# Pinal County, Arizona

Area Designation for the 2006 24-hour Fine Particle National Ambient Air Quality Standard

Technical Support Document

May 5, 2010

US Environmental Protection Agency
Region 9

### Table of Contents

**Introduction ......................................**

**................................................... ............................................. 1** 

**Factor 1: Emissions Data ..........................**

**................................................... ....................................... 5** 

**Factor 2: Air Quality Data .......................**

**................................................... ...................................... 15** 

**Factor 3: Population Density and Degree of Urbaniz ation .............................................**  **.................... 18**

**Factor 4: Traffic and Commuting Patterns .........**

**................................................... ............................ 21** 

**Factor 5: Growth Rates and Patterns ..............**

**................................................... .............................. 22** 

**Factor 6: Meteorology ............................**

**................................................... ...................................... 24** 

**Factor 7: Geography and Topography ...............**

**................................................... ............................ 30** 

**Factor 8: Jurisdictional Boundaries**

**.................................................. ................................................ 33** 

**Factor 9: Level of Control of Emissions Sources .**

**................................................... ........................... 35** 

**Appendix A – Emissions in Pinal County: Primary PM 2.5**  **, NO**

**x , NH**  **3 , SO**  **2 , VOCs ................................... A-1** 

**Appendix B – Meteorological Data ..................**

**................................................... ............................ B-1** 1 

### P INAL 

### C OUNTY 

### , A RIZONA 

### A REA 

### D ESIGNATION FOR THE 

### 2006 24-H OUR 

### F INE 

### P ARTICLE 

### NAAQS

EPA intends to designate a portion of Pinal County as not attaining the 2006 24-hour PM 2.5 national ambient air quality standards (NAAQS). 1 A county or portion of a county will be designated as nonattainment if it has an air qualit y monitor that is violating the standard or if the county or portion of a county is determined to be c ontributing to the violation of the standard.

EPA intends to designate the remainder of Pinal Cou nty, Cochise, Gila, Graham, La Paz, Maricopa, Pima, Yavapai, and Yuma counties, and, as noted below, Indian country 2 located within those areas, as “unclassifiable/attainment.” EPA is deferring designation of the Gila River Indian Community and Ak-Chin Indian Community reser vations, which are located in this portion of Pinal County.

EPA Technical Analysis for Pinal County

Introduction

Pursuant to section 107(d) of the Clean Air Act, EP A must designate as nonattainment those areas that violate the national ambient air quality standards (NAAQS) and those nearby areas that contribute to the violations. This technical analy sis identifies the monitor that violates the 24-

hour PM 2.5 standard and evaluates surrounding counties for co ntributions to fine particle

concentrations in the area. EPA has evaluated thes e counties based on the weight of evidence of the following nine factors recommended in EPA guida nce and any other relevant information:

- pollutant emissions - air quality data - population density and degree of urbanization - traffic and commuting patterns - growth

1 EPA designated nonattainment areas for the 1997 fin e particle standards in 2005. In 2006, the 24-hour PM 2.5 standard was revised from 65 micrograms per cubic m eter (average of 98th percentile values for 3 conse cutive years) to 35 micrograms per cubic meter; the level of the 1997 annual standard for PM 2.5 remained unchanged at 15 micrograms per cubic meter (average of annual avera ges for 3 consecutive years).

2 “Indian country” as defined at 18 U.S.C. 1151 refe rs to: “(a) all land within the limits of any India n reservation under the jurisdiction of the United States Governm ent, notwithstanding the issuance of any patent, an d, including rights-of-way running through the reservation, (b) all dependent Indian communities within the borders of the United States whether within the original or subseq uently acquired territory thereof, and whether with in or without the limits of a state, and (c) all Indian allotment s, the Indian titles to which have not been extingu ished, including rights-of-way running through the same.” The lands of the Fort McDowell Yavapai, Salt River Pima-Mari copa, San Carlos Apache and Tohono O’odham tribes will be des ignated “unclassifiable/attainment.”2

- meteorology - geography and topography - jurisdictional boundaries

- level of control of emissions sources

We also used analytical tools and data such as poll ution roses, coarse particle composition monitoring data, and the correlation between meteor ological data and composition data to

evaluate these areas.

Figure 1 is a map of the counties in the area and o ther relevant information such as the locations of air quality monitors. Pinal County and Maricopa County comprise the Phoenix-MesaScottsdale Core-Based Statistical Area (CBSA).

Figure 1. PM 2.5 Monitors – Pinal County and Surrounding Counties

In response to EPA’s promulgation of the revised 24 -hour PM 2.5 NAAQS in 2006, the Governor of Arizona, by letter dated December 19, 2007, reco mmended that all portions of the state, with the exception of the Nogales area, be designated as “attainment” for the 2006 24-hour PM 2.5 standard based on air quality data from 2004-2006. These data are from Federal Reference3

Method (FRM) monitors located in the state. The St ate of Arizona does not have jurisdiction over Indian country.

In October of 2009, EPA notified the Governor of Ar izona and Tribal leaders of tribes with lands located in Pinal and Maricopa counties that a monit or in Pinal County was violating the 24-hour

PM 2.5 standard based on the most recent (2006-2008) air q uality monitoring data. Due to this new violation, and due to the need for additional t ime to collect data and evaluate the area to determine an appropriate nonattainment area boundar y, EPA decided to defer the area designation of Pinal County, Maricopa County (i.e., the other county comprising the PhoenixMesa-Scottsdale CBSA), and the seven counties (i.e ., Cochise, Gila, Graham, La Paz, Pima, Yavapai, and Yuma Counties) surrounding the Phoenix -Mesa-Scottsdale CBSA, for the 2006 24-

hour PM 2.5 standard. 3

Based on EPA’s technical analysis, EPA believes the central-western portion of Pinal County, Arizona, should be designated as “nonattainment” fo r the 24-hour PM 2.5 NAAQS as shown in Figure 2. Emission inventory data, combined with s peciation and source apportionment data, point to agricultural activities and cattle feedlot s, as well as other nearby sources of PM 2.5 , as primary sources contributing to PM 2.5 levels at the Cowtown monitor on days with exceedan ces of the 24-hour PM 2.5 NAAQS. In addition, EPA assessed air quality and meteorological data, including data on monthly exceedances of the 24-hou r PM 2.5 standards; wind direction and speed for hourly and daily PM 2.5 levels; correlation of PM 2.5 with PM 10 at the Cowtown monitoring site; and, the diurnal pattern of PM 10 , wind speed, and temperature for PM 2.5 exceedance days. Results of these assessments indicate that agricult ural lands and cattle feedlots, and activities associated with these operations, particularly thos e to the south and southwest of the monitor, are contributing to PM 2.5 levels at the monitoring site.

