://www.epa.gov/scram001/userg/regmod/caline3.pdf.

16 CALINE3 treats the region directly over the highway as a zone of uniform emissions and turbulence. This is 

designated as the mixing zone, and is defined as the region over the traveled way (traffic lanes, not including 

shoulders) plus three meters on either side. http://www.epa.gov/scram001/userg/regmod/caline3.pdf.

17 Bonifacio, H.F, et al., ibid.

18 See footnotes 15 and 16. http://www.epa.gov/scram001/userg/regmod/caline3.pdf. 

19 Nonroad emissions accounted for less than 0.1% of the design day inventory for each stagnation 

modeling domain.
10

2.2 Post-Processing Methodology

Once AERMOD runs were completed, modeled PM10 concentrations at the monitor were 

adjusted to account for particles that remained airborne for longer than an hour, as well as 

the contributions of sources located outside of modeling domains, as described below.

 Background – Although wind speeds during stagnant periods were extremely low, 

they were sufficient to allow for the transport of non-anthropogenic emissions from 

outside of the nonattainment area to the three low wind modeling domains. To 

account for the contribution of transported PM10, non-anthropogenic background 

PM10 concentrations recorded at Organ Pipe Cactus National Monument were 

evaluated. This monitor, located 68 miles southwest of Tucson, is impacted by 

very little anthropogenic activity. The monitor is part of the IMPROVE monitoring 

network20. Filter-based measurements are collected every 3 days and 24-hour 

average concentrations of both PM10 and PM2.5 are stored online. PM10 data were 

downloaded from the IMPROVE network for October and November 2008, 

representing twenty (20) 24-hour averages. Using meteorological data collected on 

the same dates in Tucson (the closest representative monitoring site), the 20 Organ 

Pipe measurements were screened to eliminate days with high wind conditions. 

Analysis of the meteorological data identified one day with 10 hours of winds 

exceeding the 12 mph high wind threshold velocity, and a second day had one hour 

of winds exceeding the 12 mph threshold. On the basis of this analysis, the one day 

with 10 hours of high winds was excluded from the calculation of background 

conditions. The average of 24-hour concentrations for the remaining 19 days was 

11.5 μg/m3. This average concentration was subtracted from the monitored PM10

concentrations at each of the stagnation monitors to isolate the concentration due 

to local sources.

 Carryover – A comparison between the modeled concentrations and the monitored 

concentrations (less background) found significant shortfalls in the modeled 

estimates. This was thought to be the result of extremely low wind speeds which 

promote carryover (i.e., locally-emitted particulate matter remaining in the 

atmosphere for multiple hours and continuing to contribute to monitored 

concentrations before being removed by particle deposition). AERMOD does not 

account for carryover; concentrations are estimated for each hour based on 

particulate mass emitted within the modeling domain in that hour. To address the 

effect of carryover, modeled concentrations from the previous hour were added to 

the succeeding hour. The carryover concentrations, however, were adjusted to 

account for particle deposition that would occur over the second hour of suspension. 

Information on particle size distribution, mixing height, and particle deposition 

velocity was used to estimate the amount of deposition that would occur in the 

second hour. As noted above, two estimates of particle size distribution were used 

to configure AERMOD—values from feedlot emission studies21 were used to 

represent CAFOs emissions, and values reported in the MAG Five Percent Plan 

based on sampling conducted with a dust jar in 2008 at Durango and West 43rd

 

20 http://vista.cira.colostate.edu/improve/default.htm.

21 Bonifacio, H.F, et al., ibid.
11

Avenue were used to represent emissions from all other sources. Mixing height 

estimates for each of the design days were computed using AERMET. Estimates 

of settling velocities by particle size range were calculated using an online 

deposition velocity model.22 The results of the analysis showed that PM9 (i.e., 

particles 0 – 9 μm) would remain suspended in the second hour and that only PM9-

10 would settle out during this period. Because the fraction of an area source’s PM10

emissions that settles out by the second hour is dependent on the emissions’ particle 

size distribution, separate second-hour deposition fractions were calculated for 

CAFO and non-CAFO source emissions. These analyses reported that 87% of 

CAFO PM10 emissions would remain suspended during the second hour following 

release, and 84% of PM10 emissions from all other sources would remain 

suspended.

 Normalize – A comparison between the diurnal profiles of the modeled and 

monitored PM10 concentrations, after adjusting for background and carryover

contributions, showed that the estimates still differed. To reconcile these 

differences and to match the overall estimated concentrations with the 24-hour 

average design day PM10 measured concentration, the modeled values were 

normalized to match the 24-hour monitored values. This was accomplished by 

calculating the % difference between the average 2008 24-hour modeled

concentrations (after adding carryover) and monitored concentrations (after 

subtracting out background) and using the % difference to adjust each estimated 

hourly concentration. The 2008 modeled:monitored ratio was also applied to 2018 

modeled emissions for consistency between 2008 and 2018 modeling impacts.

2.3 Results

Tabular summaries of estimated hourly concentrations are presented in Tables 2-8 through 

2-10 (2008 base year) and Tables 2-11 through 2-13 (the projected year of 2018) for 

Cowtown, Pinal County Housing, and Stanfield, respectively. These tables provide 

information on monitored wind speed, wind direction, PM10 concentration, modeled 

mixing height, and source-specific concentrations. Also included are the total hourly 

estimated concentrations, total daily source concentration, and overall source 

apportionment. Monitored and modeled concentrations and mixing height are depicted 

graphically in Figures 2-2 through 2-4 (2008 base year) and Figures 2-6 through 2-8 (the 

projected year of 2018). Figure 2-5 (2008 base year) and Figure 2-9 (the projected year of

2018) depict the average daily source-specific contributions for each site.

Changes in source apportionment between 2008 and 2018 are the result of changes in 

source-specific emissions and their proximity to each monitor. A summary of the changes 

in emissions and related source apportionment shifts is provided below. 

 Paved roads emissions are projected to increase from 2008 to 2018 for all modeling 

domains. Depending on the modeling domain, the modeling impacts from the 

paved roads increased about 25% to 65% from 2008 to 2018.

 

22 http://www.filtration-and-separation.com/settling/settling.htm, accessed August 2013.
12

 Residential and Commercial construction emissions are forecast to decrease due to 

the decline in construction activity and the decreased number of projected dust 

permits from 2008 to 2018, while the relative source locations are held constant. 

However, road construction activity is planned for a wide variety of roads in 2018, 

including some roads nearby the monitoring sites. As a result, the total construction 

modeling impacts approximately doubled in the Cowtown and Stanfield domains.

In the PCH domain, where 2008 construction impacts were modeled to be 

negligible, but where some 2018 road work approaches the monitor, the increase 

was by orders of magnitude.

 Feedlot closures are forecast to reduce CAFO emissions in the CWT domain 

between 2008 and 2018. Feedlot expansions in the STF domain are projected to 

increase CAFO emissions between 2008 and 2018. These changes are projected to 

more than double the impact of CAFOs at STF and to reduce CAFO impacts by 

over 30% at CWT. One 2008 CAFO in the STF domain was repurposed as a dairy, 

increasing the modeled impact of dairies more than sixfold at that monitor. Even 

then, however, the impact of dairies remains negligible.

 On agricultural unpaved roads and unpaved trails, emissions are held constant from 

2008 to 2018. On both public and private roads, however, a traffic increase of nearly 

17% is projected. This growth is mitigated in places by planned or accomplished 

projects to put controls in place (including road improvements and the application 

of synthetic dust suppressants). Overall, from 2008 to 2018, the impact of unpaved 

roads are modeled to increase by 10% at CWT and 7% at STF, and to decrease by 

24% at PCH.

 The emissions for other sources, including agriculture, unpaved parking lots, and 

permitted sources, are held constant from 2008 to 2018; the resulting modeling 

impacts for these sources do not change from 2008 to 2018.
13

Table 2-8. Stagnation Day Modeling Performance at Cowtown (CWT) on 10/30/2008 Design Day,

AERMOD Simulation of Monitored Concentrations (μg/m3)

Hour

Wind Speed 

(m/s)

Wind Direction 

(degrees)

Mixing Height 

(m)

Monitor 

Observation

Point

Background

Construction

CAFOs

Non-tribal 

Agriculture

Tribal 

Agriculture

Unpaved Ag 

Roads

Public Dirt 

Roads

Private Dirt 

Roads

Unpaved Trails

Unpaved Tribal 

Roads

Vehicle Test 

Tracks

Unpaved 

Parking Lots

Paved Roads

Total

1 2.4 139.7 419 210.7 0.0 11.5 0.0 14.5 0.0 0.0 0.0 1.6 0.0 0.0 0.2 0.0 0.0 0.8 28.6

2 2.2 140.2 341 296.4 0.0 11.5 0.0 4.0 0.0 0.0 0.0 0.5 0.1 0.0 0.1 0.0 0.0 0.4 16.7

3 2.3 155.5 378 184.2 0.0 11.5 0.0 7.8 0.0 0.0 0.0 0.7 0.1 0.0 0.2 0.0 0.0 0.3 20.6

4 1.8 154.4 225 169.9 0.0 11.5 0.0 28.7 0.0 0.0 0.0 1.4 0.0 0.0 0.2 0.0 0.0 0.4 42.1

5 2.1 135.6 310 89.1 0.0 11.5 0.0 37.7 0.0 0.0 0.0 2.0 0.1 0.0 0.2 0.0 0.0 0.8 52.2

6 1.1 148.6 93 191.5 0.0 11.5 0.0 269.9 0.0 0.0 0.0 22.5 0.6 0.0 2.2 0.0 0.1 6.0 312.9

7 1.0 158.3 43 265.2 0.0 11.5 0.0 422.1 0.0 1.0 30.0 56.3 0.5 0.0 13.9 0.0 0.7 9.7 545.9

8 0.4 58.8 53 421.2 0.0 11.5 0.0 174.1 0.3 0.9 54.1 38.2 1.5 0.1 10.2 3.5 0.7 4.4 299.4

9 0.5 33.7 134 239.1 0.1 11.5 6.4 0.0 0.6 0.0 34.1 8.5 2.6 0.2 0.0 10.5 0.1 0.5 75.2

10 2.4 98.6 505 120.2 0.0 11.5 5.5 0.0 0.5 0.0 9.7 3.2 1.3 0.1 0.0 6.3 0.0 0.3 38.4

11 1.9 112.3 388 88.7 0.1 11.5 0.1 0.0 0.2 0.0 2.9 1.1 0.3 0.0 0.0 0.0 0.0 0.1 16.2

12 1.6 83.4 493 25.9 0.1 11.5 0.0 0.0 0.1 0.0 3.1 1.6 0.4 0.0 0.1 0.0 0.0 0.0 17.1

13 1.5 325.6 886 86.2 0.1 11.5 2.0 0.0 0.1 0.0 3.5 0.9 0.3 0.0 0.1 0.0 0.0 0.1 18.5

14 1.6 320.7 1225 63.8 0.5 11.5 2.7 0.2 0.0 0.0 4.1 0.3 0.2 0.0 0.0 0.0 0.0 0.3 20.0

15 1.4 335.4 1446 30.8 0.7 11.5 1.4 0.2 0.0 0.0 3.8 0.2 0.2 0.0 0.0 0.0 0.0 0.3 18.3

16 1.1 325.9 1580 49.8 0.3 11.5 1.5 0.4 0.0 0.0 4.8 0.5 0.3 0.0 0.0 0.0 0.0 0.4 19.7

17 1.4 326.7 1621 78.5 0.0 11.5 1.9 0.4 0.0 0.0 5.3 0.5 0.3 0.0 0.0 0.0 0.0 0.5 20.4

18 0.8 290.4 69 298.2 1.3 11.5 0.9 390.0 0.1 0.0 42.2 36.7 1.9 0.0 0.0 0.0 0.2 20.2 505.0

19 0.5 252.5 17 1342.7 1.2 11.5 0.0 1169.8 0.1 0.0 33.6 60.5 3.1 0.0 0.1 0.0 0.3 25.6 1305.7

20 0.8 249.1 28 286.5 0.1 11.5 0.0 1427.2 0.0 0.0 0.0 37.6 3.0 0.0 0.2 0.0 0.1 12.3 1491.9

21 0.5 129.3 17 451.9 0.1 11.5 0.0 629.8 0.0 0.0 0.0 17.1 6.4 0.0 1.1 0.0 0.2 21.8 688.0

22 1.3 170.2 109 264.7 0.0 11.5 0.0 63.8 0.0 0.0 0.0 10.6 4.3 0.0 2.1 0.0 0.1 18.0 110.4

23 0.9 164.1 40 282.8 0.0 11.5 0.0 90.4 0.0 0.0 0.0 12.3 0.0 0.0 2.5 0.0 0.0 6.7 123.5

24 1.9 148.8 269 329.8 0.0 11.5 0.0 56.1 0.0 0.0 0.0 8.1 0.0 0.0 1.4 0.0 0.0 4.0 81.1

24-Hour Average 445.4 244.5 0.2 11.5 0.9 199.5 0.1 0.1 9.6 13.5 1.2 0.0 1.4 0.8 0.1 5.6 244.5

