# Report No. SR2014

- 08

- 03



# Appendix C :

Pinal County PM 10



# Nonattainment Area Source

Apportionment Modeling for

2008 and 2018 Base

Scenario Design Days

Prepared for:



# Arizona Dept. of Environmental

Quality

August 201 4

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 PM 10 

# Nonattainment Area Source Apportionment

Modeling for 2008 and 2018 Base Scenario Design Days

prepared for:

Arizona Dept. of Environmental Quality

August 201 4

Principal authors:

Robert G. Dulla

Wei Liu

Sierra Research, Inc.

1801 J Street

Sacramento, CA 9581 1

(916) 444

- 6666

Earl Withycombe

Consultant

Revised December , 2015

Arizona Department of Environmental Quality

## i 

# Pinal County PM 10 

# 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

- Pro cessing 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 PM 10 

## Concentrations (μg/m 3 

## ) at

Cowtown (CWT) 10/30/2008 Design Day

................................ ................................ .. 14

Figure 2

- 3. Modeled vs Monitored Stagnation Day PM 10 

## Concentrations (μg/m 3 

## ) at

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

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

Figure 2

- 4. Modeled vs Monitored Stagnation Day PM 10 

## Concentrations (μg/m 3 

## ) 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/m 3 

## ) at Cowtown (CWT) 10/30/2008 Design Day

................................ ................. 21

Figure 2

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

(μg/m 3 

## ) at Pinal County Housing (PCH) 10/29/2008 Design Day

.............................. 23

Figure 2

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

(μg/m 3 

## ) at Stanfield (STF) 10/29/2008 Design Day

................................ .................... 25

Figure 2

- 9. Projected 2018 Stagnation Design Day Source Contributions

....................... 26

Figure 3

- 1. Distance

- Weigh ted 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

Ta ble 2

- 6. Particle Size Distributions Collected by Aerodynamic Particle Sizer

Spectrometer at Casa Grande Airport in July 2008

................................ ....................... 7

Ta ble 2

- 7. Particle Parameters Used for Modeling Non

- CAFO Source Categories

............ 7

Table 2

- 8. Stagnation Day Modeling Performance at Cowt own (CWT) on

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

(μg/m 3 

## )

................................ ................................ ................................ ......................... 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/m 3 

## )

................................ ................................ ................................ ......................... 15

Table 2

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

10/29/2008 Design Day, AERMOD Simulation of Monitored Conc entrations

(μg/m 3 

## )

................................ ................................ ................................ ......................... 17

Table 2

- 11. Projected 2018 Stagnation Day Modeling Performance at Cowtown

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

(μg/m 3 

## )

................................ ................................ ................................ ......................... 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/m 3 

## )

................................ ................................ ................................ 22

Table 2

- 13. Projected 2018 Stagnation Day Modeling Performance at Stanfield

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

(μg/m 3 

## )

................................ ................................ ................................ ......................... 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 De sign 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 Desig n Day

................................ ............... 37

Table 3

- 5. Projected 2018 Distance

- Weighted Emissions (lbs/mile) for the High

Wind Modeling Domain at PCH on 1/1/2008 De sign 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 C I

- 1

. Values used for Example Windblown Dust Calculation

............................ C I

- 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 PM 10 

## air quality impacts from arrays of

significa nt 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 PM 10 

## Nonattainment Area (Pinal County)

. From

prev ious 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 pur

poses. 1



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

Separate emission inventories ha d been prepared for the areas surrounding and impacting

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

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

require d 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 assessme nt 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 PM 10 

## 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 cen tral Arizona produce s 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 emissi ons sufficient to produce exceedances of PM 10 

## standards.

A ir 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 Res earch, December 2012.