3 Unless otherwise specified, references to “countie s” or to “Arizona” include all lands within the geo graphic boundary and do not differentiate between lands und er state or tribal jurisdiction.4

Figure 2. EPA Proposed Nonattainment Area Boundary

Except as noted below, EPA intends to designate the remaining portion of Pinal County, including those lands of the Tohono O’odham Nation, and the San Carlos Apache Tribe that are located in Pinal County, Arizona, as “unclassifiabl e/attainment” for the 2006 24-hour PM 2.5 NAAQS.

The population density on the lands of the Tohono O ’odham Nation, which lie to the south and west of EPA’s intended nonattainment area is very l ow at approximately 3 people per square mile, and the types of sources that data indicate a re the primary contributors to exceedances of

the 24-hour PM 2.5 NAAQS in Pinal County (e.g., cattle feedlots and u npaved roads) either are not present on Tohono O’odham tribal lands or are p resent in small amounts. EPA has therefore concluded that any emissions activities occurring t here are not contributing to nonattainment at the violating monitor in Pinal County.

The lands of the San Carlos Apache Tribe are locate d at a considerable distance from the proposed nonattainment area and are separated from it by mountainous terrain. Therefore, EPA concludes that any emissions activity there is not contributing to the violation at the monitor in Pinal County. Accordingly, EPA intends to designat e the lands of the San Carlos Apache Tribe

as “unclassifiable/attainment.”5

EPA is deferring designation of the lands of the Ak -Chin Indian Community and the Gila River Indian Community 4 in order to consider unique issues involving these tribal lands and to complete formal consultation with these tribal gove rnments.

EPA intends to designate the eight counties surroun ding Pinal County, including Indian country that lies within those counties, as “unclassifiable /attainment” for the 24-hour PM 2.5 NAAQS. These counties are: Cochise County, Gila County, G raham County, La Paz County, Maricopa County, Pima County, Yavapai County, and Yuma Count y. As stated above and described in more detail below, there are no violating monitors in these counties, and evaluation of the nine factors supports a finding that emissions within th e eight subject counties do not contribute to the

PM 2.5 violations recorded at the Cowtown monitor for the purposes of section 107(d) of the Clean Air Act. With respect to Cochise, Gila, Graha m, and Yavapai counties, this conclusion is supported by, among other factors, the speciation a nd source apportionment data for the Cowtown monitor (which point to the predominance of local sources), the distance between sources in these counties and the proposed nonattai nment area, the presence of topographical features inhibiting emissions transport to the Cowt own monitor location, and the low direct

PM 2.5 emissions and population densities characteristic of these counties. For La Paz and Yuma counties, topography plays a lesser role, but the o ther factors, the speciation and source apportionment data for the Cowtown monitor (which p oint to the predominance of local sources), the distance between sources in these cou nties and the proposed nonattainment area, as

well as the low direct PM 2.5 emissions and population densities characteristic of these counties, support a finding of little or no contribution from La Paz and Yuma counties.

For Maricopa County, the closest county with signif icant population, the meteorological evaluation along with the speciation and source app ortionment data lends support to a finding of little or no contribution. For Pima County, the fin ding of little or no contribution relies upon the speciation and source apportionment data, the corre lation between PM 2.5 and PM 10 concentrations, and the review of contemporaneous a mbient concentration, wind speed and wind direction data at the Cowtown monitor during period s when exceedances have been recorded.

The following is a summary of EPA’s technical analy sis, which supports the boundaries of the nonattainment designation for the Pinal County 2006 24-hour PM 2.5 nonattainment area and the attainment/unclassifiable designation for the remai nder of Pinal County, Cochise, Gila, Graham, La Paz, Maricopa, Pima, Yavapai, and Yuma counties, and, except as noted above, Indian country located within those areas.

Factor 1: Emissions data

For this factor, EPA evaluated county-level emissio n data for the following PM 2.5 components and precursor pollutants: “Primary PM 2.5 ,” “SO 2 ,” “NO

x ,” “VOCs,” and “NH 3. ” “Primary

PM 2.5 ” represents direct emissions of PM 2.5 and includes: “PM 2.5 emissions carbon,” “PM 2.5 emissions other,” primary sulfate (SO 4 ), and primary nitrate. (Although primary sulfate and primary nitrate, which are emitted directly from st acks rather than forming in atmospheric

reactions with SO 2 and NO

x , are part of “PM 2.5 emissions total,” they are not shown in Table 1 as

4 Gila River Indian Community reservation straddles the border between Pinal and Maricopa counties. Des ignation for the entire reservation, including the portion l ocated within Maricopa County, is deferred.6

separate items.) “PM 2.5 emissions carbon” represents the sum of organic ca rbon (OC) and elemental carbon (EC) emissions, and “PM 2.5 emissions other” represents other inorganic particles (crustal). Emissions of SO 2 and NO

x , which are precursors of the secondary PM 2.5 components sulfate and nitrate, are also considered . VOCs (volatile organic compounds) and

NH 3 (ammonia) are also potential PM 2.5 precursors and are included for consideration.

Table 1 shows emissions of PM 2.5 and precursor pollutants (given in tons per year) for counties with violating monitors and potentially contributin g counties surrounding Pinal County. The

emissions data were derived from the most current v ersion of the national emissions inventory, the 2005 National Emissions Inventory, version 2 (N EIv2). 5

Table 1. Emission Totals Per County (tons per year ). 2005 NEI version 2.

County Primary

PM 2.5 Emissions NO

x NH 3 SO 2 VOC

Pinal 4,210 12,545 5,646 757 9,217

Maricopa 14,836 99,947 19,318 5,276 108,548

Cochise 2,939 16,137 3,531 3,826 8,838

Gila 2,316 2,098 553 20,342 7,592

Graham 903 1,010 494 61 1,894

La Paz 573 3,017 597 148 2,604

Pima 4,827 30,412 1,878 6,157 31,169

Yavapai 4,717 14,640 1,300 1,912 11,552

Yuma 1,748 9,219 4,370 555 7,138

While many of the surrounding counties generate sub stantial emissions of primary PM 2.5 and

PM 2.5 precursors relative to Pinal County, as explained f urther below, the composition of the particles measured at the Cowtown monitor on high P M 2.5 days, combined with meteorological data and the presence of topographic barriers, indi cate that there is a negligible contribution from the surrounding counties to the total PM 2.5 levels at the violating monitor.

