The North Carolina 

Fine Particulate Matter Attainment Demonstration 

for the 

Hickory and Greensboro/Winston-Salem/High Point 

Fine Particulate Matter Nonattainment Areas 

(Catawba, Davidson, and Guilford Counties) 

Prepared by: 

North Carolina Department of Environment and Natural Resources 

Division of Air Quality 

August 21, 2009
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

North Carolina Attainment Demonstration August 21, 2009 

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PREFACE 

This document contains North Carolina's attainment demonstration for the Hickory and 

Greensboro/Winston-Salem/High Point fine particulate matter nonattainment areas, which 

demonstrates that both of these areas will meet the National Ambient Air Quality Standards for 

fine particulate matter by April 5, 2010. These areas include the entire counties of Catawba, 

Davidson, and Guilford. 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

North Carolina Attainment Demonstration August 21, 2009 

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EXECUTIVE SUMMARY 

INTRODUCTION

Fine particulate matter, also known as fine particles and PM2.5, refers to airborne particles less 

than or equal to 2.5 micrometers (μm) in diameter. Fine particles are treated as though they are a 

single pollutant, but they come from many different sources and are composed of many different 

compounds. PM2.5 exposure adversely affects human health, especially respiratory and 

cardiovascular systems. Individuals particularly sensitive to PM2.5 exposure include children, 

people with heart and lung disease, and older adults. 

A variety of meteorological and geographic factors influence the concentration levels of fine 

particles, including both the regional and local distribution of urbanized areas, primary and 

precursor emissions sources, and natural features such as oceans and forests. PM2.5

concentrations can also be high and exceed the national ambient air quality standards (NAAQSs) 

for fine particulate matter at any time of the year. Therefore, the United States Environmental 

Protection Agency (USEPA) mandates the year round monitoring of PM2.5 concentrations 

throughout the country (40 CFR 58.App. D, 4.7). 

NATIONAL AMBIENT AIR QUALITY STANDARD

In 1997, the USEPA promulgated the primary (health) and secondary (welfare) NAAQSs for 

PM2.5 (40 CFR 50.7), setting the standard at a 15.0 micrograms per cubic meter (μg/m3) annual 

average and at a 65 μg/m3 daily or 24-hour average. A violation of the annual PM2.5 NAAQS 

occurs when the annual average PM2.5 concentration averaged over a three consecutive year 

period is equal to or greater than 15.1 μg/m3. A violation of the daily PM2.5 NAAQS occurs 

when the annual 98th percentile of daily PM2.5 concentration averaged over a three consecutive 

year period is equal to or greater than 66 μg/m3. The annual or daily PM2.5 design value for a 

nonattainment area is the highest design value for any monitor in that area. 

The USEPA designated areas as nonattainment for the annual and daily PM2.5 NAAQSs based 

upon air quality monitoring data measured during 2001, 2002 and 2003. The effective date of 

nonattainment designations was April 5, 2005. 

NATURE OF PROBLEM IN NORTH CAROLINA

In North Carolina, there were two areas designated as nonattainment for violating the annual 

PM2.5 standard (Figure 1). All areas of North Carolina met the daily PM2.5 standard. This PM2.5

attainment demonstration submittal covers the Hickory PM2.5 nonattainment area (Catawba 

County) and Greensboro/Winston-Salem/High Point PM2.5 nonattainment area (referred to as the 

Triad area and consists of Davidson and Guilford Counties) with respect to the violations of the 

annual PM2.5 standard. 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

North Carolina Attainment Demonstration August 21, 2009 

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Figure 1. Annual PM2.5 Nonattainment Boundaries for North Carolina 

When the annual PM2.5 concentrations in both nonattainment areas are analyzed by the 

percentages of their individual component species, the organic carbon (OC) and sulfate (SO4) 

components each account for approximately one-third of the total PM2.5 mass, the ammonium 

component makes up approximately ten percent of the total PM2.5 mass, and the remaining 

nitrate (NO3), elemental carbon, crustal material, and particle bound water components each 

contribute approximately five percent or less of the total PM2.5 mass. The percentages of species 

contribution fluctuate throughout the year with the most significant changes to SO4 and NO3. 

SO4 is more pronounced in the summertime or warm season months than during the wintertime. 

NO3 fluctuates from almost undetectable in the summertime to as much as ten percent 

contribution of the total PM2.5 mass during the coldest portion of the winter. 

The speciated analysis of the PM2.5 concentrations in the Hickory and Triad PM2.5 nonattainment 

areas demonstrates that the OC and SO4 components are the most important portions of the total 

PM2.5 mass throughout the year. OC is predominately attributed to biogenic emissions sources. 

SO4 is associated with sulfur dioxide (SO2) emissions. When evaluated across North Carolina 

and also throughout both nonattainment areas and surrounding regions, the SO2 is primarily from 

the point source sector. For this reason, SO2 emissions controls from point sources are believed 

to be the most appropriate strategy for addressing the PM2.5 nonattainment issues for Hickory 

and the Triad. 

CONTROLS APPLIED

Several control measures already in place or being implemented over the next few years will 

reduce stationary point, highway mobile, and non-road mobile sources emissions. The expected 

Federal and State control measures were modeled for the attainment year of 2009. 

The Federal control measures that were modeled included the Tier 2 vehicle standards; the 

heavy-duty gasoline and diesel highway vehicle standards; low sulfur gasoline and diesel fuels, 

large non-road diesel engines standards; the non-road spark-ignition engines and recreational 

engines standard; and the Clean Air Interstate Rule (CAIR). Due to the Court challenges of 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

North Carolina Attainment Demonstration August 21, 2009 

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CAIR in 2008, the USEPA will be making changes to this program soon. However, the existing 

CAIR rules will remain in place until the USEPA promulgates changes to the program. 

The State control measures that were modeled included the Clean Air Bill, in which the vehicle 

emissions inspection and maintenance program was expanded from 9 counties to 48; the NOx

SIP Call Rule, CAIR, and the Clean Smokestacks Act, which will significantly reduce SO2

emissions from the large electrical generation units with implementation beginning prior to the 

2009 attainment year and well in advance of the Federal Clean Air Interstate Rule. The Clean 

Smokestacks Act further requires the coal-fired power plants to meet an annual SO2 emissions 

cap without an option of emissions trading from outside of North Carolina. 

ATTAINMENT TEST RESULTS

A modeled attainment test was applied to the air quality modeling results to determine if the 

annual PM2.5 NAAQS will be met by the attainment year 2009. The baseline period for the air 

quality modeling was centered on 2002 or the midpoint of the three years used for nonattainment 

designations. 

For all FRM sites in the Hickory and Triad PM2.5 nonattainment areas, the future annual PM2.5

concentrations derived from the modeled attainment test were less than 15.0 μg/m3 (Table 1). 

Therefore, the modeling assessment indicated that both nonattainment areas will attain the 

annual PM2.5 NAAQS by 2009. 