% Contribution - - 0.1% 4.7% 0.4% 81.6% 0.0% 0.0% 3.9% 5.5% 0.5% 0.0% 0.6% 0.3% 0.0% 2.3% 100%
14

Figure 2-2. Modeled vs Monitored Stagnation Day PM10 Concentrations (μg/m3) at Cowtown (CWT) 10/30/2008 Design Day

0

250

500

750

1000

1250

1500

1750

2000

0

200

400

600

800

1000

1200

1400

1600

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

Mixing Height (m)

PM10 Concentration (μg/m3

)

Hour

Paved Roads

Unpaved Parking Lots

Vehicle Test Tracks

Unpaved Tribal Roads

Unpaved Trails

Private Dirt Roads

Public Dirt Roads

Unpaved Ag Roads

Tribal Agriculture

Non-tribal Agriculture

CAFOs

Construction

Background

Point

Monitor Observation

Mixing Height
15

Table 2-9. Stagnation Day Modeling Performance at Pinal County Housing (PCH) on 10/29/2008 

Design Day, AERMOD Simulation of Monitored Concentrations (μg/m3)

Hour

Wind Speed 

(m/s)

Wind Direction 

(degrees)

Mixing Height 

(m)

Monitor 

Observation

Background

Point

Construction

Dairy

Agriculture

Unpaved Ag 

Roads

Public Dirt 

Roads

Private Dirt 

Roads

Unpaved Trails

Unpaved 

Parking Lots

Paved Roads

Total

1 1.0 100.2 49 91.4 11.5 0.0 0.0 0.0 0.0 0.0 4.1 7.4 0.0 0.4 2.0 25.4

2 0.6 122.1 24 86.1 11.5 0.0 0.0 0.0 0.0 0.0 10.8 12.8 0.0 0.4 1.3 36.9

3 0.5 73.5 19 72.5 11.5 0.0 0.0 0.0 0.0 0.0 30.4 12.5 0.0 0.5 1.2 56.1

4 0.5 144.0 19 67.8 11.5 0.0 0.0 0.0 0.0 0.0 20.3 2.8 0.0 0.3 1.3 36.2

5 0.5 246.0 19 76.6 11.5 0.0 0.0 0.0 0.0 0.0 15.7 20.8 0.0 1.0 2.9 51.9

6 0.5 142.8 19 60.1 11.5 0.0 0.0 0.0 0.0 0.0 13.2 47.4 0.0 1.9 6.7 80.7

7 0.5 189.5 19 145.8 11.5 0.0 0.0 0.0 3.5 0.0 0.0 104.4 18.8 14.2 8.1 160.4

8 0.5 276.0 36 287.0 11.5 0.1 0.0 0.0 28.5 34.6 149.5 115.0 59.7 39.4 4.0 442.4

9 0.7 133.5 146 179.2 11.5 0.2 0.0 0.0 28.7 58.1 132.7 46.2 38.6 24.1 1.2 341.4

10 0.5 300.9 273 455.2 11.5 0.1 0.0 0.0 11.3 45.4 40.8 12.5 6.1 1.7 0.6 130.0

11 0.6 18.9 601 234.8 11.5 0.1 0.0 0.0 5.8 28.3 33.5 7.3 9.1 1.3 0.2 97.2

12 0.7 259.9 956 85.6 11.5 0.0 0.0 0.1 1.9 12.1 7.2 5.0 6.9 0.6 0.3 45.7

13 0.6 308.7 1245 71.4 11.5 0.0 0.0 0.0 1.5 6.4 8.9 5.4 5.6 0.7 0.1 40.1

14 1.2 263.9 1458 62.7 11.5 0.0 0.0 0.0 1.0 4.4 7.0 5.5 5.4 0.7 0.1 35.7

15 1.0 292.9 1613 65.6 11.5 0.0 0.0 0.0 0.8 3.5 7.3 6.2 5.5 0.8 0.0 35.5

16 0.7 244.0 1705 54.5 11.5 0.0 0.0 0.2 0.7 4.2 6.4 6.8 5.3 0.8 0.2 36.1

17 0.7 294.0 1724 40.8 11.5 0.0 0.0 0.2 1.2 6.1 10.4 8.0 8.4 1.0 0.2 47.0

18 0.5 300.1 26 368.4 11.5 0.0 0.0 0.0 36.4 262.6 341.2 177.3 44.8 19.6 0.7 894.2

19 0.5 53.0 19 588.4 11.5 0.0 0.0 0.0 29.9 217.6 450.4 174.3 33.2 17.5 12.5 946.8

20 0.5 57.4 19 453.5 11.5 0.0 0.0 0.0 0.0 0.0 223.8 47.9 0.0 2.3 18.3 303.8

21 0.5 91.7 19 281.6 11.5 0.0 0.0 0.0 0.0 0.0 97.4 44.0 0.0 2.4 13.1 168.4

22 0.5 82.1 19 199.3 11.5 0.0 0.0 0.0 0.0 0.0 67.4 26.9 0.0 1.9 10.3 118.0

23 0.5 128.4 19 128.6 11.5 0.0 0.0 0.0 0.0 0.0 50.0 23.1 0.0 1.0 7.7 93.2

24 0.5 187.8 19 114.4 11.5 0.0 0.0 0.0 0.0 0.0 11.9 20.4 0.0 0.7 4.4 48.9

24-Hour Average 419.4 178.0 11.5 0.0 0.0 0.0 6.3 28.5 72.5 39.2 10.3 5.6 4.1 178.0

% Contribution - - 6.5% 0.0% 0.0% 0.0% 3.5% 16.0% 40.7% 22.0% 5.8% 3.2% 2.3% 100%
16

Figure 2-3. Modeled vs Monitored Stagnation Day PM10 Concentrations (μg/m3) at Pinal County Housing (PCH) 10/29/2008 Design Day

0

200

400

600

800

1000

1200

1400

1600

1800

2000

0

100

200

300

400

500

600

700

800

900

1000

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

Mixing Height (m)

PM10 Concentration (μg/m3

)

Hour

Paved Roads

Unpaved Parking Lots

Unpaved Trails

Private Dirt Roads

Public Dirt Roads

Unpaved Ag Roads

Agriculture

Dairy

Construction

Point

Background

Monitor Observation

Mixing Height
17

Table 2-10. Stagnation Day Modeling Performance at Stanfield (STF) on 10/29/2008 Design Day,

AERMOD Simulation of Monitored Concentrations (μg/m3)

Hour

Wind Speed 

(m/s)

Wind Direction 

(degrees)

Mixing Height 

(m)

Monitor 

Observation

Background

Construction

CAFOs

Dairy

Agriculture

Unpaved Ag 

Roads

Public Dirt 

Roads

Private Dirt 

Roads

Unpaved Trails

Unpaved 

Parking Lots

Paved Roads

Total

1 1.0 251.9 27 46.0 11.5 0.0 0.0 0.0 0.0 0.0 7.7 4.2 0.0 0.2 4.0 27.6

2 1.0 159.9 31 79.0 11.5 0.0 0.0 0.0 0.0 0.0 7.7 18.2 0.0 0.5 3.2 41.1

3 1.6 139.5 57 76.8 11.5 0.0 0.0 0.0 0.0 0.0 8.3 20.3 0.0 0.6 0.6 41.3

4 1.3 155.2 42 63.0 11.5 0.0 0.0 0.0 0.0 0.0 6.6 5.0 0.0 0.2 0.6 23.9

5 1.2 99.4 41 144.0 11.5 0.0 168.8 0.0 0.0 0.0 15.4 7.7 0.0 0.3 4.1 207.8

6 0.9 108.0 24 183.5 11.5 0.0 253.3 0.0 0.0 0.0 98.5 46.8 0.0 1.1 13.3 424.5

7 0.8 179.6 21 187.7 11.5 0.0 92.6 0.0 26.1 158.7 115.3 105.6 1.0 19.0 15.0 544.8

8 0.8 171.9 21 307.2 11.5 0.0 0.0 0.0 51.8 297.2 94.5 104.8 2.4 34.7 13.2 610.1

9 0.7 183.8 98 226.0 11.5 1.8 0.0 0.0 34.3 243.3 78.8 48.1 1.9 19.5 8.3 447.5

10 1.6 82.4 266 133.2 11.5 1.5 3.8 0.0 9.8 105.0 29.5 13.5 2.6 4.5 1.7 183.4

11 1.4 121.4 539 126.2 11.5 0.0 4.5 0.0 4.4 32.1 14.1 7.6 2.0 3.0 0.4 79.6

12 1.3 129.8 888 116.1 11.5 0.0 1.3 0.0 4.0 26.9 15.0 8.8 0.3 2.7 0.4 70.9

13 1.3 165.8 1177 101.7 11.5 0.4 0.2 0.0 2.4 14.1 8.0 9.0 0.2 2.5 0.4 48.7

14 0.9 112.1 1387 69.7 11.5 0.3 1.7 0.0 1.8 12.7 7.3 9.2 0.9 2.6 0.5 48.5

15 1.0 67.2 1541 65.5 11.5 0.0 1.7 0.0 1.7 15.1 8.8 6.3 2.5 2.8 0.4 50.8

16 1.1 94.3 1632 43.8 11.5 0.0 2.3 0.0 1.4 13.6 8.7 5.8 3.0 3.0 0.6 49.9

17 1.3 59.4 1652 43.8 11.5 0.0 1.8 0.0 1.5 16.2 6.9 4.2 5.1 3.7 0.6 51.5

18 1.2 5.3 45 509.1 11.5 0.0 0.0 0.0 7.0 278.8 3.6 6.0 8.5 11.3 0.4 327.1

19 1.1 297.8 35 341.7 11.5 0.0 0.0 0.0 5.3 227.1 1.3 35.9 4.5 8.4 2.1 296.1

20 0.8 296.4 21 628.5 11.5 0.0 0.0 0.0 0.0 0.0 0.0 53.5 0.0 0.7 3.0 68.7

21 1.3 260.5 44 124.8 11.5 0.0 0.1 0.0 0.0 0.0 8.0 37.7 0.0 0.7 17.2 75.2

22 1.0 253.8 28 72.7 11.5 0.0 0.1 0.0 0.0 0.0 13.0 17.7 0.0 0.5 28.4 71.2

23 1.3 169.3 43 93.1 11.5 0.0 0.0 0.0 0.0 0.0 14.9 14.8 0.0 0.6 14.0 55.8

24 1.6 163.9 58 106.6 11.5 0.0 0.0 0.0 0.0 0.0 15.7 12.2 0.0 0.6 1.9 41.9

24-Hour Average 405 162.1 11.5 0.2 22.2 0.0 6.3 60.0 24.5 25.1 1.5 5.2 5.6 162.0

% Contribution - - 7.1% 0.1% 13.7% 0.0% 3.9% 37.1% 15.1% 15.5% 0.9% 3.2% 3.5% 100%
18

Figure 2-4. Modeled vs Monitored Stagnation Day PM10 Concentrations (μg/m3) at Stanfield (STF) 10/29/2008 Design Day

0

250

500

750

1000

1250

1500

1750

2000

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

Mixing Height (m)

PM10 Concentration (μg/m3

)

Hour

Paved Roads

Unpaved Parking Lots

Unpaved Trails

Private Dirt Roads

Public Dirt Roads

Unpaved Ag Roads

Agriculture

Dairy

CAFOs

Construction

Background

Monitor Observation

Mixing Height
19

Figure 2-5. 2008 Stagnation Design Days Source Contributions

Cowtown Pinal County Housing

Stanfield

Background

11.5 μg/m3

4.7%

CAFOs

199.5 μg/m3

81.6%

Unpaved Ag 

Roads

9.6 μg/m3

3.9%

Public Dirt 

Roads

13.5 μg/m3

5.5%

Paved Roads

5.6 μg/m3

2.3%

Remaining 

Sources

4.9 μg/m3

2.0%

Background

11.5 μg/m3

6.5%

Construction

0.0 μg/m3

0.0%

Agriculture

6.3 μg/m3

3.5%

Unpaved Ag 

Roads

28.5 μg/m3

16.0%

Public Dirt 

Roads

72.5 μg/m3

40.7%

Private Dirt 

Roads

39.2 μg/m3

22.0%

Unpaved 

Trails

10.3 μg/m3

5.8%

Unpaved 

Parking Lots

5.6 μg/m3

3.2%

Paved Roads

4.1 μg/m3

2.3%

Remaining 

Sources

0.0 μg/m3

0.0%

Background

11.5 μg/m3

7.1%

CAFOs

22.2 μg/m3

13.7%

Agriculture

6.3 μg/m3

3.9%

Unpaved Ag 

Roads

60.0 μg/m3

37.1%

Public Dirt 

Roads

24.5 μg/m3

15.1%

Private Dirt 

Roads

25.1 μg/m3

15.5%

Unpaved 

Parking Lots

5.2 μg/m3

3.2%

Paved Roads

5.6 μg/m3

3.5%

Remaining 

Sources

1.6 μg/m3

1.0%
20

Table 2-11. Projected 2018 Stagnation Day Modeling Performance at Cowtown (CWT) on 10/30/2008,

AERMOD Simulation of Monitored Concentrations (μg/m3) 

Hour

Wind Speed 

(m/s)

Wind Direction 

(degrees)

Mixing Height 

(m)