5 http://www.epa.gov/ttn/chief/net/2005inventory.html #inventorydata . Retrieved February 3, 2010.7

To determine what nearby sources exist, EPA conside red additional emissions data for the county containing the violating monitor. Table 2 l ists source categories in Pinal County that emit direct (primary) PM 2.5 according to the 2005 NEIv2. Open burning, agricul ture (including crop tilling and livestock dust), unpaved roads and cons truction account for 67% of the primary PM 2.5 emissions in Pinal County. Additional tables showi ng source categories in Pinal County that emit nitrogen oxides, ammonia, sulfur dioxide, and volatile organic compound emissions may be found in Appendix A.

Table 2. Primary PM 2.5 Sources in Pinal County* (includes filterables + c ondensables**).

2005 NEI version2.

Source Category Emissions (tpy) % of Total Primary

PM 2.5 Emissions, Pinal County

Nonpoint

Waste Disposal - Open Burning 886 21%

Agriculture - Crop Tilling & Livestock Dust 751 1 8%

Unpaved Roads 626 15%

Construction 547 13%

Wildfires 395 9%

Industrial Process – not elsewhere classified 220 5%

Paved Roads 152 4%

Other Nonpoint 105 2%

Nonroad

Non-Road Equipment – Diesel 166 4%

Planes, Trains, & Ships 64 2%

Non-Road Equipment – Gasoline 38 1%

Onroad

On-Road Vehicles – Diesel 116 3%

On-Road Vehicles – Gasoline 42 1%

Point

Misc. Point 102 2%

TOTAL: 4,210 100%

*Emissions from tribal lands are not included becau se tribes are not required to submit

information to the NEI. ** Filterable PM consists of particles that are dir ectly emitted as a solid or liquid at stack or release conditions and are captured on the filter o f a stack test train. Condensable PM is material that is in the vapor phase at stack conditions but condenses and/or reacts upon cooling and

dilution in the ambient air to form a solid or a li quid particulate immediately after discharge

from the stack.

Sources in the immediate vicinity of the Cowtown mo nitor include cattle feedlots, an ethanol plant, agricultural fields, and a commercial compos ting facility. The monitor is approximately 300 yards from the closest feedlot. Four different cattle operations (Sawyer Cattle Company, OK Cattle Co., Maricopa Feedyard LLC, and Pinal Fee ding Co.) are located immediately8

northwest, west, south, and southeast of the monito r and account for approximately 424 acres of

feedlot. 6 As shown by Figure 3, active and fallow agricultu ral fields surround the area. Figure 4 shows issued construction permits, and point source s emitting direct PM 2.5 near the Cowtown monitor. Also shown is a close-up of the Cowtown m onitor and surrounding operations. Figure 5 shows paved and unpaved roads within fifty miles of the Cowtown monitor.

Figures 3, 4, and 5 reflect information for both tr ibal and non-tribal lands. Figure 3 contains agriculture information from the USDA (2006), and f eedlot, dairy and additional cattle operations information from the Dun and Bradstreet business database (2007) and Google Earth (retrieved February 3, 2010). Figure 4 shows const ruction permits issued according to ADEQ (2010) and point sources from EPA’s 2005 NEI versio n 2. Figure 5’s paved and unpaved roads information originates from Teledyne Atlas of North America (2006) and U.S. Department of Commerce, U.S. Census Bureau, Geography Division (2 008), respectively.

6 Dun & Bradstreet Agricultural Data9Figure 3. Agriculture, Feedlots, Dairies, and Additional Cattle Operations.77USDA 2006; Dun and Bradstreet business database 2007; Google Earth February 3, 2010.10Figure 4. Construction and Point Sources within Fifty Miles of the Cowtown PM2.5Monitor.88ADEQ 2010; 2005 NEI version 2.11Figure 5. Paved and Unpaved Roads within Fifty Miles of the Cowtown PM2.5Monitor.99Teledyne Atlas of North America 2006; U.S. Department of Commerce, U.S. Census Bureau, Geography Division 2008.12

In 2003, Pinal County Air Quality Control District (PCAQCD) undertook a source apportionment study to determine what sources were contributing to elevated PM levels. 10
Chemical fingerprints were developed for feedlot so il emissions, agricultural soil emissions, and

dirt road soil emissions. The feedlot emissions co ntained a substantial amount of total carbon (particularly OC3), making it a distinguishable sig nature. The chemical analysis was not able to distinguish between agricultural and dirt road emis sions. The report notes that a high total carbon signature may not only be associated with fe edlots, but possibly with agricultural fields recently covered with manure. The report does not mention the composting facility near the Cowtown monitor; however, emissions from this sourc e could also show high total carbon.

Open burning, agricultural fields, livestock, unpav ed roads and construction are the source categories with the highest direct PM 2.5 emissions in Pinal County according to the 2005 NEI v2. One would expect significant geological soil and fe edlot/manure signatures from the majority of these source types, which is consistent with the Pi nal County source apportionment study findings.

As shown in Figure 6, 24-hour PM 2.5 data collected at Cowtown in October and November 2 003 showed an average contribution of 49% from the feed lot soil category and 24% from geological soil. The average concentration was 67 micrograms per cubic meter (μg/m 3) , with three samples over 100μg/m 3 . Each of these three sample days showed inversion conditions with light winds throughout the day.

Figure 6. PM 2.5 Cowtown Monitor Average Source Contributions. 11

Soil Geological soil ColPP Coal fired power plant

Feedlot Feedlot soil AmSulf Ammonium sulfate

MV Emi Motor vehicle

combustion emissions AmNitr Ammonium nitrate

VgBr Vegetative burning Other Unclassified sources

10 Pinal County Air Quality Control District Source A pportionment Study: July 29, 2005

11 Pinal County Air Quality Control District Source A pportionment Study: July 29, 2005, p 35.13

Figure 7 (Table 9 and Figure 7 from the Pinal Count y Source Apportionment Study) illustrates the correlation between higher levels of PM 2.5 and increased levels of feedlot and soil emissions

. The feedlot contribution ranged from 1.41 μg/m 3 on October 12, 2003, when the total measured

PM 2.5 was 15.7 μg/m 3 (9% of the total), to 146.29 μg/m 3 on October 27, 2003, when the total

measured PM 2.5 was 183.38 ug/m3 (79.8% of the total). The soil co mponent also varied significantly, with the highest measured levels occ urring on days when the overall PM 2.5 levels were highest. On days when measured PM 2.5 levels were at or above 35 μg/m 3 , the combined

feedlot and soil emissions contribution to total PM 2.5 mass ranged from 68% to 96% of the total.