Table 1. Current And Future Year Predicted Annual PM2.5 Concentrations 

County FRM Monitoring

Site

2001-2003, Current

Design Value

(μg/m3

)

2009, Future Year

Predicted Design

Value

(μg/m3

)

Catawba Hickory 15.5 13.1

Davidson Lexington 15.8 13.4

Guilford Mendenhall 14.0 11.5

The North Carolina Division of Air Quality (NCDAQ) provided a strong set of supplemental 

analyses further supporting that the Hickory and Triad PM2.5 nonattainment areas will attain the 

annual PM2.5 NAAQS by April 5, 2010. These analyses included evaluating the air quality 

modeling from an absolute percentage reduction perspective compared to the annual PM2.5

NAAQS, investigating current air quality data trends along with the emission reductions that 

have recently occurred, and considering air quality modeling results from other region and 

national modeling exercises. 

The NCDAQ believes that the modeling attainment demonstration, in conjunction with the 

supplemental analyses, provides the necessary evidence that the Hickory and Triad PM2.5

nonattainment areas will attain the annual PM2.5 NAAQS by the April 5, 2010 attainment date 

and furthermore continue to maintain the daily PM2.5 NAAQS. In fact, both nonattainment areas 

have already attained the 1997 annual PM2.5 standard with the 2006-2008 ambient air quality 

data, one year earlier than required.
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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TABLE OF CONTENTS 

PREFACE ii

EXECUTIVE SUMMARY iii

1.0 INTRODUCTION 1

1.1 What is fine particulate matter? ............................................................................................ 1

1.2 What is the National Ambient Air Quality Standard? .......................................................... 2

1.3 Nature of Problem in North Carolina ................................................................................... 2

1.4 Major Contributors to PM2.5 in the North Carolina Nonattainment Areas ........................... 5

1.5 Clean Air Act Requirements ................................................................................................. 6

2.0 SIGNIFICANCE OF PM2.5 PRECURSOR POLLUTANTS 7

2.1 PM2.5 Component Species Analysis ..................................................................................... 7

2.2 Attribution of Emissions Sources ......................................................................................... 9

2.3 Clean Air Fine Particulate Implementation Rule Presumptions on Precursor Pollutants ... 12

3.0 ATTAINMENT DEMONSTRATION METHODS AND INPUTS 13

3.1 Analysis Method ................................................................................................................. 13

3.2 Model Selection .................................................................................................................. 14

3.2.1 Selection of Air Quality Model .................................................................................... 14

3.2.2 Selection of Meteorological Model ............................................................................. 15

3.2.3 Selection of Emissions Processing System .................................................................. 18

3.3 Selection of the Modeling Year .......................................................................................... 19

3.4 Modeling Domains ............................................................................................................. 20

3.4.1 Horizontal Modeling Domain ...................................................................................... 20

3.4.2 Vertical Modeling Domain .......................................................................................... 22

3.5 Baseline Emissions Inventory ............................................................................................. 23

3.5.1 Stationary Point Sources .............................................................................................. 26

3.5.2 Stationary Area Sources ............................................................................................... 27

3.5.3 Off-Road Mobile Sources ............................................................................................ 28

3.5.4 Highway Mobile Sources ............................................................................................. 28

3.5.5 Biogenic Emission Sources .......................................................................................... 29

4.0 MODEL PERFORMANCE EVALUATION 30

4.1 Meteorological Model Performance ................................................................................... 30

4.2 Air Quality Model Performance ......................................................................................... 31

4.2.1 Modeling Performance Goals, and Criteria ................................................................. 32

4.2.2 Domain-Wide Model Performance .............................................................................. 33

4.2.3 Nonattainment Area Model Performance .................................................................... 35

4.2.4 Air Quality Model Performance Summary .................................................................. 37
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5.0 CONTROLS APPLIED 39

5.1 Federal Control Measures ................................................................................................... 39

5.1.1 Tier 2 Vehicle Standards .............................................................................................. 39

5.1.2 Heavy-Duty Gasoline and Diesel Highway Vehicles Standards ................................. 39

5.1.3 Large Non-road Diesel Engines Rule .......................................................................... 39

5.1.4 Non-road Spark-Ignition Engines and Recreational Engines Standard ....................... 40

5.1.5 NOx SIP Call in Surrounding States ............................................................................ 40

5.1.6 Clean Air Interstate Rule.............................................................................................. 40

5.2 State Control Measures ....................................................................................................... 41

5.2.1 Clean Air Bill ............................................................................................................... 41

5.2.2 NOx SIP Call Rule ....................................................................................................... 42

5.2.3 Clean Smokestacks Act ................................................................................................ 42

5.2.4 Open Burning Bans ...................................................................................................... 43

5.2.5 Clean Air Interstate Rule.............................................................................................. 43

6.0 ATTAINMENT DEMONSTRATION 44

6.1 Attainment Test Introduction .............................................................................................. 44

6.2 Attainment Test Results ...................................................................................................... 45

6.3 Supplemental Analyses ....................................................................................................... 45

6.3.1 Air Quality Modeling Metrics ..................................................................................... 46

6.3.2 Other Modeling Results ............................................................................................... 48

6.3.3 Air Quality Trends and Additional Reductions in Emissions ...................................... 49

6.4 Unmonitored Area Analysis ............................................................................................... 51

6.5 Data Access ......................................................................................................................... 53

7.0 CLEAN AIR ACT SECTION 172(c) REQUIREMENTS 54

7.1 Reasonable Available Control Measures ............................................................................ 54

7.2 Reasonable Further Progress .............................................................................................. 55

7.3 Actual Emissions Inventory ................................................................................................ 55

7.4 Periodic Emissions Inventory ............................................................................................. 55

7.5 Permit Program Requirements ............................................................................................ 55

7.6 Other Measures ................................................................................................................... 56

7.7 Compliance with Section 110(a)(2) .................................................................................... 56

7.8 Equivalent Techniques ........................................................................................................ 56

7.9 Contingency Measures ........................................................................................................ 56

8.0 MOTOR VEHICLE EMISSIONS BUDGETS 58

8.1 Transportation Conformity ................................................................................................. 58

8.2 Pollutants to be Considered ................................................................................................ 58

8.3 Highway Mobile Source Direct PM2.5 Emissions ............................................................. 59

8.4 Establishing PM2.5 and NOx Motor Vehicle Emission Budgets ......................................... 61

9.0 REFERENCES 63
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LIST OF FIGURES 

Figure 1. Annual PM2.5 Nonattainment Boundaries for North Carolina ....................................... iv

Figure 1.3-1. Annual PM2.5 Nonattainment Boundaries for North Carolina .................................. 3

Figure 1.3-2. PM2.5 Monitoring Sites In North Carolina ................................................................ 3

Figure 1.3-3. PM2.5 FRM Monitoring Sites in the Hickory and Triad Nonattainment Areas ....... 4

Figure 1.3-4. North Carolina PM2.5 Speciation for 2004 ................................................................ 5