## 2

an EPA

- approved modified weighted rollback approach for high wind conditions were

selected to estimate hourly PM 10 

## concentrations at monitoring stations produced by

emissions of area , point

, an d mobile sources located within specified modeling domains

surrounding the monitoring stations . Because the PM 10 

## ambient air quality standard

exceeded in Pinal County is d esigned to limit short

- term acute exposures and is measured

over 24

- hour averaging p eriods, the attainment demonstrations are required by EPA policy

to show how PM 10 

## concentrations would be reduced from levels recorded on exceedance

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

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

submittal 2



## .

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 with in 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) o n high w ind

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

upwind source area to the hourly monitored PM 10 

## contribution under assumption s of (1)

emission factor uniformity within “disturbed” and “undisturbed” states of surfac e 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 th e M aricopa Association of Government ’ s (M AG ) Five Percent

Plan. T hrough experience gained in the preparation of PM 10 

## S IPs, and in consultation with

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

well in quantifying discret e 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

weigh t ed emissions is equal to that source’s fractional contribution to the ho urly PM 10



## 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 source s ). Individual s ource contr ibutions , using this

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

emission s rates

.

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

attainment of the 24

- hour PM 10 

## standard at d esignated monitors on respective stagnat ion

and high wind design days

— both in overall terms or by individual area source

— can be

quantified. E valuation and selection of suites of control measures capable of demonstrating

attainment at all moni tors on all d esign days involve many diff erent factors and are the

subject of Appendix D of this SIP submittal 3



## .

2 

### “ Pinal County PM 10 

### Nonattainment Area Emissions Inventories for 2008 and 2018 Base Years and

Design Days ,” Sierra Research, prepared August 201 4 and revised October 2015.

3 

### “Pinal County PM 10 

### 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 PM 10 

## plan for control strategy e valuation and

attainment demonstration. Section 2 summarizes the development of an assessment

methodology addressing stagnation design day s, and Section 3 reviews the methodology

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

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

basis of PM 10 

## emission inventories

, 4 

## for comparison to hourly PM 10 

## concentrations

recorded a t 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 PM 10 

### Nonattainment Area Emissions Inventories for 2008 and 2018 Base Years and

Design Days ,” Sierra Research, prepared August 201 4 and revised October 2015

.

## 4 

# 2. STAGNATION DAY MODEL ING

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

demonstrations prepared for Maricopa County determined that AERMOD is the most

suitable model for evaluating hourly source con tributions to PM 10 

## exceedances recor ded at

Pinal County monitors on stagnation design days

. AERMOD is a steady

- state Gaus sian

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

type s. A dopted by EPA as a regulator y model on December 9, 2005, AERMOD contains

improved algorithms for addressing low wind speed (near

- calm conditions) and provi de s

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 Inventory 7



## – H ourly estimates of emissions were prepared using land

parcel data provided by A DEQ and P CAQCD, activity data collected through f ield

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

AERM ET to produce these input files.

- The on

- site met eorological data collected at the Cowtown, Pinal County

Housing

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

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

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

.

- Upper air met eorological data were derived from Tucson 2008 twice

- daily

sounding s by the National Weather Service (NWS)

.

- C loud cover meteorological data were obtained from the records of the Phoenix

NWS met eorological 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, Fed eral

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

, ” i bid

. 8 

### C loud cover data were obtained for both Casa Grande airport and Phoenix S ky H arbor 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 fro m 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 va riability in ground

surface elevation. 10

, 11 

## These parameters are functions of ground cover (land use)

and affect the concentration calculations

. The monthly average v alues of these

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

Cou nty Housing, and Stanfield monitoring site s and are listed below in Tables 2

- 1,

2

- 2

, and 2

- 3, respectively. Only data from October w ere used to repre sent the

stagnation design day conditions.

- The wind measurement height 12 

## 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 We a ther Observing System (AWOS III) station, and Ph oenix S ky H arbor 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 S ky H arbor 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 sh ow

there is less than 5% difference in term s 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

. E PA. AERMOD Implementation Guide, March 19, 2009.

12 

### Reported by PCAQCD to be 3 .3 meter s , 3.5 meter s, and 9.2 meter s at the PCH, Cowtown, and Stanfield

monitoring station s , respectively.

13 

### AERMOD Description of Model Formulation, Page 24, 4.1.1 Wind Speed P rofiling.

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

.