2008 Monitor 

Observation

Point

Background

Construction

CAFOs

Non-tribal 

Agriculture

Tribal 

Agriculture

Unpaved Ag 

Roads

Public Dirt 

Roads

Private Dirt 

Roads

Unpaved Trails

Unpaved Tribal 

Roads

Vehicle Test 

Tracks

Unpaved 

Parking Lots

Paved Roads

Total

1 2.4 139.7 419 210.7 0.0 11.5 0.0 0.0 0.0 0.0 0.0 1.9 0.0 0.0 0.2 0.0 0.0 1.3 14.9

2 2.2 140.2 341 296.4 0.0 11.5 0.0 0.0 0.0 0.0 0.0 0.6 0.1 0.0 0.2 0.0 0.0 0.6 13.0

3 2.3 155.5 378 184.2 0.0 11.5 0.0 0.0 0.0 0.0 0.0 0.9 0.1 0.0 0.2 0.0 0.0 0.5 13.1

4 1.8 154.4 225 169.9 0.0 11.5 0.0 0.0 0.0 0.0 0.0 1.6 0.0 0.0 0.2 0.0 0.0 0.7 14.0

5 2.1 135.6 310 89.1 0.0 11.5 0.0 0.0 0.0 0.0 0.0 2.3 0.1 0.0 0.2 0.0 0.0 1.3 15.5

6 1.1 148.6 93 191.5 0.0 11.5 0.0 0.0 0.0 0.0 0.0 26.4 0.7 0.0 2.6 0.0 0.1 10.0 51.2

7 1.0 158.3 43 265.2 0.0 11.5 0.0 0.0 0.0 1.0 30.0 65.9 0.6 0.0 15.0 0.0 0.7 16.0 140.7

8 0.4 58.8 53 421.2 0.0 11.5 0.0 0.0 0.3 0.9 54.1 44.6 1.7 0.1 10.8 3.5 0.7 7.2 135.4

9 0.5 33.7 134 239.1 0.1 11.5 19.6 0.0 0.6 0.0 34.1 9.9 3.1 0.2 0.0 10.5 0.1 0.8 90.6

10 2.4 98.6 505 120.2 0.0 11.5 16.6 0.0 0.5 0.0 9.7 3.8 1.5 0.1 0.0 6.3 0.0 0.5 50.4

11 1.9 112.3 388 88.7 0.1 11.5 0.2 0.0 0.2 0.0 2.9 1.3 0.4 0.0 0.0 0.0 0.0 0.1 16.6

12 1.6 83.4 493 25.9 0.1 11.5 0.1 0.0 0.1 0.0 3.1 1.9 0.5 0.0 0.1 0.0 0.0 0.1 17.6

13 1.5 325.6 886 86.2 0.1 11.5 1.3 0.0 0.1 0.0 3.5 1.0 0.4 0.0 0.1 0.0 0.0 0.2 18.1

14 1.6 320.7 1225 63.8 0.5 11.5 1.8 0.1 0.0 0.0 4.1 0.3 0.3 0.0 0.0 0.0 0.0 0.5 19.2

15 1.4 335.4 1446 30.8 0.7 11.5 0.9 0.1 0.0 0.0 3.8 0.3 0.3 0.0 0.0 0.0 0.0 0.5 18.0

16 1.1 325.9 1580 49.8 0.3 11.5 0.9 0.3 0.0 0.0 4.8 0.6 0.3 0.0 0.0 0.0 0.0 0.7 19.5

17 1.4 326.7 1621 78.5 0.0 11.5 1.3 0.3 0.0 0.0 5.3 0.6 0.3 0.0 0.0 0.0 0.0 0.7 20.0

18 0.8 290.4 69 298.2 1.3 11.5 0.5 213.0 0.1 0.0 42.2 42.9 2.2 0.0 0.0 0.0 0.2 33.2 347.1

19 0.5 252.5 17 1342.7 1.2 11.5 0.0 1015.8 0.1 0.0 33.6 70.7 3.6 0.0 0.1 0.0 0.3 42.3 1179.1

20 0.8 249.1 28 286.5 0.1 11.5 0.0 1427.2 0.0 0.0 0.0 43.9 3.5 0.0 0.2 0.0 0.1 20.6 1507.1

21 0.5 129.3 17 451.9 0.1 11.5 0.0 613.0 0.0 0.0 0.0 20.0 7.5 0.0 1.3 0.0 0.2 36.1 689.7

22 1.3 170.2 109 264.7 0.0 11.5 0.0 0.0 0.0 0.0 0.0 12.4 5.0 0.0 2.5 0.0 0.1 29.7 61.2

23 0.9 164.1 40 282.8 0.0 11.5 0.0 0.0 0.0 0.0 0.0 14.4 0.0 0.0 2.9 0.0 0.0 11.1 40.0

24 1.9 148.8 269 329.8 0.0 11.5 0.0 0.0 0.0 0.0 0.0 9.5 0.0 0.0 1.6 0.0 0.0 6.7 29.3

24-Hour Average 445.4 244.5 0.2 11.5 1.8 136.2 0.1 0.1 9.6 15.7 1.3 0.0 1.6 0.8 0.1 9.2 188.4

% Contribution - - 0.1% 6.1% 1.0% 72.3% 0.0% 0.0% 5.1% 8.3% 0.7% 0.0% 0.8% 0.4% 0.1% 4.9% 100%
21

Figure 2-6. 2018 Modeled vs. 2008 Monitored Stagnation Day Concentrations (μg/m3) at Cowtown (CWT) 10/30/2008 Design Day

0

250

500

750

1000

1250

1500

1750

2000

0

200

400

600

800

1000

1200

1400

1600

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

Mixing Height (m)

PM10 Concentration (μg/m3

)

Hour

Paved Roads

Unpaved Parking Lots

Vehicle Test Tracks

Unpaved Tribal Roads

Unpaved Trails

Private Dirt Roads

Public Dirt Roads

Unpaved Ag Roads

Tribal Agriculture

Non-tribal Agriculture

CAFOs

Construction

Background

Point

Monitor Observation

Mixing Height
22

Table 2-12. Projected 2018 Stagnation Day Modeling Performance at Pinal County Housing (PCH) on 

10/29/2008, AERMOD Simulation of Monitored Concentrations (μg/m3)

Hour

Wind Speed 

(m/s)

Wind Direction 

(degrees)

Mixing Height 

(m)

2008 Monitor 

Observation

Background

Point

Construction

Dairy

Agriculture

Unpaved Ag 

Roads

Public Dirt 

Roads

Private Dirt 

Roads

Unpaved Trails

Unpaved 

Parking Lots

Paved Roads

Total

1 1.0 100.2 49 91.4 11.5 0.0 0.0 0.0 0.0 0.0 4.8 8.6 0.0 0.4 2.9 28.1

2 0.6 122.1 24 86.1 11.5 0.0 0.0 0.0 0.0 0.0 12.6 14.9 0.0 0.4 1.8 41.2

3 0.5 73.5 19 72.5 11.5 0.0 0.0 0.0 0.0 0.0 13.2 14.5 0.0 0.5 1.6 41.4

4 0.5 144.0 19 67.8 11.5 0.0 0.0 0.0 0.0 0.0 5.0 3.3 0.0 0.3 1.8 21.9

5 0.5 246.0 19 76.6 11.5 0.0 0.0 0.0 0.0 0.0 3.4 24.2 0.0 1.0 4.0 44.2

6 0.5 142.8 19 60.1 11.5 0.0 0.0 0.0 0.0 0.0 2.9 55.2 0.0 1.9 9.2 80.7

7 0.5 189.5 19 145.8 11.5 0.0 0.0 0.0 3.5 0.0 0.0 121.6 18.8 14.2 11.0 180.6

8 0.5 276.0 36 287.0 11.5 0.1 430.2 0.0 28.5 34.6 7.2 127.8 59.7 39.4 4.9 744.0

9 0.7 133.5 146 179.2 11.5 0.2 362.8 0.0 28.7 58.1 14.4 48.5 38.6 24.1 1.2 588.2

10 0.5 300.9 273 455.2 11.5 0.1 6.3 0.0 11.3 45.4 28.8 14.6 6.1 1.7 0.8 126.5

11 0.6 18.9 601 234.8 11.5 0.1 4.3 0.0 5.8 28.3 18.4 8.5 9.1 1.3 0.3 87.6

12 0.7 259.9 956 85.6 11.5 0.0 10.2 0.1 1.9 12.1 0.6 5.8 6.9 0.6 0.4 50.0

13 0.6 308.7 1245 71.4 11.5 0.0 10.0 0.0 1.5 6.4 2.9 6.3 5.6 0.7 0.2 44.9

14 1.2 263.9 1458 62.7 11.5 0.0 6.9 0.0 1.0 4.4 2.3 6.4 5.4 0.7 0.1 38.7

15 1.0 292.9 1613 65.6 11.5 0.0 7.1 0.0 0.8 3.5 1.6 7.1 5.5 0.8 0.1 38.0

16 0.7 244.0 1705 54.5 11.5 0.0 7.9 0.2 0.7 4.2 1.4 7.9 5.3 0.8 0.3 40.2

17 0.7 294.0 1724 40.8 11.5 0.0 8.8 0.2 1.2 6.1 3.1 9.3 8.4 1.0 0.3 49.8

18 0.5 300.1 26 368.4 11.5 0.0 3.2 0.0 36.4 262.6 162.6 207.2 44.8 19.6 0.9 748.8

19 0.5 53.0 19 588.4 11.5 0.0 0.0 0.0 29.9 217.6 191.8 203.7 33.2 17.5 17.0 722.1

20 0.5 57.4 19 453.5 11.5 0.0 0.0 0.0 0.0 0.0 83.1 56.2 0.0 2.3 24.8 177.8

21 0.5 91.7 19 281.6 11.5 0.0 0.0 0.0 0.0 0.0 63.6 51.6 0.0 2.4 17.8 146.9

22 0.5 82.1 19 199.3 11.5 0.0 0.0 0.0 0.0 0.0 60.4 31.6 0.0 1.9 13.9 119.3

23 0.5 128.4 19 128.6 11.5 0.0 0.0 0.0 0.0 0.0 43.0 26.9 0.0 1.0 10.4 92.8

24 0.5 187.8 19 114.4 11.5 0.0 0.0 0.0 0.0 0.0 13.8 23.8 0.0 0.7 6.0 55.9

24-Hour Average 419.4 178.0 11.5 0.0 35.7 0.0 6.3 28.5 30.9 45.2 10.3 5.6 5.5 179.6

% Contribution - - 6.4% 0.0% 19.9% 0.0% 3.5% 15.9% 17.2% 25.2% 5.7% 3.1% 3.0% 100%
23

Figure 2-7. 2018 Modeled vs. 2008 Monitored Stagnation Day Concentrations (μg/m3) at Pinal County Housing (PCH) 10/29/2008 Design 

Day

0

200

400

600

800

1000

1200

1400

1600

1800

2000

0

100

200

300

400

500

600

700

800

900

1000

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

Mixing Height (m)

PM10 Concentration (μg/m3

)

Hour

Paved Roads

Unpaved Parking Lots

Unpaved Trails

Private Dirt Roads

Public Dirt Roads

Unpaved Ag Roads

Agriculture

Dairy

Construction

Point

Background

Monitor Observation

Mixing Height
24

Table 2-13. Projected 2018 Stagnation Day Modeling Performance at Stanfield (STF) on 10/29/2008,

AERMOD Simulation of Monitored Concentrations (μg/m3)

Hour

Wind Speed 

(m/s)

Wind Direction 

(degrees)

Mixing Height

(m)

2008 Monitor 

Observation

Background

Construction

CAFOs

Dairy

Agriculture

Unpaved Ag 

Roads

Public Dirt 

Roads

Private Dirt 

Roads

Unpaved Trails

Unpaved 

Parking Lots

Paved Roads

Total

1 1.0 251.9 27 46.0 11.5 0.0 0.0 0.0 0.0 0.0 9.0 4.9 0.0 0.2 5.9 31.5

2 1.0 159.9 31 79.0 11.5 0.0 0.0 0.0 0.0 0.0 9.0 21.3 0.0 0.5 4.8 47.1

3 1.6 139.5 57 76.8 11.5 0.0 0.0 0.0 0.0 0.0 9.7 23.7 0.0 0.6 0.8 46.3

4 1.3 155.2 42 63.0 11.5 0.0 0.0 0.0 0.0 0.0 7.7 5.8 0.0 0.2 0.8 26.0

5 1.2 99.4 41 144.0 11.5 0.0 370.9 0.0 0.0 0.0 18.0 9.0 0.0 0.3 2.4 412.1

6 0.9 108.0 24 183.5 11.5 0.0 556.4 0.0 0.0 0.0 115.2 54.5 0.0 1.1 8.1 746.8

7 0.8 179.6 21 187.7 11.5 0.0 203.4 0.0 26.1 158.7 134.7 123.1 1.0 19.0 13.8 691.3