In contrast, the contribution of other sources (e.g ., vegetation burning and coal-fired power plant) was relatively constant and low. For example, for days that data were collected, the contribution from coal-fired power plants ranged from 1.73 to 5. 05 μg/m 3 and averaged 3.53 μg/m 3

.14Figure 7. PM2.5Source Attributions from Pinal County Source Apportionment Study15

The Pinal County source apportionment study results indicate that violations of the 2006 24-hour

PM 2.5 NAAQS in Pinal County may be the result of contribu tion from significant local, rather than regional, sources of emissions of PM 2.5 . For example, the high proportion of directly emitted particles suggests that there is little con tribution from more distant sources of PM 2.5 precursor emissions in surrounding counties. Unlik e other areas, where the monitored PM 2.5 does not have such characteristics, and instead ref lects both regional and local contribution, the analysis of this area indicates that certain source categories in the surrounding area are those that contribute sufficiently to require inclusion within the designated nonattainment area.

The following sections of this TSD further discuss how other factors, including air quality data and meteorology, indicate that nearby direct PM 2.5 emission sources are responsible for the majority of the monitored PM 2.5 levels at the Cowtown monitoring site.

Factor 2: Air Quality Data

This factor considers the 24-hour PM 2.5 design values (in μg/m 3 ) for air quality monitors in Pinal County and the surrounding counties based on data f or the 2006-2008 period. A monitor’s design value indicates whether that monitor attains a specified air quality standard. The 24-hour

PM 2.5 standards are met when the 3-year average of a mon itor’s 98 th percentile values are 35μg/m 3 or less. A design value is only valid if minimum data completeness criteria are met.

The location of PM 2.5 monitors and design values for these monitors are s hown in Figure 8.

Eligible monitors for providing design value data g enerally include state and local air monitoring stations (SLAMS) at population-oriented locations w ith a federal reference method (FRM) monitor. All data from special purpose monitors (S PM) using an FRM is eligible for comparison to the relevant NAAQS, subject to the requirements given in the October 17, 2006 Revision to Ambient Air Monitoring Regulations (71 FR 61236). All monitors used to provide data must meet the monitor siting and eligibility requirement s given in 71 FR 61236 to 61328 in order to be acceptable for comparison to the 24-hour PM 2.5 NAAQS for designation purposes.

The 24-hour PM 2.5 design values for the individual monitors in Pinal County are shown in Table 3. Table 4 lists the design value for surrounding c ounties (based on the highest reading monitor).

Table 3. PM 2.5 Pinal County Air Quality Monitoring Data

Site Name AQS ID PM 2.5 24-hour Design Value

2006-2008 Casa Grande 04-021-0001-1 20 μg/m 3
Apache Junction 04-021-3002-1 13 μg/m 3

Cowtown 04-021-3013-1 48 μg/m 3

EPA notes that the monitor located at Cowtown shows ambient levels more than twice as high as

those of the other monitors located in Pinal. This suggests that there may be sources that contribute more to that monitor than to the others, and that the sources may be in the vicinity of the violating monitor.16

The Cowtown monitor is located near a number of cat tle feedlots. A grain processing facility and a commercial composting facility are also located n earby. This source mix mostly likely represents a relatively unique situation

. Analysis of wind and pollution roses during exceeda nce days show that the Cowtown monitor is most likely s ignificantly influenced by the cattle feedlots located upwind. See Factor 6 discussion of meteorol ogy.

Table 4. PM 2.5 Air Quality Monitoring Data for Pinal County and Ne arby Counties County Design Value Site AQS ID PM 2.5 24-hour Design

Value 2006-2008 Cochise Douglas 04-003-1005-1 15 μg/m 3
Gila* Payson 04-007-1008-1 23 μg/m 3
Maricopa West Phoenix 04-013-0019-1 27 μg/m 3
Pima Orange Grove 04-019-0011-1 12 μg/m 3
Pinal Cowtown 04-021-3013-1 48 μg/m 3
Yavapai** Prescott Valley 04-025-2002-1 12 μg/m 3
Yuma** Yuma 04-027-0004-1 21 μg/m 3
Santa Cruz*** Nogales 04-023-2002-2 40 μg/m 3
*Only two years of data available **Only one year of data available

*** The Nogales planning area in Santa Cruz County, whi ch lies south of Pima County, has been designated nonattainment. It is the only other area in Arizona that violates the PM 2.5 24-hour NAAQS.

All of the counties surrounding Pinal County have m uch lower PM 2.5 concentrations. This information coupled with the meteorological informa tion and topographic information (following) lends support to a finding of predomina te local influence over PM 2.5 concentrations

at the Cowtown monitor.17Figure 8. PM2.5Monitors and Design Values18

Factor 3: Population density and degree of urbaniza tion (including commercial development)

Table 5 shows the 2005 population and population de nsity for each county in the area being

evaluated.

Table 5. Population: Pinal and Surrounding Countie s County State

Recommended
Nonattainment? 2005 Population 2005 Population Density (pop/sq mi) Pinal* No 240,044 45 Maricopa No 3,683,481 394 Cochise No 126,153 20 Gila No 51,528 11 Graham No 33,089 7 La Paz No 20,225 4 Pima No 925,000 101 Yavapai No 198,841 24 Yuma No 181,598 33

*Arizona submitted its recommendations on December 19, 2007. At that time, Pinal County was attaining the 24-hr PM2.5 st andard

Table 6 shows the 2008 population density for munic ipalities and reservations within Pinal County.

Table 6: Population Density within Pinal County – 2008 Entity Area in

Square

Miles 2008

Population Density 2008 Population

Pinal County

Total 5,369.6 65.3 350,558

Apache

Junction 34.23 1,108.7 32,776

Casa Grande 48.17 936 41,152 Coolidge 5.03 2,447.5 10,261 Eloy 71.67 225.4 12,750 Florence 8.29 2,903.1 20,781 Kearny 2.79 1,177.5 3,297
Mammoth 1.08 2,339.1 2,573 City of Maricopa 31.9 1,428.6 45,571

Queen Creek 25.8 944.2 Pinal Co: 5,700 Maricopa Co: 18,661 Total: 24,361 Superior 1.93 1,766.3 3,335

Ak Chin 87.2 48.3 1,591
GRIC** 581.1 37 21,665

San Carlos Apache** 2,896.6 3.6 10,416

Tohono

O’odham** 4,453 3.1 13,635

Source: U.S. Census Bureau and ADEQ TSD19

*Maricopa 2008 area from ADEQ PM 10 boundary recommendation TSD
**Population for entire reservation, including port ions that lie outside of Pinal County

.