## 6

Table 2

- 1. AERMET Stage 3 Meteorological Pr ocessing 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

 AER MOD Particle Deposition Algorithm was activated to simulate the impacts of

particle deposition on calculated PM 10 

## concentrations

. Table 2

- 4 summarizes the

particle parameters f

or modeling the Concentrated Animal Feeding Operations

( CA FO s )

. 14 

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

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

West 43 rd 

## Avenue monitors in 2008 detailed in the MAG Five Perce nt Plan, as

listed in Table 2

- 5; and (2) t he particle size data collected by the Aerodynamic

Particle Sizer (APS) Spectrometer at Casa Grande Airport i n 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/m 3 

## ) 2.5 2.5 2.5 2.5

Table 2

- 5

. Particle Size Distributions Collected from Dust Jar s

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 C omplex and West 43 rd 

## A venue monitors more close ly represents areas adjacent

to the Cowtown, Pinal County Housing

, and Stanfield monitors. Therefore, the parti cle

parameters used in the MAG Five Percent P lan, as shown in T able 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 0.1 4 0. 18 0.2 8 0. 40

Particle Density (mg/m 3 

## ) 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, J ournal of the Air & Waste Management Association (J AWMA ) Vol. 63, No. 3, p.

350

- 361

.

## 8

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

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

measurement height for each PM 10 

## monitor. The following UTM Coordinates, (in

NAD 83, zone 12) were assigned to receptor point s represent ing the se three PM 10



## monitor s :

- Pinal County Housing : 446631.83 (East)

, 3639334.80 (North);

- Cowtown : 409201.93 (E ast ), 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

sh ows 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

 Sou rce p arameters for select source categories are described below.

- Unpaved Roads: Road links were modeled as area source s with release height s

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

file provided by PCAQCD and expanded by 10 f oo t mixing zone s on each

side

, 15

, 16 

## and the length s of these l inks were also extracted from the ARCGIS

shape file provided by PCAQCD

.

- Agriculture : Agricultural parcels were modeled as area source s with release

height s of 2 meters. The horizontal dimension s of the se area sources were

extracted from the ARCGIS shape file provided by ADEQ.

- Construction: Construction sites were modeled as area source s with release

height s of 2 meters. The horizontal dimension s of these area sources were

extracted from the ARCGIS shape file provided by PCAQCD

. The m ethod for

determin ing the activ ity status of construction sites is discussed in Section 3 of

Appendix B.

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

as area source s with release height s 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 dimension s of these facilities were extracted

from an ARCGIS shape file provided by ADEQ.

- Industrial f

acilities : 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.

- P ave d Roads: Road links were modeled as area sou rce s with release height s of

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

and expanded by 10 foot mixing zones on each side ; 18 

## the length s 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

- r oad 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 t he 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 complete d

, modeled PM 10 

## concentrations at the monitor were

adjusted to account for pa rticles 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 transport ed PM 10 

## , non

- anthropogenic background

PM 10 

## concentrations recor ded at Organ Pipe Cactus National Monument were

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

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

network 20



## . Filter

- based measurements are collec ted every 3 days and 24

- hour

average concentrations of both PM 10 

## and PM 2.5 

## are stored online

. PM 10 

## 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 concentration s for the remaining 19 days was

11.5 μg/m 3 

## . This average concentration was subtracted from the monitored PM 10 

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

to local sources

.

 Carryover

– A compa rison 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

- emitte d 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 ba sed 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

— v alues from feedlot emission studies 21 

## 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 43 rd

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

. M ixing height

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

of se ttling velocities by particle size range were calcu lated using an online

deposition velocity model. 22 

## The results of the analysis showed that PM 9 

## (i.e.,

particles 0

– 9 μm) would remain suspended in the second hour and that only PM 9

-

10 

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



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

size distribution, separate second

- hour deposition fractions were c alculated for

CAFO and non

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

CA FO PM 10 

## emissions would remain suspended during the second hour following

release, and 84% of PM 10 

## emissions from all other sources would remain

suspended.

 Normalize

– A comparison between the diurnal profile s of the modeled and

monitored PM 10 

## 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 PM 10 

## measured concen tration , 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 concentration s (after

s ubtracting 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 summa ries of estimated hourly concentra t ions 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

. The se tables provide

information on monitored wind speed, wind direction

, PM 10 

## concentration, m odeled

mixing height, and source

- specific concentrations. Also included are the total hourly

estimated concentrations, total daily source concentration, and overall source

apportionment

. M onitored and modeled concentrations and mixing height are depicted

graphically in Figures 2

- 2 th rough 2

- 4 (2008 base year) and Figure s 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) de pict the average daily source

- specific contributions for each site.