Figure 2.1-1. 2002 PM2.5 Speciated Mass Contribution at Hickory Using SANDWICH .............. 8

Figure 2.1-2. 2002 PM2.5 Speciated Mass Contribution at Lexington Using SANDWICH ........... 8

Figure 2.1-3. 2002 PM2.5 Speciated Mass Contribution at Mendenhall Using SANDWICH ........ 9

Figure 2.2-1. Hickory PM2.5 Nonattainment Area SO2 Emissions in 2002 .................................. 10

Figure 2.2-2. Triad PM2.5 Nonattainment Area SO2 Emissions in 2002 ...................................... 11

Figure 2.2-3. North Carolina Total SO2 Emissions in 2002 ......................................................... 11

Figure 3.4.1-1. The MM5 and CMAQ_SOA 36-km Horizontal Domains ................................... 21

Figure 3.4.1-2. VISTAS 12-km Modeling Domain ...................................................................... 21

Figure 4.2.2-1. VISTAS STN Soccer Plots .................................................................................. 33

Figure 4.2.2-2. VISTAS STN Bugle Plots .................................................................................... 34

Figure 4.2.2-3. VISTAS FRM Soccer Plots ................................................................................. 34

Figure 4.2.2-4. VISTAS FRM Bugle Plots ................................................................................... 35

Figure 4.2.3-2. Hickory STN Bugle Plots..................................................................................... 36

Figure 4.2.3-3. Hickory FRM Soccer Plots .................................................................................. 37

Figure 4.2.3-4. Hickory FRM Bugle Plots .................................................................................... 37

Figure 5.2.1-1. North Carolina’s OBDII Test Phase-in Map ........................................................ 41

Figure 6.3.1-1. Area for which the Air Quality Metrics were Applied ........................................ 47

Figure 6.3.1-2. Percentage of Cell in PM2.5 Nonattainment Areas within Concentration 

Categories for 2002 and 2009. Table of Actual Values is Presented on the Right. ..................... 48

Figure 6.3.3-1. Annual PM2.5 Average Concentrations for the FRM Monitors in the Hickory and 

Triad Nonattainment Areas ........................................................................................................... 50

Figure 6.3.3-2. Annual SO2 Emissions From EGUs In NC .......................................................... 51

Figure 6.4-1. PM2.5 Monitors and Nonattainment Areas with Respect to the VISTAS 12km Grid 

Domain .......................................................................................................................................... 52

Figure 6.4-2. PM2.5 Monitors and 2009 Modeled Attainment Spatial Field ................................. 53
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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LIST OF TABLES 

Table 1. Current And Future Year Predicted Annual PM2.5 Concentrations .................................. v

Table 1.3-1. PM2.5 Concentrations and Design Values for the FRM monitors in the Hickory and 

Triad PM2.5 Nonattainment Areas ................................................................................................... 4

Table 3.4.1-1: Vertical Layer Definition For MM5 and CMAQ .................................................. 23

Table 3.5-1. 2002 Annual Emission Summaries .......................................................................... 25

Table 4.2.1-1. Established Model Performance Goals and Criteria for the PM2.5 Component 

Species .......................................................................................................................................... 32

Table 5.2.1-1 OBDII Phase-in Effective Dates ............................................................................ 42

Table 6.2-1. Quarterly Mean and Annual Mean PM2.5 Mass Estimates for 2009 ........................ 45

Table 6.3.1-1. Number of Cells within Concentration Bins. Increases (decreases) in the Number 

of Cells within the Bins are Noted by Red (Blue) Coloration in the Last Column. ..................... 48

Table 6.3.2-1. USEPA’s CAIR Modeling Results ........................................................................ 49

Table 6.3.3-1. Annual Average PM2.5 Concentrations for the Past 10 Years ............................... 49

Table 6.3.3-2. Three Year Design Values for the FRM Monitors in the Hickory and Triad PM2.5

Nonattainment Areas .................................................................................................................... 50

Table 8.4-1. County Level PM2.5 Highway Mobile Emissions for 2009 ...................................... 61

Table 8.4-2. County Level NOX Highway Mobile Emissions for 2009 ....................................... 61

Table 8.4-3. County Level PM2.5 MVEBs for 2009 ..................................................................... 62

Table 8.4-4. County Level NOx MVEBs for 2009 ....................................................................... 62
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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LIST OF APPENDICES 

Appendix A: Policy and Memorandums 

Appendix B: Stakeholders Correspondence Regarding Motor Vehicle Emissions Budgets 

Appendix C: Air Quality Data 

Appendix D: Modeling Protocol 

Appendix E: Emissions Inventory Summary 

Appendix F: Emissions Inventory Documentation 

Appendix G: Emissions Inventory Quality Assurance Project Plan 

Appendix H: Emissions Modeling and Related 

Appendix I: Meteorological Development Documentation 

Appendix J: Model Performance Evaluation 

Appendix K: Modeling Results 

Appendix L: Attainment Test 

Appendix M: Adopted State Measures 

Appendix N: Contingency Measures Documentation 

Appendix O: Insignificance of NH3 and VOCs to PM2.5 Attainment in North Carolina 

Appendix P: Supporting Documentation from VISTAS and ASIP 

Appendix Q: Public Notice Report, Comments Received, and Responses 
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1.0 INTRODUCTION 

1.1 What is fine particulate matter? 

Fine particulate matter, also known as fine particles and PM2.5, refers to airborne particles less 

than or equal to 2.5 micrometers (μm) in diameter. Fine particles are treated as though they are a 

single pollutant, but they come from many different sources and are composed of many different 

compounds. PM2.5 exposure adversely affects human health, especially respiratory and 

cardiovascular systems. Individuals particularly sensitive to PM2.5 exposure include children, 

people with heart and lung disease, and older adults. 

PM2.5 can be liquid, solid, or can have a solid core surrounded by liquid. PM2.5 can include 

material produced by combustion, photochemical reactions, and can contain salt from sea spray 

and soil-like particles. Particles are distinguished based on the method of formation. Primary 

particles are particles directly emitted into the atmosphere and retain the same chemical 

composition as when they were released. Secondary particles are those formed through chemical 

reactions involving atmospheric oxygen, water vapor, hydroxyl radical, nitrates, sulfur dioxide 

(SO2), oxides of nitrogen (NOx), and organic gases from natural and anthropogenic sources. 

PM2.5 can therefore be composed of varying amount of different species, including: 

• Sulfates 

• Nitrates (usually found in the form of ammonium nitrate) 

• Ammonium 

• Hydrogen ion 

• Particle bound water 

• Elemental carbon 

• Organic compounds 

o Primary organic species (from cooking and combustion) 

o Secondary organic compounds 

• Crustal material (includes calcium, aluminum, silicon, magnesium, and iron) 

• Sea salt (generally only found at coastal monitoring sites) 

• Transitional metals 

• Potassium (generally from wood burning or cooking) 

The most significant sources of PM2.5 and its precursors are coal-fired power plants, industrial 

boilers and other combustion sources. These emissions are often transported over large 

distances. Other sources of PM2.5 emissions include mobile sources, area sources, biogenic, 

fires, windblown dust, and oceans. 