8 0.8 171.9 21 307.2 11.5 0.0 0.0 0.0 51.8 297.2 110.3 122.2 2.4 34.7 17.0 647.1

9 0.7 183.8 98 226.0 11.5 1.2 0.0 0.0 34.3 243.3 92.0 56.1 1.9 19.5 10.6 470.4

10 1.6 82.4 266 133.2 11.5 1.9 0.7 0.0 9.8 105.0 34.4 15.8 2.6 4.5 2.1 188.3

11 1.4 121.4 539 126.2 11.5 1.4 3.1 0.0 4.4 32.1 16.5 8.9 2.0 3.0 0.4 83.3

12 1.3 129.8 888 116.1 11.5 1.0 2.8 0.0 4.0 26.9 17.6 10.3 0.3 2.7 0.5 77.6

13 1.3 165.8 1177 101.7 11.5 0.6 0.5 0.0 2.4 14.1 9.4 10.5 0.2 2.5 0.5 52.2

14 0.9 112.1 1387 69.7 11.5 0.6 3.6 0.0 1.8 12.7 8.5 10.7 0.9 2.6 0.5 53.4

15 1.0 67.2 1541 65.5 11.5 0.6 3.5 0.0 1.7 15.1 10.3 7.4 2.5 2.8 0.4 55.8

16 1.1 94.3 1632 43.8 11.5 0.5 4.3 0.0 1.4 13.6 10.1 6.7 3.0 3.0 0.7 54.8

17 1.3 59.4 1652 43.8 11.5 0.4 3.5 0.0 1.5 16.2 8.0 4.9 5.1 3.7 0.8 55.6

18 1.2 5.3 45 509.1 11.5 0.2 0.0 0.0 7.0 278.8 4.2 7.1 8.5 11.3 0.2 328.8

19 1.1 297.8 35 341.7 11.5 0.0 0.0 0.0 5.3 227.1 1.5 41.9 4.5 8.4 2.7 302.9

20 0.8 296.4 21 628.5 11.5 0.0 0.0 0.0 0.0 0.0 0.0 62.3 0.0 0.7 4.3 78.8

21 1.3 260.5 44 124.8 11.5 0.0 0.1 0.0 0.0 0.0 9.3 43.9 0.0 0.7 25.0 90.5

22 1.0 253.8 28 72.7 11.5 0.0 0.1 0.0 0.0 0.0 15.1 20.7 0.0 0.5 41.7 89.6

23 1.3 169.3 43 93.1 11.5 0.0 0.0 0.0 0.0 0.0 17.4 17.2 0.0 0.6 20.6 67.3

24 1.6 163.9 58 106.6 11.5 0.0 0.0 0.0 0.0 0.0 18.3 14.2 0.0 0.6 2.7 47.3

24-Hour Average 404.9 162.1 11.5 0.4 48.0 0.0 6.3 60.0 28.6 29.3 1.5 5.2 7.0 197.7

% Contribution - - 5.8% 0.2% 24.3% 0.0% 3.2% 30.4% 14.5% 14.8% 0.7% 2.6% 3.5% 100%
25

Figure 2-8. 2018 Modeled vs. 2008 Monitored Stagnation Day Concentrations (μg/m3) at Stanfield (STF) 10/29/2008 Design Day

0

250

500

750

1000

1250

1500

1750

2000

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

Mixing Height (m)

PM10 Concentration (μg/m3

)

Hour

Paved Roads

Unpaved Parking Lots

Unpaved Trails

Private Dirt Roads

Public Dirt Roads

Unpaved Ag Roads

Agriculture

Dairy

CAFOs

Construction

Background

Monitor Observation

Mixing Height
26

Figure 2-9. Projected 2018 Stagnation Design Day Source Contributions

Cowtown Pinal County Housing

Stanfield

Background

11.5 μg/m3

6.1%

CAFOs

136.2 μg/m3

72.3%

Unpaved Ag 

Roads

9.6 μg/m3

5.1% Public Dirt 

Roads

15.7 μg/m3

8.3%

Paved Roads

9.2 μg/m3

4.9%

Remaining 

Sources

6.1 μg/m3

3.2%

Background

11.5 μg/m3

6.4%

Construction

35.7 μg/m3

19.9%

Agriculture

6.3 μg/m3

3.5%

Unpaved Ag 

Roads

28.5 μg/m3

15.9%

Public Dirt 

Roads

30.9 μg/m3

17.2%

Private Dirt 

Roads

45.2 μg/m3

25.2%

Unpaved 

Trails

10.3 μg/m3

5.7%

Unpaved 

Parking Lots

5.6 μg/m3

3.1%

Paved Roads

5.5 μg/m3

3.0%

Remaining 

Sources

0.0 μg/m3

0.0%

Background

11.5 μg/m3

5.8%

CAFOs

48.0 μg/m3

24.3%

Agriculture

6.3 μg/m3

3.2%

Unpaved Ag 

Roads

60.0 μg/m3

30.4%

Public Dirt 

Roads

28.6 μg/m3

14.5%

Private Dirt 

Roads

29.3 μg/m3

14.8%

Unpaved 

Parking Lots

5.2 μg/m3

2.6%

Paved Roads

7.0 μg/m3

3.5%

Remaining 

Sources

1.8 μg/m3

0.9%
27

3. HIGH WIND DAY MODELING

High wind design days selected for Pinal County PM10 monitoring sites included both high 

wind hours (when hourly average wind speeds exceeded 12 mph) and low wind hours. 

During high wind hours, windblown PM10 emissions are generally much greater than those 

generated by mechanical sources. However, as discussed in the emission inventory report, 

emissions from sources of mechanically generated PM10 were included in the modeling of 

windblown PM10 emissions in order to fully account for all source contributions during 

high wind hours. For low wind hours, it was assumed that all PM10 emissions are generated 

by mechanical sources and none are produced by wind entrainment. The remainder of this 

section describes how high wind hour emissions were treated and how the benefits from 

high wind control measures were evaluated.

3.1 Methodology

The method used to assess high wind hour source apportionment and to provide a basis for 

demonstrating attainment is the weighted rollback method, a demonstration approach that 

was employed in MAG’s Five Percent Plan23 and approved by EPA. As discussed in the 

Five Percent Plan:

The fundamental assumption underlying any rollback method is that 

pollutant concentrations are directly proportional to total emissions over 

the area of interest. A weighted rollback approach applies a distance 

reduction factor to the emissions of each source in the modeling domain to 

help assess the impact of emissions as distance from the monitor increases. 

The reduction factor is calculated based upon the distance between each 

source and the impacting monitor. 

The concept for this approach came from a saturation monitoring study in which Maricopa 

County placed a string of temporary PM10 continuous monitors along the Salt River 

channel west of the permanent monitors in the Salt River industrial zone (i.e., West 43rd

Avenue and Durango Complex stations). Data were collected for an extended period, and 

differences between sequential monitored concentrations were calculated during high wind 

hours when winds generally followed a path parallel to the line connecting the temporary 

and permanent monitors. The results of that analysis and the AERMOD analysis of 

alternate weighting factors determined that distance weighting (1/distance, where distance 

is measured from the centroid of the source to the monitor) was an appropriate mechanism 

to evaluate the impacts of PM10 emissions from individual land parcels within back-

 

23 Section 6, Attainment Demonstration, “MAG 2012 Five Percent Plan for PM-10 for Maricopa County 

Nonattainment Area,” Maricopa Association of Governments, May 2012.
28

trajectory modeling domains. MAG used this approach to evaluate all high wind hour 

emission estimates. 

Because Maricopa County had not experienced a low wind violation of the PM10 standard 

since 2007, the Five Percent Plan focused on modeling windblown fugitive dust produced 

during high wind hours. This resulted in the distance-weighted modeling approach cited 

above to assess impacts at monitors. Low wind monitor impacts were not modeled; instead,

emission inventory estimates for the low wind domains were simply quantified24 to 

represent the basis for low wind hour concentrations. 

In contrast to Maricopa County, Pinal County experienced violations under both stagnation 

and high wind conditions. A review of low wind hour concentrations on high wind design 

days found that some low wind hour concentrations exceeded high wind hour 

concentrations. Based on this finding, decisions were made (1) to model the effect of low 

wind hour mechanically generated emissions and (2) to model both mechanically generated 

emissions and windblown dust emissions during high wind hours.

As noted in the accompanying base year emission inventory document, mechanically 

driven emissions were quantified for the low wind domains at each monitor for each hour 

of the high wind design days. Because the areal extent of these domains encompassed the 

high wind domains, mechanically driven emissions for sources located within the high 

wind domains were extracted from the low wind domains for the high wind hours using 

45o arcs centered on and opening in the direction opposite to the vector-average wind 

direction for each high wind hour. The rationale supporting this choice was that the areal 

extent of the low wind domains should approximate the modeling domains used for high 

winds. A similar approach was adopted to define the areal boundaries of low wind hour 

domains to be modeled.25 Parcel-specific emissions within the low wind and high wind 

domains were weighted in proportion to their distance from the monitor. This approach 

ensured that both high and low wind hourly emissions were weighted in the same manner 

so as to be additive and facilitate control strategy benefit analysis.

3.2 Non-Anthropogenic Background

Evaluations of meteorological conditions on high wind design days revealed that winds 

capable of entraining surface soil particles (i.e., having hourly average speeds ≥ 12 mph) 

were consistently from the northeast direction during high wind hours. One of the closest 

PM10 monitors outside the boundary of the Western Pinal County nonattainment area and 

generally upwind in a northeasterly direction from the four high wind exceedance monitors 

is a station located in the small community of Queen Valley. The community of Queen 

Valley was recorded in the 2010 Census as having a permanent population of 788. The 

permanent population is augmented in winter by seasonal residents drawn by the relatively 

moderate climate. Land use in the area is predominately residential, light commercial use, 

 

24 Page V-75, “Technical Document in Support of the MAG 2012 Five Percent Plan for PM-10 for the 

Maricopa County Nonattainment Area,” Maricopa Association of Governments, May 2012.

25 Boundaries for both low and high wind hour domains on high wind days are displayed in Section 2 of

Appendix B of this SIP submittal, “Pinal County PM10 Nonattainment Area Emissions Inventories for 

2008 and 2018 Base Years and Design Days,” ibid.
29

and recreation (e.g., the nearby golf course). The topography of the area is generally hilly 

or mountainous, with the Queen Creek wash running east to west through the community. 

PM10 source emissions near the site are low and limited to contributions from vehicular 

traffic and residential and commercial activities. In general, roadways in Queen Valley are 

paved, with the exception of roads outside the populated area. The Queen Valley site was 

selected to represent PM10 concentrations near the upwind boundary of the nonattainment 

area during high wind hours.

Because the Queen Valley PM10 monitoring period included days during which no high 

wind hours were recorded, available 24-hour average PM10 concentrations were screened 

to identify the subset of high wind days. Because the Queen Valley site does not record 

meteorological conditions, meteorological data were obtained from a monitoring station 

located in Superior, Arizona, approximately 12 miles to the east. The Queen Valley data 

were screened to eliminate days with fewer than 6 hours of high winds (> 12 mph), to be 

consistent with the criteria used to define days eligible for high wind design day 

designation, and days when high winds were predominantly from directions other than the 

northeast. This produced a 6-day data set, with an average concentration of 17.5 μg/m3. 

An analysis of high wind days at Organ Pipe Cactus National Monument, the background 

site used in the MAG Five Percent Plan, produced a 5-day data set with an average 

concentration of 18.5 μg/m3, demonstrating that the Queen Valley high wind day 

concentrations were in the same range as those collected at Organ Pipe, a rural site with 

almost no anthropogenic activity or disturbance nearby. The 6-day average of 17.5 μg/m3

recorded at Queen Valley was selected to represent the background PM10 level in high wind 

rollback calculations. 

3.3 Results

A summary of the source contributions to overall weighted emissions is presented by hour 

for each monitor and design day in Tables 3-1 through 3-4 (2008 base year) and Tables 3-

5 through 3-8 (the projected year of 2018) for Pinal County Housing, Cowtown, Maricopa,

and Stanfield monitoring sites, respectively. Also presented is information on hourly wind 

speed, wind direction, and monitored concentration. While these variables employ 

different units (degrees, miles/hour, μg/m3, etc.), insight into source apportionment can be 

gained by contrasting the modeled diurnal profiles of individual source categories and the 

monitored diurnal profiles of the four sites on designated high wind design days. Visual 

displays of the source-specific hourly weighted emission estimates and monitored 

concentrations are displayed in Figures 3-1 through 3-4 (2008 base year) and Figures 3-6 

through 3-9 (the projected year of 2018). Figure 3-5 (2008 base year) and Figure 3-10 (the 

projected year of 2018) summarize the average daily source-specific contributions for each 

site.

The methodology for computing high wind emission factors is presented in Appendix B of 

this SIP submittal.

26

 Independent of the relationships developed between windblown PM10

emission factors and hourly-average wind speed, the analysis of emission factors in the 

accompanying document includes discussions of particle saltation initiation times and soil 

 

26

“Pinal County PM10 Nonattainment Area Emissions Inventories for 2008 and 2018 Base Years and 

Design Days,” ibid.
30

reservoir depletion that also play a role in the diurnal profile of windblown PM10 emissions 

on high wind days. 

High wind days are comprised of activity-based emissions (occurring during low and high 

wind hours) and windblown emissions (occurring during high wind hours). Changes in the 

low wind hour emissions estimates between 2008 and 2018 are similar to those described 

in Section 2. High wind hour windblown emission estimates are projected to remain the 

same between 2008 and 2018 except for a few land use categories:

 Windblown dust emissions from construction are projected to decline by 36% as 

the number of dust permits decreases from 2008 to 2018.