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

source

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

in emissions a nd 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, th e modeling impacts from the

paved roads increased a bout 25% to 65% from 2008 to 2018

.

22 

### http://www.filtration

- and

- separation.com/settling/settling.htm , accessed August 2013.

## 12

 Residential and Commercial c onstruction emissions are forecast to dec rease 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. A s a result

, the total construction

modeling impacts approximately doubled in the Cowtown and Stanfield domain s

. 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

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

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

more than double the impact of CAFO s 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 u npaved road s and unpaved trails, emissio ns are held constant from

2008 t o 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 a nd 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

2 4 % at PCH

.

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

permitted sources

, are held constant from 2008 to 2018 ; t he resulting modeling

impacts for the se sources do n o t 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/m 3 

## )

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 PM 10 

## Concentrations (μg/m 3 

## ) 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)

PM 10 Concentration (μg/m 3 )



### 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/m 3 

## )

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 PM 10 

## Concentrations (μg/m 3 

## ) 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)

PM 10 Concentration (μg/m 3 )



### 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/m 3 

## )

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

1 8 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 PM 10 

## Concentrations (μg/m 3 

## ) 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)

PM 10 Concentration (μg/m 3 )



### 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

Co wtown 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/m 3 

## )

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/m 3 

## ) 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)

PM 10 Concentration (μg/m 3 )



### 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 Coun ty Housing (PCH) on

10/29/2008, AERMOD Simulation of Monitored Concentrations (μg/m 3 

## )

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/m 3 

## ) 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)

PM 10 Concentration (μg/m 3 )



### 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/m 3 

## )

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/m 3 

## ) 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)

PM 10 Concentration (μg/m 3 )



### 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 MODELI NG

High wind design days selected for Pinal County PM 10 

## monitoring sites include d both high

wind hours ( when hourly average wind speeds exceed ed 12 m ph) and low wind hours.

During high wind hours, windblown PM 10 

## emissions are generally much greater than those

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

emission s from sources of mechanically generated PM 10 

## wer e included in the modeling of

windblown PM 10 

## emissions in order to fully account for all source contributions during

high wind hour s

. For low wind hours

, it was assumed that all PM 10 

## 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 Plan 23 

## 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 fro m a saturation monitoring study in which Maricopa

County pl aced a string of temporary PM 10 

## continuous monitors along the Salt River

channel west of the permanent monitors in the Salt River industrial zone ( i

. e ., West 43 rd



## Ave nue 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

an d 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 mechani sm

to evaluate the impacts of PM 10 

## emissions from individual land parcels within back

-

23 

### Section 6, Attainme nt 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 violatio n of the PM 10 

## 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 impa cts were not modeled ; instead

, emission inventory estimates for the low wind domains were simply quantified 24 

## to

represent the basis for low wind hour concentrations.

In contrast to Maricopa County , Pinal County experienced violations u nder both stagn ation

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

days found that some low wind hour concentra t ions exceed ed 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 mechanical ly generated

emissions and windblown dust emissions during high wind hours.

As noted in the accompanying base year emission inventory document, mechanicall y

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 t he 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 t hat 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 analysi s.



# 3.2 N on

- A nthropogenic B ackground

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 directi on during high wind hours . One of the closest

PM 10 

## monitors outside the boundar y of the Western Pinal County nonattainment area and

generally upwind in a northeast er ly 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 

### Pa ge V

- 75, “ T echnical 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.

## 2 9

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

. PM 10 

## 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 Vall ey site was

selected to represent PM 10 

## concentrations near the upwind boundary of the nonattainment

area during high wind hours.

Because the Queen Valley PM 10 

## monitoring period included days during which no high

wind hours were recorded, available 24

- hou r average PM 10 

## 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, A rizona , approx imately 12 miles to the east . The Queen Valley data

w ere 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/m 3



## . 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/m 3 

## , 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 activi ty or disturbance nearby

. The 6

- day average of 17.5 μg/m 3



## recorded at Queen Valley was selected to represent the background PM 10 

## level in high wind

rollback calculation s

.