A variety of meteorological and geographic factors influence the concentration levels of fine 

particles, including both the regional and local distribution of urbanized areas, primary and 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

North Carolina Attainment Demonstration August 21, 2009 

2

precursor emissions sources, and natural features such as oceans and forests. PM2.5

concentrations can also be high and exceed the national ambient air quality standards (NAAQSs) 

for fine particulate matter at any time of the year. Therefore the United States Environmental 

Protection Agency (USEPA) mandates the year round monitoring of PM2.5 concentrations 

throughout the country (40 CFR 58.App. D, 4.7). 

1.2 What is the National Ambient Air Quality Standard? 

In 1997, the USEPA promulgated the primary (health) and secondary (welfare) NAAQSs for 

PM2.5 (40 CFR 50.7), setting the standard at a 15.0 micrograms per cubic meter (μg/m3

) annual 

average and at a 65 μg/m3 daily or 24-hour average. A violation of the annual PM2.5 NAAQS 

occurs when the annual average PM2.5 concentration averaged over a three consecutive year 

period is equal to or greater than 15.1 μg/m3. A violation of the daily PM2.5 NAAQS occurs 

when the annual 98th percentile of daily PM2.5 concentration averaged over a three consecutive 

year period is equal to or greater than 66 μg/m3. The annual or daily PM2.5 design value for a 

nonattainment area is the highest design value for any monitor in that area. 

Since the 1977 amendments to the Clean Air Act (CAA), areas of the country that violated the 

ambient standard for a particular pollutant were formally designated as nonattainment for that 

pollutant. This formal designation concept was retained in the 1990 Amendments (CAAA). 

With the implementation of the PM2.5 standard, areas could be designated under Section 172 of 

the CAAA (subpart 1) and have five years from designation to attain the standard. 

The USEPA designated areas as nonattainment for the annual and daily PM2.5 NAAQSs based 

upon air quality monitoring data measured during 2001, 2002 and 2003. The effective date of 

nonattainment designations was April 5, 2005. 

1.3 Nature of Problem in North Carolina 

In North Carolina, there were two areas designated as nonattainment for violating the annual 

PM2.5 standard (Figure 1.3-1). All areas of North Carolina met the daily PM2.5 standard. This 

PM2.5 attainment demonstration submittal covers the Hickory PM2.5 nonattainment area 

(Catawba County) and Greensboro/Winston-Salem/High Point PM2.5 nonattainment area 

(referred to as the Triad area and consists of Davidson and Guilford Counties) with respect to the 

violations of the annual PM2.5 standard. 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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Figure 1.3-1. Annual PM2.5 Nonattainment Boundaries for North Carolina 

Figure 1.3-2 displays the distribution of the PM2.5 monitoring sites across North Carolina. A 

closer view of the PM2.5 federal reference method (FRM) monitoring sites in the Hickory and 

Triad PM2.5 nonattainment areas is found in Figure 1.3-3. The Hickory monitoring site is the 

only FRM monitor in the Hickory PM2.5 nonattainment area. There are two FRM monitoring 

sites, Lexington and Mendenhall, in the Triad PM2.5 nonattainment area. 

Figure 1.3-2. PM2.5 Monitoring Sites In North Carolina 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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Figure 1.3-3. PM2.5 FRM Monitoring Sites in the Hickory and Triad Nonattainment Areas 

Table 1.3-1 contains the quarterly and annual average PM2.5 concentrations for the FRM 

monitors in the PM2.5 nonattainment areas for the three-year period used in the nonattainment 

designation determinations. Table 1.3-1 also presents the 2001-2003 PM2.5 design value for the 

FRM monitors based on these quarterly and annual averages. The historic quarterly, yearly, and 

design value air quality data for the FRM monitors in both PM2.5 nonattainment areas can be 

found in Appendix C. 

Table 1.3-1. PM2.5 Concentrations and Design Values for the FRM monitors 

in the Hickory and Triad PM2.5 Nonattainment Areas 

County FRM Monitoring

Site Year

1st 

Quarter

(Q1)

2nd 

Quarter

(Q2)

3rd 

Quarter

(Q3)

4th 

Quarter

(Q4)

Annual

Average

Design 

Value

2001 15.3 16.6 18.8 13.2 16.0

2002 13.3 14.3 21.1 12.7 15.4

2003 12.9 16.1 19.3 11.8 15.0

2001 14.8 18.6 18.8 13.6 16.5

2002 14.9 15.0 19.3 14.3 15.9

2003 12.6 16.1 19.1 12.9 15.2

2001 12.0 16.7 18.0 12.9 14.9

2002 11.7 13.1 18.3 11.7 13.7

2003 11.6 13.6 16.5 11.7 13.3

15.5

15.8

14.0

Catawba

Davidson

Guilford

Hickory

Lexington

Mendenhall
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As mentioned in Section 1.1, PM2.5 is composed of many species from varying sources. 

Figure 1.3-4 presents the North Carolina statewide averaged PM2.5 speciation data from the 

speciation trends network (STN) monitors for the year 2004. The figure presents sulfates (SO4) 

and organic carbons (OC) as the main contributors to PM2.5, each with 29%; ammonium (NH4) 

contributes 11%; nitrates (NO3) contribute 7%; elemental carbon (EC) is approximately 4%; and 

crustal material is 3% of the total PM2.5 mass. The “other” portion of the PM2.5 that accounts for 

17% of the mass can be attributed to water (H2O), sea salts, and other trace materials captured 

with the STN monitors. 

Figure 1.3-4. North Carolina PM2.5 Speciation for 2004 

1.4 Major Contributors to PM2.5 in the North Carolina Nonattainment Areas 

When the annual PM2.5 concentrations in both nonattainment areas are analyzed by the 

percentages of their individual component species, a similar distribution of components are 

found. The OC and SO4 components each account for approximately one-third of the total PM2.5

mass; NH4 makes up approximately ten percent of the total PM2.5 mass; and the remaining NO3, 

EC, crustal material, and particle bound water components each contribute approximately five 

percent or less of the total PM2.5 mass. Individual plots of the speciated PM2.5 data (similar to 

Figure 1.3-4) from the three PM2.5 monitoring locations in the nonattainment areas can be found 

in Appendix C. 

The percentages of species contribution fluctuate throughout the year with the most significant 

changes to SO4 and NO3. SO4 is more pronounced in the summertime or warm season months 

than during the wintertime. NO3 fluctuates from almost undetectable in the summertime to as 

much as ten percent contribution of the total PM2.5 mass during the coldest portion of the winter. 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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The speciated analysis of the PM2.5 concentrations in the Hickory and Triad PM2.5 nonattainment 

areas demonstrates that the OC and SO4 components are the most important portions of the total 

PM2.5 mass throughout the year. OC is predominately attributed to biogenic emissions sources. 