Table 5 illustrates that, with the exception of Mar icopa County, Pinal County and other surrounding counties are relatively sparsely popula ted. Maricopa County, which lies to the north and includes the Phoenix metro area, has a populati on density of 394 people per square mile, but

does not violate the 2006 24-hour PM 2.5 NAAQS. As illustrated by Figure 9, about 95% of t he Pinal County population resides in the more urbaniz ed areas that lie in the western/central portion of the County, where a number of relatively densely populated areas are located. Even within those more densely populated areas, the numb ers of inhabitants are relatively low (see Table 6).

Population data can give an indication of whether i t is likely that population-based emissions are contributing to PM 2.5 levels at the violating monitor. For this area, po pulation density, however, does not appear to be a driving factor in the high PM 2.5 levels measured at the Cowtown monitor in Pinal County. Instead, the violations in this area appear to be contributed to most heavily by cattle feedlots and other agricultural activities t hat in fact are inversely related to the population density. Therefore, in this area, population and p opulation density are not as relevant to evaluating the geographic extent of the area with e missions activities contributing to the

violations.20Figure 9. Population Density and PM2.5Monitors21

Factor 4: Traffic and commuting patterns

This factor considers the number of commuters in ea ch surrounding county who drive to Pinal County, the percent of total commuters in each coun ty who commute to Pinal County

, the percent of total commuters in each county who commu te into the statistical area in which Pinal County is located, as well as the total vehicle miles traveled (VMT) f or each county, in millions

of miles.

Data on commuting illustrate that the majority of P inal County’s working residents are employed within the county. Data from 2000 12 illustrate that a sizeable number (19,918) commute to Maricopa County to the north, with 7,750 commuters entering Pinal from Maricopa County. About 2,600 Pinal County residents commute to Pima County to the south, while 1,970 Pima County residents commute into Pinal County. The nu mber of commuters to and from other surrounding counties is negligible. See Table 7 an d Figure 10.

Table 7. Traffic and Commuting Patterns – 2005 County State

Recommended

Nonattainment? 2005

VMT (millio

ns of miles) Number

Commuting

to Pinal County Percent

Commuting

to Pinal County Number

Commuting

into

statistical

area* Percent

Commuting

into

statistical

area Pinal No 3,126 35,960 60.1 55,880 93.4 Maricopa No 32,392 7,750 0.6 1,389,480 98.9 Cochise No 1,906 40 0.1 260 0.6 Gila No 536 330 1.9 1,390 7.9

Graham No 373 - 0.0 150 1.4

La Paz No 684 - 0.0 150 1.4 Pima No 8,759 1,970 0.5 3,810 1.0 Yavapai No 2,385 30 0.0 3,640 5.4 Yuma No 1,902 10 0.0 240 0.5 *Pinal and Maricopa Counties comprise the Phoenix-M esa-Scottsdale CBSA

Commuting patterns can indicate the extent of an ur ban area and can serve as an indicator of likely contribution to fine particle concentrations in an area. However, in this area, the technical analysis suggests that the violations at the Cowtow n monitor are the result of contribution not from secondary particles from more distant mobile s ource emissions, but rather from other types of emissions activity closer to the violating monit or. The nature of the PM 2.5 violation in Pinal County indicates the violations occurring there are driven primarily by nearby stationary and

area sources of PM 2.5 . See Factors 1 and 2. Traffic may contribute som ewhat to the PM 2.5 levels on days with violations at the Cowtown monitor, but it does not appear to be one of the major

factors in the violations.

Note: The 2005 VMT data used for Tables 7 and 8 of the 9-factor analysis has been derived using methodology such as that described in “Docume ntation for the 2005 Mobile National Emissions Inventory,” Version 2, December 2008, pre pared for the Emission Inventory Group,

12 Arizona Air Quality Designations Technical Support Document; Boundary Recommendation for the Pinal Co unty
24-hour PM 10 Nonattainment Area, Table 3-6, March 15, 2010.22

U.S. EPA. This document can be found at: at ftp://ftp.epa.gov/EmisInventory/2005_nei/mobile_sec tor/documentation//2005_mobile_nei_versi on_2_report.pdf

Figure 10. Traffic, Commuting Patterns, and PM2.5 Monitors

Factor 5. Growth rates and patterns

This factor considers population growth for 2000-20 05 and growth in vehicle miles traveled for 1996-2005 for Pinal and the surrounding counties, a s well as patterns of population and VMT growth. Population growth within Pinal County between the y ears of 2000 and 2008 is also reviewed. A county with rapid population or VMT gro wth is generally an integral part of an urban area and likely to be contributing to fine pa rticle concentrations in the area.

Table 8 below shows population, population growth, VMT and VMT growth between 1996 and 2005 for Pinal and the surrounding counties.23

Table 8. Population and VMT Values and Percent Cha nge Location Population

(2005) Population

Density (2005) Population

% change (2000 - 2005) 2005 VMT

(millions mi) VMT

% change (1996 to 2005) Pinal 240,044 45 32 3,126 54

Maricopa 3,683,481 394 17 32,392 53

Cochise 126,153 20 7 1,906 29

Gila 51,528 11 0 536 6

Graham 33,089 7 -1 373 32

La Paz 20,225 4 3 684 48

Pima 925,000 101 9 8,759 52

Yavapai 198,841 24 18 2,385 12

Yuma 181,598 33 13 1,902 38

Table 9 shows the 2006 and 2008 population density for municipalities within Pinal County.