27

 

 To account for the completion of construction projects, some Construction land 

use area was reclassified as Developed Urban Lands. As a result, the Developed 

Urban Lands windblown dust total grew by 24% from 2008 to 2018.

 Similarly, as a result of road improvement construction projects being completed, 

Unpaved Road windblown dust emissions were slightly lower in 2018 than in 

2008.

 CAFOs which stopped operating between 2008 and 2018 were reclassified as 

Cleared Areas. Subsequently, windblown dust emissions from CAFOs dropped 

by 43%, while emissions from Cleared Areas increased by 15%. 

The resulting changes in high wind modeling impacts from 2008 to 2018 are generally 

small, except for the Maricopa site, where construction is one of the dominant source

categories.

 

27 The detailed construction emission projections from 2008 to 2018 are described in Section 3.2.2 of the 

emission inventory document, “Pinal County PM10 Nonattainment Area Emissions Inventories for 2008 

and 2018 Base Years and Design Days,” ibid.
31

Table 3-1. Distance-Weighted Emissions (lbs/mile) for the High Wind Modeling Domain at Pinal County Housing (PCH) on 

1/1/2008 Design Day

Hour

Wind 

Speed 

(mph)

Wind 

Direction 

(degrees)

Monitor 

Obser- vation

Paved 

Road

Point 

Sources

Con- struction

Unpaved 

Parking 

Lots

Cleared 

Area

Desert 

Shrubland

Developed 

Rural Lands

Developed 

Urban 

Lands

Agri- culture

Unpaved 

Ag Roads

Public Dirt 

Roads

Private Dirt 

Roads

Unpaved 

Trails

Total

1 1.6 303.8 28.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.4 0.2 0.0 2.6

2 1.5 318.0 21.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 2.0 1.5 0.0 3.6

3 1.9 335.4 22.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.2 1.2 0.0 2.4

4 2.5 333.7 24.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.5 0.0 0.0 1.5

5 5.9 352.2 16.4 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.4 1.2 0.0 2.8

6 3.1 299.6 19.1 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 13.0 2.7 0.0 15.9

7 3.9 339.3 16.2 0.1 0.0 0.0 1.6 0.0 0.0 0.0 0.0 12.8 46.2 13.1 10.2 0.9 85.0

8 5.7 5.0 22.7 1.3 0.0 0.0 0.9 0.0 0.0 0.0 0.0 14.1 61.2 13.2 5.2 0.1 96.0

9 4.8 53.9 34.7 0.7 0.0 0.0 0.5 0.0 0.0 0.0 0.0 15.2 60.8 22.2 9.8 0.4 109.6

10 16.2 41.2 871.2 0.6 0.0 0.0 0.7 16.2 60.2 29.1 2.5 473.1 96.9 33.8 31.2 6.3 750.7

11 21.3 46.3 919.3 0.6 0.0 0.0 0.5 67.0 238.9 115.6 11.0 2050.3 231.1 65.9 57.5 26.5 2865.0

12 24.9 49.6 1136.1 0.4 0.0 0.0 0.6 221.0 787.7 381.0 36.2 6735.9 621.1 191.0 163.3 86.5 9224.7

13 23.4 48.5 790.7 0.4 0.0 0.0 0.5 91.3 325.4 157.4 15.0 2790.1 291.0 91.0 74.8 36.0 3873.0

14 22.8 48.3 946.1 0.4 0.0 0.0 0.6 48.5 172.8 83.6 8.0 1487.8 182.8 61.7 56.7 19.3 2122.3

15 19.1 47.6 320.0 0.5 0.0 0.0 0.5 23.7 87.9 42.5 3.6 686.7 115.2 45.2 34.5 9.0 1049.3

16 22.1 53.6 397.9 0.8 0.0 0.0 0.5 45.3 161.7 78.2 7.4 1394.8 176.6 64.8 47.7 18.1 1995.9

17 19.8 53.6 281.9 0.8 0.0 0.0 0.5 26.4 98.0 47.4 4.0 768.7 123.6 48.0 29.2 10.0 1156.7

18 15.0 50.6 65.8 0.7 0.0 0.0 0.6 7.3 28.1 13.6 1.0 207.5 76.4 30.8 16.3 2.8 385.1

19 15.5 54.6 50.9 0.8 0.0 0.0 0.1 4.1 15.2 7.3 0.6 116.6 9.7 17.5 14.3 1.5 187.6

20 19.2 58.1 61.5 0.6 0.0 0.0 0.1 10.0 37.2 18.0 1.5 285.8 23.8 15.7 14.9 3.6 411.2

21 19.2 56.7 70.6 0.4 0.0 0.0 0.1 9.1 33.8 16.4 1.4 259.8 21.7 15.6 15.7 3.3 377.2

22 19.0 57.4 67.6 0.4 0.0 0.0 0.0 7.3 27.0 13.1 1.1 207.8 17.3 12.8 7.2 2.6 296.7

23 17.1 55.7 32.7 0.2 0.0 0.0 0.0 3.5 12.8 6.2 0.5 98.7 8.2 7.5 4.6 1.3 143.7

24 14.8 54.6 139.3 0.1 0.0 0.0 0.0 3.4 13.0 6.3 0.5 89.3 7.4 5.6 2.7 1.1 129.3

24-Hour Average 264.9 0.4 0.0 0.0 0.4 24.3 87.5 42.3 3.9 737.3 90.5 32.4 25.1 9.6 1053.7

% Contribution a- 0.0% 0.0% 0.0% 0.0% 2.3% 8.3% 4.0% 0.4% 70.0% 8.6% 3.1% 2.4% 0.9% 100%

2008 Source Contribution (μg/m3) 17.5 0.1 0.0 0.0 0.1 5.7 20.5 9.9 0.9 173.1 21.2 7.6 5.9 2.2 264.9

a. Percentage Contribution is based on source only, without considering the background concentrations. Shaded Area = High Wind Hours
32

Figure 3-1. Distance-Weighted Emissions for Pinal County Housing (PCH) 1/1/2008 High Wind Design Day

0

5

10

15

20

25

0

250

500

750

1000

1250

1500

1750

2000

2250

2500

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

Wind Speed (MPH)

PM10 Concentration (μg/m3

)

Hour

Unpaved Trails

Private Dirt Roads

Public Dirt Roads

Unpaved Ag Roads

Agriculture

Developed Urban Lands

Developed Rural Lands

Desert Shrubland

Cleared Area

Unpaved Parking Lots

Construction

Point Sources

Paved Road

Background

Monitor Observation

Wind Speed
33

Table 3-2. Distance-Weighted Emissions (lbs/mile) for the High Wind Modeling Domain at Cowtown (CWT) on 4/27/2008 Design Day Hour Wind Speed 

(mph)

Wind Direction 

(degrees)

Monitor 

Observation

Point Sources

Paved Road

ConstructionCleared Area

Unpaved 

Parking Lots

County Desert 

Shrubland

Tribal Desert 

Shrubland

Developed 

Rural Lands

Developed 

Urban Lands

Other

CAFOs

County 

Agriculture

Tribal 

Agriculture

Unpaved Ag 

Roads

Public Dirt 

Roads

Private Dirt 

Roads

Unpaved Trails

Tribal Unpaved 

Roads

Unpaved Test 

Tracks

Total

1 6.0 332 68.3 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.1 0.1 0.0 0.0 0.0 0.5

2 0.7 321 73.0 0.2 0.7 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 4.3 0.0 0.0 0.0 0.0 0.9 0.0 0.0 0.0 6.2

3 5.8 315 88.1 0.0 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 8.7 0.0 0.0 0.0 0.2 0.4 0.0 0.0 0.0 9.9

4 3.8 84 59.7 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.0 0.0 0.7 0.0 0.0 0.0 0.0 1.3

5 2.1 26 92.3 5.5 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.0 0.0 0.0 1.4 0.0 0.0 0.0 7.6

6 2.4 157 492.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 110.8 0.0 0.5 0.0 18.7 0.0 0.0 7.1 0.0 137.1

7 1.6 229 326.4 0.0 0.1 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 329.6 1.9 6.3 11.4 30.0 0.0 0.0 23.8 0.0 403.2

8 2.1 12 222.0 0.2 0.9 0.0 0.0 0.4 0.0 0.0 0.0 0.0 0.0 0.0 2.0 0.0 33.0 0.2 8.7 0.2 0.0 0.0 45.6

9 10.7 33 372.4 0.2 1.3 0.0 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.0 2.2 0.0 31.0 26.7 9.6 0.5 0.0 0.0 71.6

10 19.6 53 886.8 0.2 0.4 257.4 27.4 0.3 828.5 163.4 83.2 1.5 0.0 0.0 1136.0 0.0 179.7 62.8 109.0 14.6 32.3 32.3 2929.0

11 17.3 44 107.7 0.2 0.6 73.1 7.8 0.2 235.2 46.4 23.6 0.4 0.0 0.0 324.1 0.0 73.0 37.3 32.7 4.4 9.2 9.2 877.4

12 15.4 43 122.3 0.2 0.6 31.0 3.3 0.3 99.8 19.7 10.0 0.2 0.0 0.0 138.9 0.0 49.4 39.3 18.0 2.1 3.9 3.9 420.6

13 17.4 37 72.0 0.2 0.8 68.2 7.3 0.2 219.6 43.3 22.0 0.4 0.0 0.0 302.9 0.0 67.5 37.4 41.4 4.1 8.6 8.6 832.4

14 14.5 44 38.4 0.2 0.7 22.7 2.5 0.3 79.8 15.7 8.0 0.1 0.0 0.0 106.4 0.0 43.0 36.2 15.3 1.6 2.8 2.8 338.1

15 15.8 50 36.4 0.2 0.7 27.3 2.9 0.2 87.7 17.3 8.8 0.2 0.0 0.0 121.7 0.0 44.8 38.8 16.7 2.0 3.4 3.4 376.0

16 14.9 51 23.1 0.2 1.4 18.4 2.1 0.2 64.8 12.8 6.5 0.1 0.0 0.0 86.5 0.0 39.9 36.8 13.0 1.5 2.3 2.3 288.7

17 11.9 59 69.7 0.2 0.9 0.0 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.7 0.0 29.7 32.9 5.2 0.6 0.0 0.0 70.4

18 9.0 69 101.2 0.0 0.7 0.0 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 25.0 33.7 4.4 0.2 0.9 0.0 66.3

19 5.2 41 230.1 0.0 0.7 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.0 0.0 12.8 3.4 0.0 0.0 0.0 17.5

20 4.0 8 72.9 0.2 0.5 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.0 0.0 0.2 10.3 0.0 0.0 0.0 11.7

21 2.9 37 79.7 0.2 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.0 0.0 5.4 10.5 0.0 0.0 0.0 17.2

22 3.0 35 42.6 0.2 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.0 0.0 4.7 2.7 0.0 0.0 0.0 8.6

23 3.8 112 232.5 0.2 1.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.0 0.0 4.7 1.9 0.0 0.1 0.0 8.9

24 3.2 9 127.5 0.2 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.0 0.0 0.0 1.0 0.0 0.0 0.0 2.0

24-Hour Average 168.3 0.3 0.6 20.8 2.2 0.1 67.3 13.3 6.8 0.1 0.0 18.9 92.9 0.3 26.1 19.1 12.8 1.3 3.9 2.6 289.5

% Contributiona- 0.1% 0.2% 7.2% 0.8% 0.1% 23.3% 4.6% 2.3% 0.0% 0.0% 6.5% 32.1% 0.1% 9.0% 6.6% 4.4% 0.5% 1.4% 0.9% 100%

2008 Source 

Contribution (μg/m3)

17.5 0.2 0.3 10.8 1.2 0.1 35.1 6.9 3.5 0.1 0.0 9.8 48.4 0.1 13.6 10.0 6.6 0.7 2.0 1.4 168.3

a. Percentage Contribution is based on source only, without considering the background concentrations. Shaded Area = High Wind Hours
34

Figure 3-2. Distance-Weighted Emissions for Cowtown (CWT) 4/27/2008 High Wind Design Day

0

5

10

15

20

0

200

400

600

800

1000

1200

1400

1600

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

Wind Speed (MPH)

PM10 Concentration (μg/m3

)

Hour

Unpaved Test Tracks

Tribal Unpaved Roads

Unpaved Trails

Private Dirt Roads

Public Dirt Roads

Unpaved Ag Roads

Tribal Agriculture

County Agriculture

CAFOs

Other

Developed Urban Lands

Developed Rural Lands

Tribal Desert Shrubland

County Desert Shrubland

Unpaved Parking Lots

Cleared Area

Construction

Paved Road

Point Sources

Background

Monitor Observation

Wind Speed
35

Table 3-3. Distance-Weighted Emissions (lbs/mile) for the High Wind Modeling Domain at Maricopa on 10/27/2008 Design Day

Hour

Wind 

Speed 

(mph)

Wind 

Direction 

(degrees)