SO4 is associated with SO2 emissions. When evaluated across North Carolina and also 

throughout both nonattainment areas and surrounding regions, the SO2 is primarily from the 

point source sector. For this reason, SO2 emissions controls from point sources are believed to 

be the most appropriate strategy for addressing the current PM2.5 nonattainment issues for 

Hickory and the Triad. 

Further details on the nature of the PM2.5 problem in both PM2.5 nonattainment areas are 

discussed in Section 2 and can also be found in the Conceptual Description of Fine Particulate 

Matter in North Carolina section of Appendix D.1. 

1.5 Clean Air Act Requirements 

Section 172(c) as amended, contains the general requirements for nonattainment areas. These 

requirements are listed below and are discussed in more detail in Section 7. 

Section 172(c) Nonattainment Plan Provisions

 (1) Reasonable available control measures (RACM) 

 (2) Reasonable further progress (RFP) 

 (3) Actual emissions inventory and periodic emissions inventory 

 (4) New source review (NSR) 

 (5) Permit requirements for new and modified sources 

 (6) Other measures as may be necessary to provide attainment by specified 

attainment date 

 (7) Compliance with Section 110(a)(2) 

 (8) Equivalent techniques 

 (9) Contingency measures 
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2.0 SIGNIFICANCE OF PM2.5 PRECURSOR POLLUTANTS 

As suggested in the Section 1.4, SO2 emissions are believed to be the most appropriate strategy 

for addressing the 1997 PM2.5 NAAQS for the Hickory and Triad nonattainment areas. This 

finding is based on several factors including: 

• An analysis of the percentage contribution of the PM2.5 component species annually 

and seasonally within the nonattainment areas 

• Attribution of emissions sources to these PM2.5 component species 

• Clean Air Fine Particulate Implementation Rule presumptions on precursor pollutants 

2.1 PM2.5 Component Species Analysis 

To fully understand the nature of the PM2.5 nonattainment issues in the Hickory and Triad 

nonattainment areas, it is important to analyze the percentage contribution of the individual 

PM2.5 component species, both from an annual perspective and seasonally throughout the year. 

Unfortunately, the FRM monitoring sites only provide a total mass PM2.5 concentration and do 

not provide any information concerning the speciated breakdown of various components. A 

separate PM2.5 monitoring network, STN, does allow for the speciation of these components, but 

the STN PM2.5 concentration data is not directly comparable to the FRM PM2.5 concentration 

data due to slight difference in the monitoring methodology. This creates an issue in using raw 

STN PM2.5 data in an attainment demonstration, because it is not absolutely equivalent to the 

FRM PM2.5 data of which the nonattainment is based and of which attainment will ultimately be 

evaluated. 

To address this issue, Neil Frank with the USEPA developed an approach to use the raw STN 

PM2.5 data to appropriately estimate the components of PM2.5 as measured by the FRM monitors. 

The approach is termed the “Sulfate, Adjusted Nitrate, Derived Water, Inferred Carbonaceous 

material balance approacH” method or SANDWICH (Frank, 2006). The SANDWICH approach 

is discussed in greater detail in Appendix L. 

Using the SANDWICH approach, it is now possible to analyze the percentage contribution of the 

individual PM2.5 component species relative to the total FRM PM2.5 mass. Figures 2.1-1 through 

2.1-3 present the speciated mass contributions of the component species at the Hickory, 

Lexington, and Mendenhall monitoring sites, respectively. The speciated mass contributions 

displayed are for the 2002 baseline year. Figures 2.1-1 through 2.1-3 illustrate daily speciated 

mass contributions for each day of the 2002 calendar year (expressed in Julian days) from left to 

right, with the farthest right bar of the charts representing the 2002 annual averaged speciated 

mass contributions. 
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0

5

10

15

20

25

30

35

40

4 28 40 52 70 82 94 106 118 130 142 154 166 178 196 208 220 232 244 256 268 280 292 304 316 328 340 352 364 _ Avg.

Julian Day

Mass (μg m-3)

Crustal

EC

OC

H2O

NH4

NO3

SO4

Figure 2.1-1. 2002 PM2.5 Speciated Mass Contribution at Hickory Using SANDWICH 

0

5

10

15

20

25

30

35

40

16 28 40 52 64 76 94 106 118 130 142 154 166 178 190 202 214 226 238 250 262 274 286 298 310 322 334 346 358 _ Avg.

Julian Day

Mass (μg m-3)

Crustal

EC

OC

H2O

NH4

NO3

SO4

Figure 2.1-2. 2002 PM2.5 Speciated Mass Contribution at Lexington Using SANDWICH 
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0

5

10

15

20

25

30

35

40

4 16 28 40 52 64 76 100 112 124 136 154 166 178 190 202 214 226 238 250 262 274 286 310 322 334 346 358 _ Avg.

Julian Day

Mass (μg m-3)

Crustal

EC

OC

H2O

NH4

NO3

SO4

Figure 2.1-3. 2002 PM2.5 Speciated Mass Contribution at Mendenhall Using SANDWICH 

From each of the three 2002 PM2.5 speciated mass contribution plots, it is clear that SO4 and OC 

are the dominant PM2.5 components throughout the year. SO4 is most pronounced during the 

summertime, but remains a reasonably important component of the total PM2.5 mass in any of the 

seasons. NH4 and H2O are less dominant than SO4 and OC but are relatively consistent in each 

season. EC and crustal material are much less prevalent at any time of the year. Finally, NO3

contributions are almost undetectable in the summertime to as much as ten percent contribution 

of the total PM2.5 mass during the wintertime. 

2.2 Attribution of Emissions Sources 

Precursor pollutants to PM2.5 can be emitted directly, such as in smoke from a fire, or they can 

form from chemical reactions of gases such as SO2, nitrogen dioxide and some organic gases. 

Sources of these precursor pollutants include power plants, gasoline and diesel engines, wood 

combustion, and high-temperature industrial processes such as smelters and steel mills. Other 

sources of the PM2.5 precursor pollutants include mobile sources, area sources, biogenic, fires, 

windblown dust, and oceans. 

The speciated analysis of the PM2.5 concentrations in the Hickory and Triad PM2.5 nonattainment 

areas presented above demonstrates that the OC and SO4 components are the most important 

portions of the total PM2.5 mass throughout the year at all three monitoring locations. OC is 

predominately attributed to biogenic volatile organic compound (VOC) emissions. SO4 is 

associated with SO2 emissions. NH4 can have a variety of sources including both industrial and 

natural processes. What little NO3 is present in the PM2.5 nonattainment areas throughout the 

year are attributed to NOx from combustion sources. Of all these components and associated 

emission sources, SO4 is the only dominant PM2.5 component species found throughout the year 
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that is attributed to a set of emissions source (SO2) that are controllable through regulatory 

actions by the North Carolina Division of Air Quality (NCDAQ). 