Table 9. Population Growth within Pinal County Entity Area in

Square

Miles Population Density Population

2000 2008 2000 2008

Pinal County

Total 5,369.6 33.5 65.3 179,727 350,558

Apache

Junction 34.23 929.3 1108.7 31,814 32,776

Casa Grande 48.17 523.7 936 25,224 41,152 Coolidge 5.03 1,549.1 2,447.5 7,786 10,261 Eloy 71.67 144.8 225.4 10,375 12,750 Florence 8.29 2,056.2 2,903.1 17,054 20,781 Kearny 2.79 805.4 1,177.5 2,249 3,297 Mammoth 1.08 1,626.5 2,339.1 1,762 2,573 City of Maricopa* 2000 – 4.04

2008 – 31.9 257.6 1,428.6 1,040 45,571

Queen

Creek** 25.8 167.3 944.2 Pinal Co: 119 Maricopa Co: 4,197 Total: 4,316 Pinal Co: 5,700

Maricopa Co: 18,661 Total: 24,361

Superior 1.93 1,684.6 1,766.3 3,254 3,335 Source: U.S. Census Bureau and ADEQ TSD *Maricopa 2008 area from ADEQ PM10 boundary recomme ndation TSD ** Queen Creek straddles the Pinal and Maricopa Cou nty border, with about 23.4% of the city’s area lyi ng within Pinal County. The population figures in the table a re pro-rated to reflect the proportion of the city that is within each county, but density is not pro-rated.24

The State of Arizona has experienced rapid populati on growth in recent years (26.7% between 2000 and 2008); however, vast areas remain sparsely inhabited. In Pinal County the population increased 82% between 2000 and 2008, with almost al l of the population growth occurring in the central and western portion of the county. Along w ith this growth, VMT has also increased dramatically.

Growth in Pinal County may be contributing somewhat to the PM 2.5 levels on days with violations at the Cowtown monitor; however, it does not appear to be one of the major factors in

the violations.

Factor 6. Meteorology

Like most of Arizona, Pinal County is hot and dry. Average maximum temperatures at the Maricopa weather station (part of the National Weat her Service Cooperative Network) range from 67 degrees Fahrenheit ( o F) in January to 107 o F in July, and minimum temperatures from

25 o F in January to 75 o F in August. The rainiest month is July, with just over an inch of rain; the yearly total averages 8 inches. Despite the drynes s, there is substantial agriculture in Pinal County, supported by irrigation from groundwater an d the Central Arizona Project. Weather systems typically arrive from the west, except duri ng "monsoon" season, which occurs June through August or September, when moisture from the south arrives and creates thunderstorms.

The wind at the Cowtown monitor is typically from t he southeast during the cooler hours of 7 pm - 6 am, corresponding to downhill drainage flow down the Gila River valley. Flow at other times is less consistent, though there can be stead y winds from the west in late morning through the afternoon, and on occasion from the north or so uth. While there are periods of high wind and gusts, especially during "monsoon" season, wind spe eds are most often 3 meters per second (m/s) or less, with higher speeds usually from the west. High wind and gusts, especially over disturbed desert areas, can lead to substantial fug itive dust emissions. Sometimes there are “haboob” dust storms that have the appearance of an approaching “wall of dust,” in which visibility is very low and gusts very strong.

EPA examined available PM and meteorological data i n a number of ways to assess the extent to which surrounding nearby areas could be contributin g to PM 2.5 violations at the Cowtown monitor. Results of these analyses are presented b elow in the form of: a) a pollution rose for daily PM 2.5 levels, b) a graph of the correlation of PM 2.5 with PM 10 at four monitoring sites in the Pinal County area, and c) graphs showing the diurna l pattern of PM 10 , wind speed, and temperature for PM 2.5 exceedance days. The potential for transport of P M 2.5 from the metropolitan Phoenix area to the north was consider ed in the analyses, given the large number of emitting sources and the high population density th ere.

a. Pollution rose

EPA developed a “pollution rose” for the Cowtown si te to understand the prevailing wind direction and wind speed on the days with highest f ine particle concentrations. Figure 11 categorizes 24-hour PM 2.5 values by color: days exceeding 35μg/m 3 are denoted with large red or25

black symbols. Small blue symbols are for days und er 30μg/m 3 , and intermediate sized yellow symbols are between 30 and 35μg/m 3 . Symbol shape distinguishes time of year the exce edance occurred: a circle for the warm season (May through September), and a triangle for the cool season (October through April). The center of the figure indicates the location of the air quality monitoring site, and distance of the symbol from th e center indicates average wind speed on the day, with lower wind speeds nearer the center. The angular location of the symbol indicates the compass direction from which the average wind was b lowing on that day. (Note that, since a pollution rose symbol direction is the resultant of 24 hourly winds during each day, a symbol in the southwest may be a combination of westerly and southerly flow, for example.)

The pollution rose indicates that most PM 2.5 exceedances occur when resultant wind is from the southwest through southeast, although there are a n umber of days with no clear wind direction (symbols without fill, near the center), and a few days with wind from the north and northeast. There does not seem to be a clear separation betwee n the cool and warm seasons. The highest

PM 2.5 concentrations (black symbols) have wind direction s from the south or southwest, and two from the north. Only a few days have resultant win d speeds above 8 m/s; the vast majority have speeds of 4 m/s or less. Altogether, the pollution rose indicates that PM 2.5 exceedances are generally not associated with steady strong winds, or with winds from the north. This is evidence

that the exceedances of the 24-hour PM 2.5 standard measured at the Cowtown monitor are likel y due to local sources.

Figure 11. Pollution Rose26

b. Correlation of PM 2.5 and PM 10

EPA examined the correlation of daily PM 10 with daily PM 2.5 , and also the correlation of the

PM 2.5 / PM 10 ratio with PM 2.5 , for various monitoring sites in Pinal County and neighboring Maricopa County, as illustrated in Figure 12. The Cowtown monitor has a consistent PM 2.5 /

PM 10 ratio that is lower than other nearby sites, sugge sting that the causes of Cowtown PM 2.5 concentrations are different than for other locatio ns. In addition, the Cowtown ratio is independent of the PM 2.5 level, whereas for other sites, the ratio increase s with PM 2.5. This indicates that the Cowtown monitor is impacted by d ifferent PM 2.5 sources than other locations.

The correlation of the PM 2.5 / PM 10 ratio with PM 2.5 concentrations at the Cowtown monitor also suggests that PM 2.5 and PM 10 concentrations at the Cowtown monitoring site are generated by

the same sources.

Figure 12. Correlation Between Ratio of PM 2.5 / PM 10 and PM 2.5

c. Diurnal pattern of PM 10 , wind speed, wind direction, and temperature

Hourly PM 2.5 data are not available for the Cowtown site, but h ourly PM 10 data are. EPA

examined the diurnal variation of PM 10 , wind speed, wind direction, and temperature, toge ther with daily PM 2.5 values. PM 10 , wind speed, and temperature for two representativ e quarters are presented in Figures 13 and 14. 13 Hourly wind direction for all exceedance days is p rovided in Figure 15. While PM 10 is not the same as PM 2.5 , the correlation of 24-hour PM 10 and PM 2.5 described above suggests that diurnal PM 10 patterns may provide useful information about PM 2.5

.