Monitor 

Obs- ervation

Paved 

Road

Con- struction

CAFOs

Cleared 

Area

Unpaved 

Parking 

Lots

Desert 

Shrubland

Developed 

Rural 

Lands

Developed 

Urban 

Lands

Other

County 

Agri- culture

Tribal Agri- culture

Unpaved 

Ag Roads

Public Dirt 

Roads

Private 

Dirt Roads

Unpaved 

Trails

Tribal 

Unpaved 

Roads

Total

1 4.5 160.0 239.9 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7 0.4 0.0 0.0 1.4

2 2.4 106.0 143.5 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.6 0.0 0.0 1.2

3 1.6 6.0 70.3 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.7

4 1.6 348.0 73.8 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5

5 2.9 290.0 98.7 0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.0 0.0 1.1

6 2.4 241.0 91.8 1.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.8 3.1

7 1.6 215.0 129.8 2.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.0 0.0 0.0 0.0 0.0 21.8 26.1

8 6.9 82.0 160.4 4.6 119.9 0.0 0.0 1.9 0.0 0.0 0.0 0.0 0.8 0.0 11.0 2.9 1.3 0.1 0.0 142.5

9 16.0 84.0 326.2 4.5 316.7 0.0 57.0 1.9 32.7 24.0 23.8 3.2 72.6 0.0 17.9 3.7 7.4 0.4 0.0 565.6

10 20.7 85.0 852.9 4.4 1455.1 0.0 345.9 2.2 190.6 139.7 155.0 18.8 428.8 0.0 57.8 10.7 40.1 2.0 0.0 2851.1

11 23.6 81.0 496.5 4.2 1356.0 0.0 319.1 2.1 175.9 128.9 143.0 17.4 395.7 0.0 54.8 9.6 36.1 1.9 0.0 2644.6

12 21.0 82.0 293.2 4.5 791.4 0.0 173.3 2.3 95.5 70.0 77.7 9.4 215.3 0.0 34.8 7.1 21.8 1.0 0.0 1504.0

13 21.9 79.0 176.0 4.9 584.0 0.0 120.0 2.1 66.1 48.4 53.8 6.5 149.3 0.0 27.6 5.4 15.0 0.7 0.0 1083.9

14 21.6 74.0 141.9 4.5 524.1 0.0 93.3 2.2 51.4 37.7 41.8 5.1 116.3 0.1 22.2 4.0 11.5 0.6 0.0 914.7

15 19.9 72.0 84.8 4.5 335.0 0.0 45.5 1.9 26.1 19.2 19.0 2.5 58.2 0.1 14.9 0.9 5.7 0.3 0.0 533.9

16 17.6 71.0 76.6 4.5 257.7 0.0 24.6 1.9 14.1 10.4 10.3 1.4 31.9 0.1 12.0 0.5 3.4 0.1 0.0 372.9

17 16.0 72.0 68.6 5.3 201.8 0.0 9.5 1.8 5.5 4.0 4.0 0.5 12.8 0.1 10.3 0.2 1.9 0.1 0.0 257.7

18 10.8 62.0 60.4 4.0 0.0 0.0 0.0 1.7 0.0 0.0 0.7 0.1 0.6 0.3 6.7 0.0 1.0 0.0 1.7 16.7

19 8.8 61.0 56.2 4.1 0.0 0.0 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8 0.0 0.4 5.6

20 9.1 68.0 45.1 2.7 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7 0.0 0.1 3.7

21 11.9 70.0 36.1 2.4 0.0 0.0 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.0 0.1 3.2

22 12.2 80.0 30.8 2.7 6.4 0.0 1.8 0.1 1.1 0.8 0.7 0.1 2.3 0.0 0.2 0.5 0.6 0.0 0.0 17.4

23 11.3 82.0 33.2 1.7 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.0 0.0 2.6

24 11.1 78.0 38.7 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.1 0.0 0.0 1.5

24-Hour Average 159.4 2.9 247.8 0.0 49.6 1.0 27.5 20.1 22.1 2.7 61.9 0.1 11.3 2.0 6.2 0.3 1.1 456.5

% Contribution a- 0.6% 54.3% 0.0% 10.9% 0.2% 6.0% 4.4% 4.8% 0.6% 13.6% 0.0% 2.5% 0.4% 1.4% 0.1% 0.2% 100%

2008 Source 

Contribution (μg/m3)

17.5 0.9 77.0 0.0 15.4 0.3 8.5 6.3 6.9 0.8 19.2 0.0 3.5 0.6 1.9 0.1 0.3 159.4

a. Percentage Contribution is based on source only, without considering the background concentrations. Shaded Area = High Wind Hours
36

Figure 3-3. Distance-Weighted Emissions for Maricopa 10/27/2008 High Wind Design Day

0

5

10

15

20

25

0

100

200

300

400

500

600

700

800

900

1000

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

Wind Speed (MPH)

PM10 Concentration (μg/m3

)

Hour

Tribal Unpaved Roads

Unpaved Trails

Private Dirt Roads

Public Dirt Roads

Unpaved Ag Roads

Tribal Agriculture

County Agriculture

Other

Developed Urban Lands

Developed Rural Lands

Desert Shrubland

Unpaved Parking Lots

Cleared Area

CAFOs

Construction

Paved Road

Background

Monitor Observation

Wind Speed
37

Table 3-4. Distance-Weighted Emissions (lbs/mile) for the High Wind Modeling Domain at Stanfield (STF) on 11/21/2008 

Design Day

Hour

Wind 

Speed 

(mph)

Wind 

Direction 

(degrees)

Monitor 

Obs- ervation

Paved 

Road 

Con- struction

CAFOs 

Dairy

Cleared 

Area

Unpaved 

Parking 

Lots

Desert 

Shrubland

Developed 

Rural 

Lands

Agri- culture

Unpaved 

Ag Roads

Public Dirt 

Roads

Private 

Dirt Roads

Unpaved 

Trails

Total

1 3.5 119.2 112.4 0.1 0.0 2.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.5 0.0 3.8

2 3.0 161.6 59.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.8 0.2 0.0 2.0

3 3.4 117.3 157.4 0.1 0.0 4.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9 1.2 0.0 6.5

4 3.7 125.4 158.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0

5 3.2 274.2 102.3 0.2 0.0 30.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.3 0.0 31.3

6 3.4 240.9 234.2 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.0 2.2 0.0 4.8

7 13.2 85.5 357.4 1.1 0.0 47.2 0.0 8.2 0.4 60.1 12.3 239.2 58.9 24.3 10.9 7.0 469.6

8 14.7 81.9 326.6 1.6 0.0 50.3 0.0 9.3 0.4 68.2 13.9 270.6 63.4 33.0 10.1 8.0 528.7

9 16.3 82.2 584.6 1.5 0.0 121.2 0.0 33.2 0.4 233.3 47.7 987.2 107.6 37.7 31.6 25.8 1627.2

10 16.0 81.1 429.2 1.0 0.0 62.6 0.0 13.1 0.5 91.9 18.8 394.8 71.1 31.9 18.2 11.8 715.7

11 16.0 80.2 334.3 1.0 0.0 35.1 0.0 11.3 0.4 79.3 16.2 342.3 63.7 28.2 14.2 10.5 602.3

12 14.6 80.4 186.1 1.1 0.0 32.8 0.0 4.8 0.5 34.8 7.1 143.3 51.1 30.4 11.2 5.5 322.5

13 12.2 79.2 93.9 1.2 0.0 7.5 0.0 2.1 0.4 15.4 3.2 68.5 46.9 26.8 7.0 3.7 182.8

14 11.1 78.5 65.1 1.2 0.0 1.7 0.0 0.0 0.5 0.0 0.0 9.4 43.8 29.9 8.6 2.3 97.3

15 10.2 75.3 64.8 0.6 0.0 1.7 0.0 0.0 0.5 0.0 0.0 9.1 44.8 38.0 6.8 2.4 103.8

16 8.2 77.2 65.2 1.8 0.0 2.3 0.0 0.0 0.5 0.0 0.0 8.8 43.9 38.8 7.3 2.3 105.6

17 5.9 74.7 87.1 1.3 0.0 2.8 0.0 0.0 0.4 0.0 0.0 9.5 44.8 40.3 5.3 2.4 106.8

18 4.0 73.8 104.6 1.3 0.0 4.0 0.0 0.0 0.4 0.0 0.0 9.7 45.4 36.3 4.4 2.5 104.0

19 5.3 75.1 88.3 0.7 0.0 5.1 0.0 0.0 0.1 0.0 0.0 0.0 0.0 20.6 4.6 0.0 31.1

20 4.6 86.2 56.1 1.0 0.0 44.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 11.3 3.5 0.0 60.1

21 2.3 158.4 98.3 0.1 0.0 0.0 0.3 0.0 0.1 0.0 0.0 0.0 0.0 7.5 0.8 0.0 8.8

22 1.9 230.2 249.6 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.9 0.9 0.0 3.3

23 2.5 270.1 171.6 0.6 0.0 9.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.0 10.4

24 2.1 291.4 99.5 0.0 0.0 9.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 9.5

24-Hour Average 178.6 0.8 0.0 19.8 0.0 3.4 0.2 24.3 5.0 103.8 28.6 18.5 6.3 3.5 214.1

% Contribution a- 0.4% 0.0% 9.2% 0.0% 1.6% 0.1% 11.3% 2.3% 48.5% 13.3% 8.6% 2.9% 1.6% 100%

2008 Source Contribution 

(μg/m3)

17.5 0.6 0.0 14.9 0.0 2.6 0.2 18.3 3.7 78.1 21.5 13.9 4.7 2.6 178.6

a. Percentage Contribution is based on source only, without considering the background concentrations. Shaded Area = High Wind Hours
38

Figure 3-4. Distance-Weighted Emissions for Stanfield (STF) 11/21/2008 High Wind Design Day

0

2

4

6

8

10

12

14

16

18

0

150

300

450

600

750

900

1050

1200

1350

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

Wind Speed (MPH)

PM10 Concentration (μg/m3

)

Hour

Unpaved Trails

Private Dirt Roads

Public Dirt Roads

Unpaved Ag Roads

Agriculture

Developed Rural Lands

Desert Shrubland

Unpaved Parking Lots

Cleared Area

Dairy

CAFOs

Construction

Paved Road

Background

Monitor Observation

Wind Speed
39

Figure 3-5. 2008 High Wind Design Day Source Contributions

Pinal County Housing Cowtown

Maricopa Stanfield

Background

17.5 μg/m3

6.6%

Cleared Area

5.7 μg/m3

2.2%

Desert 

Shrubland

20.5 μg/m3

7.8%

Developed 

Rural Lands

9.9 μg/m3

3.8%

Agriculture

173.1 μg/m3

65.4%

Unpaved Ag 

Roads

21.2 μg/m3

8.0%

Public Dirt 

Roads

7.6 μg/m3

2.9%

Private Dirt 

Roads

5.9 μg/m3

2.2%

Remaining 

Sources

3.3 μg/m3

1.3%

Background

17.5 μg/m3

10.4%

Construction

10.8 μg/m3

6.4%

County 

Desert 

Shrubland

35.1 μg/m3

20.8%

Tribal Desert 

Shrubland

6.9 μg/m3

4.1%

CAFOs 

9.8 μg/m3

5.8% County 

Agriculture

48.4 μg/m3

28.7%

Unpaved Ag 

Roads

13.6 μg/m3

8.1%

Public Dirt 

Roads

10.0 μg/m3

5.9%

Private Dirt 

Roads

6.6 μg/m3

4.0%

Remaining 

Sources

9.5 μg/m3

5.7%

Background

17.5 μg/m3

11.0%

Construction

77.0 μg/m3

48.3%

Cleared Area

15.4 μg/m3

9.7%

Desert 

Shrubland

8.5 μg/m3

5.4%

Developed 

Rural Lands

6.3 μg/m3

3.9%

Developed 

Urban Lands

6.9 μg/m3

4.3%

County 

Agriculture

19.2 μg/m3

12.1%

Remaining 

Sources

8.6 μg/m3

5.4%

Background

17.5 μg/m3

9.8%

CAFOs 

14.9 μg/m3

8.3%

Desert 

Shrubland

18.3 μg/m3

10.2%

Agriculture

78.1 μg/m3

43.7%

Unpaved Ag 

Roads

21.5 μg/m3

12.0%

Public Dirt 

Roads

13.9 μg/m3

7.8%

Private Dirt 

Roads

4.7 μg/m3

2.6% Remaining 

Sources

9.7 μg/m3

5.4%
40

Table 3-5. Projected 2018 Distance-Weighted Emissions (lbs/mile) for the High Wind Modeling Domain at PCH on 1/1/2008 Design 

Day

Hour

Wind Speed 

(mph)

Wind 

Direction 

(degrees)

2008 Mon- itor Obs- ervation

Paved Road 

Point 

Sources

Con- struction

Unpaved 

Parking Lots

Cleared 

Area

Desert 

Shrubland

Developed 

Rural Lands

Developed 

Urban 

Lands

Agri-culture

Unpaved Ag 

Roads

Public Dirt 

Roads

Private Dirt 

Roads

Unpaved 

Trails

Total

1 1.6 303.8 28.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.1 0.3 0.0 1.4

2 1.5 318.0 21.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 2.4 1.7 0.0 4.2

3 1.9 335.4 22.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.4 1.4 0.0 2.9