When evaluated throughout both nonattainment areas and across North Carolina, SO2 is 

primarily from the point source sector. Figures 2.2-1 and 2.2-2 present the SO2 emissions from 

the various source sectors in the Hickory and Triad PM2.5 nonattainment areas, respectively. 

Both figures are presented on same vertical axis scales to illustrate the significance of a single 

point source facility that is inside of the Hickory nonattainment area and immediately adjacent 

and upwind of the Triad nonattainment area. The magnitude of the point source sector 

completely masks the SO2 emissions from all other source categories. When SO2 emissions by 

source category are evaluated across North Carolina (Figure 2.2-3), the point source emissions 

are 6 times larger than emissions contained in either of the nonattainment area SO2 emissions 

plots. Again, the magnitude of the point source sector completely masks the SO2 emissions from 

all other source sectors. 

Figure 2.2-1. Hickory PM2.5 Nonattainment Area SO2 Emissions in 2002 
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Figure 2.2-2. Triad PM2.5 Nonattainment Area SO2 Emissions in 2002 

Figure 2.2-3. North Carolina Total SO2 Emissions in 2002 
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2.3 Clean Air Fine Particulate Implementation Rule Presumptions on Precursor Pollutants 

The USEPA’s Clean Air Fine Particulate Implementation Rule (72 FR 20586), commonly 

referred to as the PM2.5 Implementation Rule, guides States as they develop state implementation 

plans in response to annual and/or daily PM2.5 nonattainment. It establishes a hierarchy of 

precursor pollutants: SO2 is always considered a precursor, NOx is presumptively a precursor, 

and VOCs and ammonia are presumed not to be precursors. The State of North Carolina is 

following the assertions and presumptions of significant and insignificant precursor pollutants 

established in the PM2.5 Implementation Rule in this attainment demonstration. Further 

discussion on the significant or insignificance of the various precursor pollutants is discussed in 

Appendix O. 
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3.0 ATTAINMENT DEMONSTRATION METHODS AND INPUTS 

The attainment modeling for the Hickory and Triad PM2.5 nonattainment areas was performed in 

conjunction with the regional haze modeling being done by Southeast Regional Planning 

Organization (RPO), Visibility Improvement State and Tribal Association of the Southeast 

(VISTAS) and the PM2.5 and ozone (O3) modeling being done by the Association of 

Southeastern Integrated Planning (ASIP). VISTAS and ASIP are managed by the ten Southeast 

states (Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, 

Tennessee, Virginia and West Virginia). Since the VISTAS/ASIP regional modeling utilized 

annual simulations and includes modeling for the attainment year required for the Hickory and 

Triad PM2.5 nonattainment areas, the NCDAQ decided to use this modeling for its attainment 

demonstration. The sections below outline the methods and inputs used by VISTAS/ASIP for 

the regional modeling.

3.1 Analysis Method 

The modeling analysis is a complex technical evaluation that begins by selection of the modeling 

system. VISTAS decided to use the following modeling system: 

• Meteorological Model: The Pennsylvania State University/National Center for 

Atmospheric Research (PSU/NCAR) Mesoscale Meteorological Model (MM5) is a 

nonhydrostatic, prognostic meteorological model routinely used for urban- and regionalscale photochemical, fine particulate matter, and regional haze regulatory modeling 

studies. 

• Emissions Model: The Sparse Matrix Operator Kernel Emissions (SMOKE) modeling 

system is an emissions modeling system that generates hourly gridded speciated emission 

inputs of mobile, non-road mobile, area, point, fire and biogenic emission sources for 

photochemical grid models. 

• Air Quality Model: The USEPA’s Models-3/ Community Multiscale Air Quality 

(CMAQ) modeling system is a “One-Atmosphere” photochemical grid model capable of 

addressing O3, particulate matter, visibility and acid deposition at regional scale for 

periods up to one year. 

Additionally, an historical year is selected to model that represents typical meteorological 

conditions in the Southeast when high ozone, high PM2.5 and poor visibility are observed 

throughout the region. Once the historical year is selected, meteorological inputs are developed 

using the meteorological model. Emission inventories are also developed for the historical year 

and processed through the emissions model. These inputs are used in the air quality model to 

predict ozone, PM2.5 and visibility, with the results compared to the historic data. The model 

performance is evaluated by comparing the modeled predicted data to the historic air quality 

data. 

Once model performance is deemed adequate, typical baseline and future year emissions are 

processed through the emissions model. For this demonstration, the baseline year was 2002, 

which corresponds with the same year as the historic meteorology used in the modeling. The 

attainment future year the NCDAQ is using for this demonstration is 2009, since the mandatory 

attainment date for the Hickory and Triad PM2.5 nonattainment areas is April 5, 2010. The 
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attainment date is set prior to the completion of the 2010 calendar year; therefore the attainment 

of the NAAQS would have to be met by the end of 2009. These emissions are processed through 

the air quality model with the meteorological inputs. The air quality modeling results are used to 

determine a relative reduction in future PM2.5 concentrations, which is used in the attainment 

demonstration. 

The complete modeling protocol used by the NCDAQ for this analysis can be found in 

Appendix D.1. For additional reference, the VISTAS/ASIP modeling protocol can be found in 

Appendix D.2. 

3.2 Model Selection 

To ensure that a modeling study is defensible, care must be taken in the selection of the models 

to be used. The models selected must be scientifically appropriate for the intended application 

and be freely accessible to all stakeholders. Scientifically appropriate means that the models 

address important physical and chemical phenomena in sufficient detail, using peer-reviewed 

methods. Freely accessible means that model formulations and coding are freely available for 

review and that the models are available to stakeholders, and their consultants, for execution and 

verification at little or no cost. 

The following sections outline the criteria for selecting a modeling system that is both defensible 

and capable of meeting the study's goals. These criteria were used in selecting the modeling 

system used for this modeling attainment demonstration. 

3.2.1 Selection of Air Quality Model 

3.2.1.1 Criteria 

For an air quality model to qualify as a candidate for use in an attainment demonstration, a State 

needs to show that it meets several general criteria: 

• The model has received a scientific peer review. 

• The model can be demonstrated applicable to the problem on a theoretical basis. 

• Data bases needed to perform the analysis are available and adequate. 

• Available past appropriate performance evaluations have shown the model is not biased 

toward underestimates or overestimates. 

• A protocol on methods and procedures to be followed has been established. 

• The developer of the model must be willing to make the source code available to users 

for free or for a reasonable cost, and the model cannot otherwise be proprietary. 