13 Appendix B includes meteorological data for all qu arters.27

Figure 13. Diurnal Variation of PM 10 , Wind Speed, and Temperature on PM 2.5 Exceedance Days in Quarter 128

Figure 14. Diurnal Variation of PM 10 , Wind Speed, and Temperature on PM 2.5 Exceedance Days in Quarter 429

Figure 15. Wind Vectors on 2006-2008 Cowtown PM 2.5 Exceedance Days30

Most of the PM 2.5 exceedance days have a very large PM 10 "spike" (1000 - 3000 μg/m 3 ) some time in hours 20-23 (Figures 13 and 14, top panel). This spike is independent of wind speed (Figures 13 and 14, middle panel), temperature (Fig ures 13 and 14, bottom panel), or direction (Figure 15) during the day. During the rest of the day, PM 10 is generally low, though with morning excursions on a few days. Thus, the PM 10 spike appears to be associated with some local activity, possibly at the nearby feedlots.

A few days (e.g., 2007-10-09) have elevated PM 10 after elevated winds (10 m/s); other days have high wind, but well before any increase in PM 10 levels. However, in general, wind speeds are at most 4 m/s, so high PM 10 is not typically caused by local wind-generated fu gitive dust.

The height of the PM 10 spike is not directly related to the PM 2.5 value for the day, despite the

overall correlation of 24-hour PM 10 and PM 2.5 . High winds do not seem to be the cause of the

PM 2.5 exceedances, though may be a contributing factor i n a few cases.

Approximately half of the PM 2.5 exceedance days have steady wind from the north du ring the afternoon (Figure 15). However, the period of nort herly wind generally coincides with the period of lowest PM 10 . Quarter 4 includes December 1, 2006, one of the two exceedance days shown in the pollution rose (Figure 11) where the r esultant wind direction was from the north. The hourly PM 10 concentrations for 12/1/2006 show the same spike d uring the hours of 20-23,

which coincides with wind directions from the south rather than the north (Figure 15). Thus, it is unlikely that PM 10 transported from the north (i.e., metropolitan Pho enix) is the cause of elevated

PM 10 concentrations. Since daily PM 2.5 and PM 10 levels rise and fall roughly together at the Cowtown site, as described above, this is evidence that PM 2.5 levels measured at the Cowtown monitoring site are due to local activity.

The overall correlation between PM 2.5 and PM 10 at the Cowtown monitoring site, combined with the generally low wind speeds, is evidence that the PM 2.5 levels are likely due to emissions from

local sources.

The fact that wind speeds and PM 10 concentrations are low when the wind is from the n orth is

evidence that emissions from the north do not contr ibute to PM 2.5 exceedances. This is unlike what might have been expected based on the proximit y and large emissions of the greater Phoenix metropolitan area, but these analyses provi de evidence that the Phoenix area does not

contribute to PM 2.5 exceedances at the Cowtown monitor.

Factor 7. Geography and Topography

The geography/topography analysis evaluates the phy sical features of the land that might have an effect on the airshed and, therefore, on the distri bution of PM 2.5 into and within the Pinal County

area.

The counties of Yavapai, Gila, Graham, and Cochise, which lie to the north and east of Pinal and Maricopa counties, are separated topographically fr om Pinal County by mountainous terrain, which impedes the transport of emissions. This len ds weight to EPA’s determination that the31

Yavapai, Gila, Graham, and Cochise counties are unl ikely contributors to violations at the

Cowtown monitor.

Figure 16 illustrates the general topographic featu res for Pinal County and the surrounding counties. Pinal County itself area has topographic al barriers significantly limiting air pollution transport within its airshed and from neighboring a irsheds, though these barriers are not absolute. Therefore, this factor provides some support for EP A’s suggested boundary for the nonattainment area. Pinal County generally has fai rly low relief and is at around 1,200 feet elevation, but it is punctuated by various mountain s and ranges having peaks from 3,000 to 5,000 feet. The mountain ranges generally run southeast- northwest, and form broad desert valleys. In the vicinity of the violating monitor, there are th e Sacaton Mountains to the east, rising to 2,235 feet, the Maricopa Mountains to the west to 2,400 f eet. Nearest is the southeastern tip of the Sierra Estrella Mountains, starting at about 10 mil es northwest of the monitor; they have peaks to 3,000 and 4,500 feet. To the north, between Pinal a nd Maricopa Counties, are the South Mountains rising to 2,500 feet; they run west-south west to east-northeast unlike most of the ranges. They are only 10 miles long, but along with the Sierra Estrella they form a partial barrier between Pinal and metropolitan Phoenix to the north . Approximately 50 miles east of the violating monitor, the eastern quarter of the count y becomes more mountainous, ultimately rising to some 6,000 feet near the eastern borders with Gi la and Graham Counties. Overall, the mountains within the county can redirect winds, and form a partial barrier to transport from the eastern portions of the County and from neighboring counties.

Approximately 12 miles north of the monitor is the Gila River channel, which in this area is dry. It descends toward the west-northwest before it joi ns the Salt River in Maricopa County, and ultimately the Colorado River. The general area aro und the monitor is in the valley of this river,

which is oriented in the same direction as that of the mountain ranges. As a result, air drainage flows towards the northwest are typically seen.

The presence of topographic barriers both outside a nd within Pinal County supports EPA’s suggested partial county boundary for the nonattain ment area and lends further support to a designation of “unclassifiable/attainment” to the s urrounding counties.32Figure 16. Topography33

Factor 8: Jurisdictional boundaries

In evaluating the jurisdictional factor, EPA consid ered the planning and organizational structure of Pinal County, the State of Arizona, and Indian c ountry to ensure that the implementation of controls within the prospective nonattainment area can be carried out in a cohesive manner. See Figure 17 for jurisdictional boundaries.

The Arizona Department of Environmental Quality has overall jurisdiction over environmental programs in the state of Arizona, as well as jurisd iction over certain source types, including smelters, refineries, and coal-fired power plants, and retains authority for regulating emissions from agricultural operations. Three Arizona countie s, Maricopa, Pima, and Pinal, have their own air pollution control programs and operate pursuant to agreements with ADEQ. The lead air quality planning agencies responsible for state imp lementation plans (SIPs) for Maricopa County and Pima County are the metropolitan planning organ izations (MPO), the Maricopa Association of Governments (MAG) and the Pima Association of Go vernments (PAG), respectively. There is no MPO and thus no lead air quality planning agency for SIP purposes in Pinal County. Therefore, ADEQ is responsible for developing SIPs for Pinal County. Pinal County has permitting authority, and can adopt control measure s by rule, but is preempted from adopting rules regulating certain categories of sources.