# 3.3 Results

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

for each monit or and design day in Tables 3

- 1 through 3

- 4 (2008 base year) and Table s 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/m 3 

## , 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

concentra tions 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 PM 10 

## 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 C ounty PM10 Nonattainment Area Emissions Inventories for 2008 and 2018 Base Years and

Design Days ,” i bid.

## 30

reservoir depletion that also play a role in the diurnal profile of windblown PM 10 

## emissions

on high wind days.

High wind days are comprised of activity

- ba sed 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 windbl own emission estimates are projected to remain the

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

 W indblown dust emissions from construction are project ed to decline by 3 6 % a s

the number of dust permits decrease s from 2008 to 2018

. 27



##  To account for the completion of construction projects, some C onstruction land

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

Urban Lan ds windblown dust total grew by 2 4 % from 2008 to 2018

.

 Similarly, as a result of road im provement 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 PM1 0 Nonattainment Area Emissions Inventories for 2008

and 2018 Base Years and Design Days ,” i bid.

## 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 Devel o ped 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/m 3 ) 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)

PM 10 Concentration (μg/m 3 )



### 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 Construction Cleared Area Unpaved Parking Lots County Desert Shrubland Tribal Desert Shrubland Developed Rural Lands Developed Urban Lands Other CAFOs County Agriculture Tribal Agriculture

Un paved 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

% Contribution a

- 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/m 3 ) 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)

PM 10 Concentration (μg/m 3 )



### 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/m 3 ) 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)

PM 10 Concentration (μg/m 3 )



### 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/m 3 ) 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. Percen tage 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)

PM 10 Concentration (μg/m 3 )



### 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

C

leared 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/m 3 ) 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)

PM 10 Concentration (μg/m 3 )



### 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

P

rivate 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/m 3 ) 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)

PM 10 Concentration (μg/m 3 )



### 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 1 4.0 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/m 3 ) 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 F igure 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)

PM 10 Concentration (μg/m 3 )



### 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/m 3 ) 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)

PM 10 Concentration (μg/m 3 )



### 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 m 2 

## ) 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 page s 114 and 115 of Appendix

B would be employed and the area utilized in each equation would be the product of the area o f the parcel and

the disturbed fraction and stable fraction of the land of interest , respectively )

.

E sj 

## = F EFAdjustment 

## × A × EF Dist u rbed bin 

## × V ′

w h e r e :

Esj

= s uspe n d e d PM 10 

## in g r a m / s e c f o r hour j

,

F EFAdjustment 

## = the emission adjustment factor for diminished particle supply (detailed in Appendix B,

Exhibit BVII)

,

A = the a rea of e ac h c ro p ’s l a nd p a rc e l, in m 2



## ,

E F D i s tu r b e d,bin 

## = t he windbl o wn dust emission f ac tor d e v e loped f

o r disturb e d s oil f

or that wind sp ee d bin,

g / m 2



## - s e c for h our j ( d e tailed in Appendix B, Exhibit BV ) , and

V’ = v e g e tative c ov e r for c rop sp ec if i c , presented in Appendix B, Table 3

- 48

.

Table C I

- 1

. Values used for Example Windblown Dust Calculation

Variable Value Units Source

F EFAdjustment 

## 51 % Exhibit BVII, Table BVII

- 4

A 202,343 m 2 

## Given in assumptions (area of the field)

EF Disturbed,bin 

## 4.27E

- 04 g/m 2



## - s Exhibit BV, Table BV

- 4

V' 0.7 unitless Appendix B, Table 3

- 48

Using the values presented in Table C I

- 1 and the equation above, we can calculate windblown emissions from

the cotton field during this single hour of high wind as:

E sj 

## = 0

. 51 × 202

, 343 m 2 

## × 0

. 000427 g

m 2



## − s × 0

. 7 = 30

. 8 g

s × 3600 s

h r ÷ 453

. 6 g

lb = 244 lb

h r

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 (25,2 8 8 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/m 3 

## ) 28 

## . This results in a 24

- hr ave rage impact from this single cotton field on

the monitor of 1.8 μg/m 3 

## for the PCH design day.

28 

### 247.4 μg/m 3 

### is calculated as the design day concentration (264.9 μg/m 3 

### ) minus the calculated non

- anthropogenic background on

high risk days (17.5 μg/m 3



### , per S ection 3.2 of Appendix C ).