3.2.1.2 Overview of CMAQ 

The air quality model selected for this study was CMAQ version 4.5, which was the most recent 

release at the point the attainment modeling exercise started. For more than a decade, the 

USEPA has been developing the Models-3 CMAQ modeling system with the overarching aim of 

producing a “One-Atmosphere” air quality modeling system capable of addressing ozone, fine 
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particulate matter, visibility and acid deposition within a common platform. The original 

justification for the Models-3 development emerged from the challenges posed by the CAAA 

and the USEPA’s desire to develop an advanced modeling framework for “holistic” 

environmental modeling utilizing state-of-science representations of atmospheric processes in a 

high performance computing environment. The USEPA completed the initial stage of 

development with Models-3 and released the CMAQ model in mid 1999 as the initial operating 

science model under the Models-3 framework. 

Another reason for choosing CMAQ as the atmospheric model is the ability to do oneatmospheric modeling. Since the NCDAQ will be using the same modeling exercise for the 

ozone and PM2.5 attainment demonstration state implementation plans (SIPs), as well as the 

regional haze SIP, having a model that can handle both ozone and particulate matter is essential. 

A number of features in CMAQ’s theoretical formulation and technical implementation make the 

model well suited for annual PM2.5 modeling. 

CMAQ contains three options for treating secondary organic aerosol (SOA), latest being the 

Secondary Organic Aerosol Model (SORGAM) that was updated in August 2003 to be a 

reversible semi-volatile scheme whereby VOC emissions can be converted to condensable gases 

that can then form SOA and then evaporate back into condensable gases depending on 

atmospheric conditions. 

The CMAQ chemical-transport model processor (CTM) requires the following inputs: 

• Three-dimensional hourly meteorological fields that will be generated by the CMAQ 

MCIP2.3 processing of the BAMS MM5 output 

• Three-dimensional hourly emissions generated by SMOKE 

• Initial conditions and boundary conditions 

• Topographic information 

• Land use categories 

• Photolysis rates generated by the CMAQ JPROC processor 

The configuration used for this modeling demonstration, as well as a more detailed description of 

the CMAQ_SOA (CMAQ version with SOA modification) model, can be found in Appendix 

D.1. The resulting model performance evaluation can be found in Appendix J. 

3.2.2 Selection of Meteorological Model 

3.2.2.1 Criteria 

Meteorological models, either through objective, diagnostic, or prognostic analysis, extend 

available information about the state of the atmosphere to the grid upon which photochemical 

grid modeling is to be carried out. The criteria for selecting a meteorological model are based on 

both the models ability to accurately replicate important meteorological phenomena in the region 

of study, and the model's ability to interface with the rest of the modeling systems, particularly 

the air quality model. With these issues in mind, the following criteria were established for the 

meteorological model to be used in this study: 
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• Non-Hydrostatic Formulation 

• Reasonably current, peer reviewed formulation 

• Simulates Cloud Physics 

• Publicly available at no or low cost 

• Output available in I/O API format 

• Supports Four Dimensional Data Assimilation 

• Enhanced treatment of Planetary Boundary Layer heights for AQ modeling 

3.2.2.2 Overview of MM5 

The non-hydrostatic MM5 model is a three-dimensional, limited-area, primitive equation, 

prognostic model that has been used widely in regional air quality model applications. The basic 

model has been under continuous development, improvement, testing, and open peer-review for 

more than 20 years and has been used worldwide by hundreds of scientists for a variety of 

mesoscale studies. 

MM5 uses a terrain-following non-dimensionalized pressure, or "sigma", vertical coordinate 

similar to that used in many operational and research models. In the non-hydrostatic MM5, the 

sigma levels are defined according to the initial hydrostatically balanced reference state so that 

the sigma levels are also time-invariant. The gridded meteorological fields produced by MM5 

are directly compatible with the input requirements of “one atmosphere” air-quality models using 

this coordinate. MM5 fields can be easily used in other regional air quality models with different 

coordinate systems by performing a vertical interpolation, followed by a mass-conservation 

readjustment. 

Distinct planetary boundary layer parameterizations are available for air-quality applications, 

both of which represent sub-grid-scale turbulent fluxes of heat, moisture and momentum. One 

scheme uses a first-order eddy diffusivity formulation for stable and neutral environments and a 

modified first-order scheme for unstable regimes. The other scheme uses a prognostic equation 

for the second-order turbulent kinetic energy, while diagnosing the other key boundary layer 

terms. 

Initial and lateral boundary conditions are specified for real-data cases from mesoscale threedimensional analyses performed at 12-hour intervals on the outermost grid mesh selected by the 

user. Surface fields are analyzed at three-hour intervals. The GEOS-CHEM global chemical 

transport model was run for 2002 to develop the initial and boundary conditions. More details 

on the GEOS-CHEM model used in this attainment demonstration can be found in Appendix P . 

A Cressman-based technique is used to analyze standard surface and radiosonde observations, 

using the National Meteorological Center's spectral analysis, as a first guess. The lateral 

boundary data are introduced using a relaxation technique applied in the outermost five rows and 

columns of the coarsest grid domain. 

Results of detailed performance evaluations of the MM5 modeling system in regulatory air 

quality application studies have been widely reported in the literature (e.g., Emery et al., 1999; 
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Tesche et al., 2000, 2003) and many have involved comparisons with other prognostic models 

such as the Regional Atmospheric Modeling System (RAMS) and the Systems Application 

International Mesoscale Model. The MM5 enjoys a far richer application history in regulatory 

modeling studies compared with RAMS or other models. Furthermore, in evaluations of these 

models in over 60 recent regional scale air quality application studies since 1995, it has generally 

been found that the MM5 model tends to produce somewhat better photochemical model inputs 

than alternative models. 

The databases required for setting up, exercising, and evaluating the MM5 model for the 2002 

season consist of various fixed and variable inputs. 

• Topography: High resolution (e.g., 30 sec to 5 min) topographic information derived 

from the Geophysical Data Center global datasets from the NCAR terrain databases are 

available for prescribing terrain elevations throughout the 36-km and 12-km grid domain. 

• Vegetation Type and Land Use: Vegetation type and land use information on the 36-km 

grid may be developed using the PSU/NCAR 10 min. (~18.5 km) databases while for the 

12-km grids, the United States Geological Survey (USGS) data are available. 

• Atmospheric Data: Initial and boundary conditions to the MM5 may be developed from 

operationally analyzed fields derived from the National Centers for Environmental 

Prediction (NCEP) Eta model (40 km resolution) following the procedures outlined by 

Stauffer and Seaman (1990). These 3-hour synoptic-scale initialization data include the 

horizontal wind components (u and v), temperature, and relative humidity at the standard 

pressure levels, plus sea-level pressure and ground temperature. Here, ground 

temperature represents surface temperature over land and sea-surface temperature over 

water. 

• Water Temperature: Water temperatures required on both 36-km and 12-km grids can be 

derived from the Eta skin temperature variable. These temperatures are bi-linearly 

interpolated to each model domain and, where necessary, filtered to smooth out 

irregularities. 