4 2.5 333.7 24.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.7 0.0 0.0 1.7

5 5.9 352.2 16.4 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.6 1.4 0.0 3.2

6 3.1 299.6 19.1 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 5.7 3.1 0.0 9.0

7 3.9 339.3 16.2 0.2 0.0 0.0 1.6 0.0 0.0 0.0 0.0 12.7 46.4 15.3 11.9 0.9 89.1

8 5.7 5.0 22.7 1.9 0.0 0.0 0.9 0.0 0.0 0.0 0.0 14.0 61.6 11.9 6.1 0.1 96.4

9 4.8 53.9 34.7 0.7 0.0 0.0 0.5 0.0 0.0 0.0 0.0 15.2 61.2 20.1 11.5 0.4 109.5

10 16.2 41.2 871.2 0.7 0.0 1.5 0.7 16.2 60.2 29.1 2.5 473.0 97.2 28.0 34.8 6.3 750.3

11 21.3 46.3 919.3 0.8 0.0 0.0 0.5 67.0 238.9 115.6 11.0 2050.2 231.4 39.6 59.9 26.5 2841.4

12 24.9 49.6 1136.1 0.5 0.0 0.0 0.6 221.0 787.7 381.0 36.2 6735.9 621.4 91.8 166.8 86.5 9129.3

13 23.4 48.5 790.7 0.5 0.0 0.0 0.5 91.3 325.4 157.4 15.0 2790.1 291.4 48.9 77.5 36.0 3834.0

14 22.8 48.3 946.1 0.5 0.0 0.0 0.6 48.5 172.8 83.6 8.0 1487.7 183.2 37.8 61.0 19.3 2103.0

15 19.1 47.6 320.0 0.5 0.0 0.0 0.5 23.7 87.9 42.5 3.6 686.7 115.5 32.5 37.9 9.0 1040.4

16 22.1 53.6 397.9 0.8 0.0 0.0 0.5 45.3 161.7 78.2 7.4 1394.7 177.0 42.9 50.8 18.1 1977.4

17 19.8 53.6 281.9 0.9 0.0 0.0 0.5 26.4 98.0 47.4 4.0 768.6 124.0 36.3 31.5 10.0 1147.6

18 15.0 50.6 65.8 0.8 0.0 0.0 0.6 7.3 28.1 13.6 1.0 207.5 76.7 27.0 18.4 2.7 383.7

19 15.5 54.6 50.9 0.8 0.0 0.0 0.1 4.1 15.2 7.3 0.6 116.6 9.7 15.6 16.2 1.5 187.7

20 19.2 58.1 61.5 0.6 0.0 0.0 0.1 10.0 37.2 18.0 1.5 285.8 23.8 11.9 16.4 3.6 408.9

21 19.2 56.7 70.6 0.4 0.0 0.0 0.1 9.1 33.8 16.4 1.4 259.8 21.7 12.3 17.4 3.3 375.7

22 19.0 57.4 67.6 0.4 0.0 0.0 0.0 7.3 27.0 13.1 1.1 207.8 17.3 10.2 7.6 2.6 294.5

23 17.1 55.7 32.7 0.2 0.0 0.0 0.0 3.5 12.8 6.2 0.5 98.7 8.2 6.1 5.0 1.3 142.7

24 14.8 54.6 139.3 0.1 0.0 0.0 0.0 3.4 13.0 6.3 0.5 89.3 7.4 4.1 2.9 1.1 128.1

24-Hour Average 264.9 0.5 0.0 0.1 0.4 24.3 87.5 42.3 3.9 737.3 90.6 21.1 26.7 9.5 1044.3

% Contribution a- 0.0% 0.0% 0.0% 0.0% 2.3% 8.4% 4.1% 0.4% 70.6% 8.7% 2.0% 2.6% 0.9% 100%

2018 Source 

Contribution (μg/m3)

17.5 0.1 0.0 0.0 0.1 5.7 20.5 9.9 0.9 173.1 21.3 5.0 6.3 2.2 262.7

a. Percentage Contribution is based on source only, without considering the background concentrations. Shaded Area = High Wind Hours
41

Figure 3-6. Forecast of 2018 Distance-Weighted Emissions for Pinal County Housing (PCH) 1/1/2008 High Wind Design Day

0

5

10

15

20

25

0

250

500

750

1000

1250

1500

1750

2000

2250

2500

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

Wind Speed (MPH)

PM10 Concentration (μg/m3

)

Hour

Unpaved Trails

Private Dirt Roads

Public Dirt Roads

Unpaved Ag Roads

Agriculture

Developed Urban Lands

Developed Rural Lands

Desert Shrubland

Cleared Area

Unpaved Parking Lots

Construction

Point Sources

Paved Road

Background

Monitor Observation

Wind Speed
42

Table 3-6. Projected 2018 Distance-Weighted Emissions (lbs/mile) for the High Wind Modeling Domain at CWT on 4/27/2008 Design Day Hour Wind Speed (mph) Wind Direction (degrees) 2008 Mon-itor Obs-ervation Point Sources Paved Road Con-struction Cleared Area Unpaved Parking Lots County Desert Shrubland Tribal Desert Shrubland Developed Rural Lands Developed Urban Lands Other CAFOs County Agri- culture Tribal Agri- culture Unpaved Ag Roads Public Dirt Roads

Private Dirt 

Roads

Unpaved Trails

Tribal Unpaved 

Roads

Unpaved Test 

Tracks

Total

1 6.0 332 68.3 0.3 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.1 0.2 0.0 0.0 0.0 1.0

2 0.7 321 73.0 1.0 1.1 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 3.2

3 5.8 315 88.1 0.9 0.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.5 0.0 0.0 0.0 2.6

4 3.8 84 59.7 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.0 0.0 0.8 0.0 0.0 0.0 0.0 1.5

5 2.1 26 92.3 0.2 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.0 0.0 0.0 1.6 0.0 0.0 0.0 2.7

6 2.4 157 492.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.0 21.8 0.0 0.0 8.2 0.0 30.7

7 1.6 229 326.4 0.3 0.3 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 329.6 1.9 6.3 11.4 35.1 0.0 0.0 25.6 0.0 410.6

8 2.1 12 222.0 1.4 1.5 0.0 0.0 0.4 0.0 0.0 0.0 0.0 0.0 0.0 2.0 0.0 33.0 0.2 10.2 0.2 0.0 0.0 49.0

9 10.7 33 372.4 1.7 1.8 0.0 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.0 2.2 0.0 31.0 31.2 11.2 0.5 0.0 0.0 79.8

10 19.6 53 886.8 0.6 0.6 165.5 27.4 0.3 828.5 163.4 83.2 5.8 0.1 0.0 1136.0 0.0 179.7 68.6 95.5 14.6 32.3 32.3 2834.5

11 17.3 44 107.7 0.8 0.9 47.0 7.8 0.2 235.2 46.4 23.6 1.6 0.0 0.0 324.1 0.0 73.0 42.2 29.3 4.4 9.2 9.2 855.1

12 15.4 43 122.3 0.9 0.9 19.9 3.3 0.3 99.8 19.7 10.0 0.7 0.0 0.0 138.9 0.0 49.4 45.3 17.2 2.1 3.9 3.9 416.3

13 17.4 37 72.0 1.1 1.2 43.9 7.3 0.2 219.6 43.3 22.0 1.5 0.0 0.0 302.9 0.0 67.5 42.4 39.8 4.1 8.6 8.6 814.0

14 14.5 44 38.4 0.9 1.0 14.6 2.5 0.3 79.8 15.7 8.0 0.5 0.0 0.0 106.4 0.0 43.0 41.9 15.1 1.6 2.8 2.8 337.0

15 15.8 50 36.4 1.0 1.0 17.5 2.9 0.2 87.7 17.3 8.8 0.6 0.0 0.0 121.7 0.0 44.8 44.8 16.1 2.0 3.4 3.4 373.5

16 14.9 51 23.1 1.8 1.9 11.8 2.1 0.2 64.8 12.8 6.5 0.4 0.0 0.0 86.5 0.0 39.9 42.6 13.0 1.5 2.3 2.3 290.4

17 11.9 59 69.7 1.1 1.3 0.0 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.7 0.0 29.7 38.5 6.1 0.6 0.0 0.0 78.2

18 9.0 69 101.2 1.2 1.3 0.0 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 25.0 39.4 5.1 0.2 1.0 0.0 74.5

19 5.2 41 230.1 0.9 1.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.0 0.0 14.9 4.0 0.0 0.0 0.0 21.5

20 4.0 8 72.9 0.8 0.9 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.0 0.0 0.2 12.0 0.0 0.0 0.0 14.4

21 2.9 37 79.7 0.7 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.0 0.0 6.3 12.2 0.0 0.0 0.0 20.7

22 3.0 35 42.6 0.7 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.0 0.0 5.5 3.2 0.0 0.0 0.0 10.7

23 3.8 112 232.5 2.2 2.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.0 0.0 5.5 2.3 0.0 0.1 0.0 12.9

24 3.2 9 127.5 0.4 0.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.0 0.0 0.0 1.2 0.0 0.0 0.0 2.6

24-Hour Average 168.3 0.9 0.9 13.3 2.2 0.1 67.3 13.3 6.8 0.5 0.0 13.7 92.9 0.3 26.1 22.0 12.4 1.3 4.1 2.6 280.7

% Contribution a- 0.3% 0.3% 4.8% 0.8% 0.1% 24.0% 4.7% 2.4% 0.2% 0.0% 4.9% 33.1% 0.1% 9.3% 7.8% 4.4% 0.5% 1.4% 0.9% 100%

2018 Source 

Contribution (μg/m3)

17.5 0.5 0.5 7.0 1.2 0.1 35.1 6.9 3.5 0.2 0.0 7.2 48.4 0.1 13.6 11.5 6.4 0.7 2.1 1.4 163.7

a. Percentage Contribution is based on source only, without considering the background concentrations. Shaded Area = High Wind Hours
43

Figure 3-7. Forecast of 2018 Distance-Weighted Emissions for Cowtown (CWT) 4/27/2008 High Wind Design Day

0

5

10

15

20

0

200

400

600

800

1000

1200

1400

1600

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

Wind Speed (MPH)

PM10 Concentration (μg/m3

)

Hour

Unpaved Test Tracks

Tribal Unpaved Roads

Unpaved Trails

Private Dirt Roads

Public Dirt Roads

Unpaved Ag Roads

Tribal Agriculture

County Agriculture

CAFOs

Other

Developed Urban Lands

Developed Rural Lands

Tribal Desert Shrubland

County Desert Shrubland

Unpaved Parking Lots

Cleared Area

Construction

Paved Road

Point Sources

Background

Monitor Observation

Wind Speed
44

Table 3-7. Projected 2018 Distance-Weighted Emissions (lbs/mile) for the High Wind Modeling Domain at Maricopa on 10/27/2008 

Design Day

Hour

Wind Speed 

(mph)

Wind 

Direction 

(degrees)

2008 Mon- itor Obs- ervation

Paved Road 

Con- struction

CAFOs 

Cleared 

Area

Unpaved 

Parking Lots

Desert 

Shrubland

Developed 

Rural Lands

Developed 

Urban 

Lands

Other

County 

Agri-culture

Tribal Agri- culture

Unpaved Ag 

Roads

Public Dirt 

Roads

Private Dirt 

Roads

Unpaved 

Trails

Tribal 

Unpaved 

Roads

Total

1 4.5 160.0 239.9 0.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.4 0.0 0.0 1.3

2 2.4 106.0 143.5 0.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.6 0.0 0.0 1.3

3 1.6 6.0 70.3 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.1 0.7

4 1.6 348.0 73.8 0.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5

5 2.9 290.0 98.7 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.0 0.0 1.3

6 2.4 241.0 91.8 1.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.1 3.5

7 1.6 215.0 129.8 2.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.0 0.0 0.0 0.0 0.0 22.7 27.1

8 6.9 82.0 160.4 5.6 77.1 0.0 0.0 1.9 0.0 0.0 0.0 0.0 0.8 0.0 11.0 3.4 1.4 0.0 0.0 101.3

9 16.0 84.0 326.2 5.5 229.8 0.0 57.0 1.9 32.7 24.0 25.8 3.2 72.6 0.0 17.9 4.1 7.0 0.3 0.0 482.0

10 20.7 85.0 852.9 5.5 1102.1 0.0 345.9 2.2 190.6 139.7 168.2 18.8 428.8 0.0 57.8 11.2 36.9 2.0 0.0 2509.8

11 23.6 81.0 496.5 5.2 1025.5 0.0 319.1 2.1 175.9 128.9 155.2 17.4 395.7 0.0 54.8 10.1 33.0 1.8 0.0 2324.7

12 21.0 82.0 293.2 5.6 592.3 0.0 173.3 2.3 95.5 70.0 84.3 9.4 215.3 0.0 34.8 7.6 20.3 1.0 0.0 1311.8

13 21.9 79.0 176.0 6.1 433.3 0.0 120.0 2.1 66.1 48.4 58.4 6.5 149.3 0.0 27.6 5.9 14.0 0.7 0.0 938.5

14 21.6 74.0 141.9 5.6 381.9 0.0 93.3 2.2 51.4 37.7 45.4 5.1 116.3 0.1 22.2 4.3 10.5 0.5 0.0 776.6