Four tribes are located in Pinal County. A portion of the Tohono O’odham Nation (TON) lies in southeastern Pinal County, south of the proposed no nattainment area. A portion of the San Carlos Apache tribal lands lie within the eastern p art of Pinal County, east of the proposed nonattainment area. Both the TON and San Carlos Ap ache lands are within the area EPA intends to designate “unclassifiable/attainment.” A s explained above, EPA is deferring designation of the two remaining tribes pending con sideration of issues unique to tribal lands and completion of formal consultation. The Ak-Chin Indi an Community tribal lands lie entirely within the County, and are encircled by the new non attainment area. The Gila River Indian Community tribal lands lie to the north of the nona ttainment area and straddle the PinalMaricopa boundary. Neither ADEQ nor the counties ha ve jurisdiction over tribal lands.

Of the four tribes, only the Gila River Indian Comm unity has treatment as a state (TAS) status for Clean Air Act section 107 designations, and an air quality monitoring network that reports quality-assured data to EPA’s Air Quality System (A QS). None of the tribes currently monitor

for PM 2.5

.34Figure 17. Jurisdictional Boundaries35

Factor 9: Level of control of emission sources

Under this factor, the existing level of control of emission sources is taken into consideration. The emissions data used by EPA in this technical an alysis and provided in Table 1 (under Factor 1) represent emissions levels taking into account a ny control strategies implemented in Pinal and nearby counties before 2005 on stationary, mobile, and area sources. Data are presented for

PM 2.5 components that are directly emitted (carbonaceous PM 2.5 and crustal PM 2.5 ) and for pollutants that react in the atmosphere to form fin e particles (e.g., SO 2 , NOx, VOC, and ammonia). EPA is not aware of any additional inform ation on emissions controls that is relevant to assessing sources contributing to the monitored violation.A-1 

## Appendix A Emissions in Pinal County: Primary PM 2.5 

## , NO
x 

## , NH 3 

## , SO 2 

## , VOCs.A-2

**Pinal County: Primary** PM 2.5 **(includes filterables + condensibles) Sources. 20 05 NEI version2.** 

**Source Category Emissions**  **(tpy) % of Total Primary** 

PM 2.5 **Emissions, Pinal County**

**Nonpoint**
Waste Disposal - Open Burning 886 21%
Agric - Crop Tilling & Livestock Dust 751 18%
Unpaved Roads 626 15%

Construction 547 13%

Wildfires 395 9%

Indus Process – NEC 220 5%

Paved Roads 152 4%
Other Nonpoint 105 2%

**Nonroad**

Non-Road Equipment - Diesel 166 4%
Planes, Trains, & Ships 64 2%
Non-Road Equipment - Gasoline 38 1%

**Onroad**

On-Road Vehicles - Diesel 116 3%

On-Road Vehicles - Gasoline 42 1%

**Point**

Misc. Point 102 2%

**TOTAL: 4,210 100%** A-3

**Pinal County: Nitrogen Oxides (** NO

x **) Sources. 2005 NEI version 2.**

**Source Category Emissions**  **(tpy) % of Total**  NO

x **Emissions, Pinal**

**County**

**Onroad**

On-Road Vehicles - Diesel 3,889 31%

On-Road Vehicles - Gasoline 3,715 30%

**Nonroad**

Planes, Trains, & Ships 2,275 18%
Non-Road Equipment - Diesel 1,775 14%
Non-Road Equipment - Gasoline 142 1%

**Nonpoint**

Waste Disposal - Open Burning 235 2%

Wildfires 113 1%

Fuel Comb - Industrial Boilers, ICEs 81 1%

Fuel Comb - Residential Fossil 65 1%
Other Nonpoint 35 0%

**Point**

Fuel Comb - Electric Utility 173 1%

Misc. Point 47 0%

**TOTAL: 12,545 100%** 

**Pinal County: Ammonia (** NH 3 **) Sources. 2005 NEI version 2.**

**Source Category Emissions**  **(tpy) % of Total** 

NH 3 **Emissions, Pinal**
**County**

**Nonpoint**

Livestock Waste 4,344 77%
Fertilizer Application 845 15%
Other Nonpoint 75 1%

**Onroad**

On-Road Vehicles - Gasoline 305 5%

On-Road Vehicles - Diesel 9 0%

**Point**

Fuel Comb - Electric Utility 65 1%

**Nonroad**

Misc. Nonroad 2 0%

**TOTAL: 5,646 100%** A-4

**Pinal County: Sulfur Dioxide (** SO 2 **) Sources. 2005 NEI version 2.**

**Source Category Emissions**  **(tpy) % of Total**  SO 2

**Emissions, Pinal County**

**Nonroad**

Non-Road Equipment - Diesel 244 32%
Planes, Trains, & Ships 163 22%
Non-Road Equipment - Gasoline 1 0%

**Nonpoint**

Fuel Comb - Industrial Boilers, ICEs 130 17%

Wildfires 48 6%
Other Nonpoint 21 3%

**Onroad**

On-Road Vehicles - Diesel 105 14%

On-Road Vehicles - Gasoline 38 5%

**Point**

Misc. Point 7 1%

**TOTAL: 757 100%** 

**Pinal County: Volatile Organic Compounds (VOC) Sour ces. 2005 NEI version 2.** 

**Source Category Emissions**  **(tpy) % of Total VOC** 

**Emissions, Pinal**
**County**

**Onroad**

On-Road Vehicles - Gasoline 3,539 38%

On-Road Vehicles - Diesel 200 2%

Nonroad
Non-Road Equipment - Gasoline 1,476 16%
Non-Road Equipment - Diesel 195 2%
Planes, Trains, & Ships 96 1%
**Nonpoint**

Wildfires 978 11%

Gas Stations 687 7%
Waste Disposal - Open Burning 642 7%

Solvent - Non-industrial 518 6%
Surface Coating - Industrial 206 2%

Miscellaneous Sources 186 2%
Surface Coating - Architectural 176 2%
Other Nonpoint 239 3%

**Point**

Misc. Point 80 1%

**TOTAL: 9,217 100%** A-5B-1 

## Appendix B Meteorological DataB-2B-3B-4B-5B-6