15 19.9 72.0 84.8 5.7 236.3 0.0 45.5 1.9 26.1 19.2 20.6 2.5 58.2 0.1 14.9 0.9 5.3 0.2 0.0 437.5

16 17.6 71.0 76.6 5.5 177.0 0.0 24.6 1.9 14.1 10.4 11.2 1.4 31.9 0.1 11.9 0.5 3.4 0.1 0.0 294.0

17 16.0 72.0 68.6 6.5 134.1 0.0 9.5 1.8 5.5 4.0 4.3 0.5 12.8 0.1 10.3 0.2 1.7 0.1 0.0 191.4

18 10.8 62.0 60.4 4.6 0.0 0.0 0.0 1.7 0.0 0.0 0.0 0.0 0.6 0.3 6.5 0.0 0.9 0.0 1.7 16.3

19 8.8 61.0 56.2 5.1 0.0 0.0 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.4 6.8

20 9.1 68.0 45.1 3.3 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8 0.0 0.2 4.5

21 11.9 70.0 36.1 3.0 0.0 0.0 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.0 0.1 3.9

22 12.2 80.0 30.8 3.4 4.9 0.0 1.8 0.1 1.1 0.8 0.8 0.1 2.3 0.0 0.2 0.5 0.7 0.0 0.0 16.8

23 11.3 82.0 33.2 2.2 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.5 0.0 0.0 3.2

24 11.1 78.0 38.7 1.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.2 0.0 0.0 1.8

24-Hour Average 159.4 3.6 183.1 0.0 49.6 1.0 27.5 20.1 23.9 2.7 61.9 0.1 11.2 2.1 5.8 0.3 1.1 394.0

% Contribution a- 0.9% 46.5% 0.0% 12.6% 0.2% 7.0% 5.1% 6.1% 0.7% 15.7% 0.0% 2.9% 0.5% 1.5% 0.1% 0.3% 100%

2018 Source Contribution 

(μg/m3)

17.5 1.1 56.9 0.0 15.4 0.3 8.5 6.3 7.4 0.8 19.2 0.0 3.5 0.7 1.8 0.1 0.4 140.0

a. Percentage Contribution is based on source only, without considering the background concentrations. Shaded Area = High Wind Hours
45

Figure 3-8. Forecast of 2018 Distance-Weighted Emissions for Maricopa 10/27/2008 High Wind Design Day

0

5

10

15

20

25

0

100

200

300

400

500

600

700

800

900

1000

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

Wind Speed (MPH)

PM10 Concentration (μg/m3

)

Hour

Tribal Unpaved Roads

Unpaved Trails

Private Dirt Roads

Public Dirt Roads

Unpaved Ag Roads

Tribal Agriculture

County Agriculture

Other

Developed Urban Lands

Developed Rural Lands

Desert Shrubland

Unpaved Parking Lots

Cleared Area

CAFOs

Construction

Paved Road

Background

Monitor Observation

Wind Speed
46

Table 3-8. Projected 2018 Distance-Weighted Emissions (lbs/mile) for the High Wind Modeling Domain at STF on 11/21/2008 Design Day Hour Wind Speed mph (H=10m) Wind Direction (degrees) 2008 Monitor Observation Paved Road Construction CAFOs Dairy Cleared Area Unpaved Parking Lots Desert Shrubland Developed Rural Lands Agriculture Unpaved Ag Roads Public Dirt Roads Private Dirt Roads Unpaved Trails Total

1 3.5 119.2 112.4 0.1 0.0 4.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.1 0.6 0.0 6.6

2 3.0 161.6 59.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.2 0.3 0.0 2.4

3 3.4 117.3 157.4 0.0 0.0 9.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.5 0.0 12.1

4 3.7 125.4 158.4 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 1.1 0.0 0.0 1.3

5 3.2 274.2 102.3 0.2 0.0 31.0 2.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.0 33.9

6 3.4 240.9 234.2 0.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.3 2.6 0.0 5.8

7 13.2 85.5 357.4 1.1 0.0 66.2 4.4 0.4 8.2 60.1 12.3 239.2 58.9 27.9 11.7 7.0 497.4

8 14.7 81.9 326.6 1.8 0.6 68.6 5.0 0.4 9.3 68.2 13.9 270.6 63.4 38.0 10.5 8.0 558.3

9 16.3 82.2 584.6 1.6 0.6 125.7 18.8 0.4 33.2 233.3 47.7 987.2 107.6 42.0 32.2 25.8 1656.1

10 16.0 81.1 429.2 0.9 0.6 78.6 7.4 0.5 13.1 91.9 18.8 394.8 71.1 36.4 19.4 11.8 745.3

11 16.0 80.2 334.3 0.9 0.6 26.4 6.4 0.4 11.3 79.3 16.2 342.3 63.7 32.2 15.1 10.5 605.4

12 14.6 80.4 186.1 1.0 0.6 48.9 2.6 0.5 4.8 34.8 7.1 143.3 51.1 35.2 12.4 5.5 347.7

13 12.2 79.2 93.9 1.1 0.6 4.7 1.1 0.4 2.1 15.4 3.2 68.5 46.9 31.3 7.9 3.7 186.9

14 11.1 78.5 65.1 1.1 0.6 0.0 0.0 0.5 0.0 0.0 0.0 9.4 43.8 35.0 10.0 2.3 102.6

15 10.2 75.3 64.8 1.0 0.6 0.0 0.0 0.5 0.0 0.0 0.0 9.1 44.8 44.4 8.0 2.4 110.6

16 8.2 77.2 65.2 2.2 0.6 0.0 0.0 0.5 0.0 0.0 0.0 8.8 43.9 45.3 8.5 2.3 112.0

17 5.9 74.7 87.1 1.9 0.6 0.0 0.0 0.4 0.0 0.0 0.0 9.5 44.8 47.0 6.2 2.4 112.9

18 4.0 73.8 104.6 2.0 0.0 0.0 0.0 0.4 0.0 0.0 0.0 9.7 45.4 42.4 5.1 2.5 107.5

19 5.3 75.1 88.3 1.1 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 24.0 5.4 0.0 30.6

20 4.6 86.2 56.1 0.9 0.0 86.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 13.1 4.1 0.0 104.5

21 2.3 158.4 98.3 0.1 0.0 0.0 0.3 0.1 0.0 0.0 0.0 0.0 0.0 8.7 0.9 0.0 10.2

22 1.9 230.2 249.6 0.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.2 1.1 0.0 4.1

23 2.5 270.1 171.6 0.9 0.0 9.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.0 10.8

24 2.1 291.4 99.5 0.1 0.0 9.3 0.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 10.3

24-Hour Average 178.6 0.9 0.3 23.7 2.1 0.2 3.4 24.3 5.0 103.8 28.6 21.4 6.9 3.5 224.0

% Contribution a- 0.4% 0.1% 10.6% 0.9% 0.1% 1.5% 10.8% 2.2% 46.4% 12.7% 9.5% 3.1% 1.6% 100%

2018 Source Contribution (μg/m3) 17.5 0.7 0.2 17.8 1.5 0.2 2.6 18.3 3.7 78.1 21.5 16.1 5.2 2.6 186.0

a. Percentage Contribution is based on source only, without considering the background concentrations. Shaded Area = High Wind Hours
47

Figure 3-9. Forecast of 2018 Distance-Weighted Emissions for Stanfield (STF) 11/21/2008 High Wind Design Day

0

2

4

6

8

10

12

14

16

18

0

150

300

450

600

750

900

1050

1200

1350

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

Wind Speed (MPH)

PM10 Concentration (μg/m3

)

Hour

Unpaved Trails

Private Dirt Roads

Public Dirt Roads

Unpaved Ag Roads

Agriculture

Developed Rural Lands

Desert Shrubland

Unpaved Parking Lots

Cleared Area

Dairy

CAFOs

Construction

Paved Road

Background

Monitor Observation

Wind Speed
48

Figure 3-10. Projected 2018 High Wind Design Day Source Contributions

Pinal County Housing Cowtown

Maricopa Stanfield

Background

17.5 μg/m3

6.7%

Cleared Area

5.7 μg/m3

2.2%

Desert 

Shrubland

20.5 μg/m3

7.8%

Developed 

Rural Lands

9.9 μg/m3

3.8%

Agriculture

173.1 μg/m3

65.9%

Unpaved Ag 

Roads

21.3 μg/m3

8.1%

Public Dirt 

Roads

5.0 μg/m3

1.9%

Private Dirt 

Roads

6.3 μg/m3

2.4%

Remaining 

Sources

3.4 μg/m3

1.3%

Background

17.5 μg/m3

10.7%

Construction

7.0 μg/m3

4.2%

County 

Desert 

Shrubland

35.1 μg/m3

21.4%

Tribal Desert 

Shrubland

6.9 μg/m3

4.2%

CAFOs 

7.2 μg/m3

4.4% County 

Agriculture

48.4 μg/m3

29.5%

Unpaved Ag 

Roads

13.6 μg/m3

8.3%

Public Dirt 

Roads

11.5 μg/m3

7.0%

Private Dirt 

Roads

6.4 μg/m3

3.9%

Remaining 

Sources

10.3 μg/m3

6.3%

Background

17.5 μg/m3

12.5%

Construction

56.9 μg/m3

40.7%

Cleared Area

15.4 μg/m3

11.0%

Desert 

Shrubland

8.5 μg/m3

6.1%

Developed 

Rural Lands

6.3 μg/m3

4.5%

Developed 

Urban Lands

7.4 μg/m3

5.3%

County 

Agriculture

19.2 μg/m3

13.7%

Remaining 

Sources

8.7 μg/m3

6.2%

Background

17.5 μg/m3

9.4%

CAFOs 

17.8 μg/m3

9.6%

Desert 

Shrubland

18.3 μg/m3

9.8%

Agriculture

78.1 μg/m3

42.0%

Unpaved Ag 

Roads

21.5 μg/m3

11.5%

Public Dirt 

Roads

16.1 μg/m3

8.6%

Private Dirt 

Roads

5.2 μg/m3

2.8% Remaining 

Sources

11.5 μg/m3

6.2%
CI-1

Exhibit CI High Wind Design Day 

Example Calculation
CI-2

High Wind Design Day Sample Calculation

Assume calculation of the hourly windblown emissions from a 50 acre (202,343 m2) cotton field located 1.3 miles 

directly upwind of the Pinal County Housing (PCH) monitor during harvesting season for a single hour averaging 

22 mph wind speed. This is the fourth consecutive hour of high winds (i.e. >12mph) for this wind event and one 

hour following the maximum measured concentration for this wind event at the PCH monitor. The harvesting 

season is assumed to have fully disturbed soil, so use of Equation 1 on page 114 of Appendix B is appropriate 

(Note: For those lands determined to be partially disturbed, Equations 1 and 2 on pages 114 and 115 of Appendix 

B would be employed and the area utilized in each equation would be the product of the area of the parcel and 

the disturbed fraction and stable fraction of the land of interest, respectively).

Esj = FEFAdjustment × A × EFDisturbed bin × V′

where:

Esj = suspended PM10 in gram/sec for hour j,

FEFAdjustment = the emission adjustment factor for diminished particle supply (detailed in Appendix B, 

Exhibit BVII),

A = the area of each crop’s land parcel, in m2,

EFDisturbed,bin = the windblown dust emission factor developed for disturbed soil for that wind speed bin, 

g/m2-sec for hour j (detailed in Appendix B, Exhibit BV), and

V’ = vegetative cover for crop specific, presented in Appendix B, Table 3-48.

Table CI-1. Values used for Example Windblown Dust Calculation

Variable Value Units Source

FEFAdjustment 51 % Exhibit BVII, Table BVII-4

A 202,343 m2 Given in assumptions (area of the field)

EFDisturbed,bin 4.27E-04 g/m2-s Exhibit BV, Table BV-4

V' 0.7 unitless Appendix B, Table 3-48

Using the values presented in Table CI-1 and the equation above, we can calculate windblown emissions from 

the cotton field during this single hour of high wind as:

Esj = 0.51 × 202,343 m2 × 0.000427

g

m2 − s

× 0.7 = 30.8

g

s

× 3600

s

hr

÷ 453.6

g

lb = 244

lb

hr

The emissions produced within that hour are 245 lbs. This can then be modeled as monitor impacts by dividing 

by the straight-line distance to the monitor (1.3 miles). This results in a monitor impact of 188 lb/mile. 

If this impact was assumed to occur on the 2008 PCH high wind design day and only assumed to occur for this

one hour, we can normalize the field’s impact to the monitor by dividing the individual cotton field’s impact 

calculated above by the total emission impacts on the monitor for that day (25,288 lb/mile; calculated as the sum 

of the hourly total impacts presented in Section 3.3 of Appendix C, Table 3-1) multiplied by the non-background 

monitor 24-hour average (247.4 μg/m3)

28. This results in a 24-hr average impact from this single cotton field on 

the monitor of 1.8 μg/m3for the PCH design day.

 

28 247.4 μg/m3

is calculated as the design day concentration (264.9 μg/m3) minus the calculated non-anthropogenic background on 

high risk days (17.5 μg/m3, per Section 3.2 of Appendix C).