• Clouds and Precipitation: While the non-hydrostatic MM5 treats cloud formation and 

precipitation directly through explicit, resolved-scale, and parameterized sub-grid scale 

processes, the model does not require precipitation or cloud input. The potential for 

precipitation and cloud formation enters through the thermodynamic and cloud processes 

formulations in the model. The only precipitation-related input required is the initial 

mixing ratio field that is developed from the National Weather Service (NWS) and 

National Meteorological Center (NMC) datasets.

• Multi-Scale Four Dimensional Data Assimilation (FDDA): The standard "multi-scale" 

data assimilation strategy to be used on the 36-km and 12-km grids will objectively 

analyze three-dimensional fields produced every 3 hours from the NWS rawinsonde 

wind, temperature, and mixing ratio data, and similar analyses are generated every three 

hours from the available NWS surface data. 

The configuration used for this modeling demonstration, as well as a more detailed description of 

the MM5 model, can be found in Appendix I as well as Section 4.6 of the Modeling Protocol 

(Appendix D.1). 
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3.2.3 Selection of Emissions Processing System 

3.2.3.1 Criteria 

The principal criterion for an emissions processing system is that it accurately prepares 

emissions files in a format suitable for the photochemical grid model being used. The following 

list includes clarification of this criterion and additional desirable criteria for effective use of the 

system. 

• File System Compatibility with the I/O API 

• File Portability 

• Ability to grid emissions on a Lambert Conformal projection 

• Report Capability 

• Graphical Analysis Capability 

• MOBILE6 Mobile Source Emissions 

• Biogenic Emissions Inventory System version 2 (BEIS-3) 

• Ability to process emissions for the proposed domain in a reasonable amount of time. 

• Ability to process control strategies 

• Little or no cost for acquisition and maintenance 

• Expandable to support other species and mechanisms 

3.2.3.2 Overview of SMOKE 

The Sparse Matrix Operator Kernel Emissions (SMOKE) Modeling System was originally 

developed at the Micro-computing Center of North Carolina. As with most emissions models, 

SMOKE is principally an emission processing system and not a true emissions modeling system

in which emissions estimates are simulated from “first principles”. This means that, with the 

exception of mobile and biogenic sources, its purpose is to provide an efficient, modern tool for 

converting emissions inventory data into the formatted emission files required by an air quality 

simulation model. For mobile sources, SMOKE actually simulates emissions rates based on 

input mobile-source activity data, emission factors and outputs from transportation traveldemand models. 

SMOKE was originally designed to allow emissions data processing methods to utilize emergent 

high-performance-computing as applied to sparse-matrix algorithms. Indeed, SMOKE is the 

fastest emissions processing tool currently available to the air quality modeling community. The 

sparse matrix approach utilized throughout SMOKE permits both rapid and flexible processing 

of emissions data. The processing is rapid because SMOKE utilizes a series of matrix 

calculations instead of less efficient algorithms used in previous systems. The processing is 

flexible because the processing steps of temporal projection, controls, chemical speciation, 

temporal allocation, and spatial allocation have been separated into independent operations 

wherever possible. The results from these steps are merged together at a final stage of 

processing. 
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SMOKE contains a number of major features that make it an attractive component of the 

modeling system. The model supports a variety of input formats from other emissions 

processing systems and models. It supports both gridded and county total land use scheme for 

biogenic emissions modeling. SMOKE can accommodate emissions files from up to 10 

countries and any pollutant can be processed by the system. 

For additional information about the SMOKE model please refer to Appendix D.1. 

3.3 Selection of the Modeling Year 

A crucial step to SIP modeling is the selection of the period of time to model to represent current 

air quality conditions and to project changes in air quality in response to changes in emissions. 

The year 2002 was selected as the base year for several reasons. 

The USEPA’s April 2007 Guidance on the use of Models and Other Analyses for Demonstrating 

Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze (Attainment Modeling 

Guidance) identifies specific goals to consider when selecting one or more episodes for use in 

modeling to demonstrate the attainment of the NAAQS. The USEPA recommends that episode 

selection derive from three principal criteria: 

• Simulate a variety of meteorological conditions 

• Model time periods in which observed concentrations are close to the appropriate 

baseline design value 

• Model periods for which extensive air quality/meteorological data bases exist 

• Model a sufficient number of days so that the modeled attainment test applied at each 

monitor violating the NAAQS is based on multiple days 

VISTAS adopted a logical, stepwise approach in implementing the Attainment Modeling 

Guidance in order to identify the most preferable, representative modeling year. These steps 

include the following: 

• Representativeness of Meteorological Conditions: The VISTAS meteorological 

contractor (BAMS) identified important meteorological characteristics and data sets in 

the VISTAS region directly relevant to the evaluation of candidate annual modeling 

episodes. This analysis is discussed in more detail in the project report in Appendix I, 

Attachment 1. 

• Initial Episode Typing: At the time of selection in 2003, meteorological and air quality 

data were available for 2002 for model inputs and model performance evaluation. 

VISTAS used Classification and Regression Tree (CART) analyses to evaluate the 

candidate modeling years (Douglas et al., 2006). The year 2002 was found to be 

representative of conditions in the other years. Subsequently, these analyses were 

repeated with the meteorological and air quality monitoring data for 2000 to 2004 to 

evaluate how well the 2002 modeling year represented the full 2000-2004 baseline 

period. This analysis confirmed that PM2.5 concentrations in 2002 were representative of 

the five-year baseline period. The CART analysis is discussed in more detail in 

Appendix P. 
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• Data Availability: In parallel with the CART analysis, episode characterization analyses, 

collaborative investigations by VISTAS states (e.g., North Carolina, Georgia, and 

Florida) intensively studied the availability of PM2.5, meteorological, and emissions data 

and representativeness of alternative baseline modeling periods from a regulatory 

standpoint. Additionally, 2002 was the year that the USEPA was requiring states to 

provide emissions inventory data for the Consolidated Emissions Reporting Rule 

(CERR), it made sense to use 2002 as the modeling year to take advantage of the 2002 

inventory. 

• Years to be used by other RPOs: VISTAS also considered what years other RPO would 

be modeling, and several had already chosen calendar year 2002 as the modeling year. 

After a lengthy process of integrated studies, the episode selection process culminated in the 

selection of calendar year 2002 (1 January through 31 December) as the most current, 

representative, and pragmatic choice for modeling. All of the USEPA criteria for model year 

selection were directly considered in this process together with many other considerations (e.g., 

timing of new emissions or aerometric data deliveries by the USEPA or the states to the 

modeling teams). 

3.4 Modeling Domains 

3.4.1 Horizontal Modeling Domain 

The CMAQ_SOA model was run in one-way nested grid mode. This allowed the larger outer 

domains to feed concentration data to the inner nested domain. One-way nesting is believed to 

be appropriate for the generally stagnant conditions experienced during North Carolina’s poor air 

quality episodes. Two-way nesting was not considered due to numerical and computational 

uncertainty associated with the technique. 

The horizontal coarse grid modeling domain boundaries were determined through a national 

effort to develop a common grid projection and boundary. A smaller 12-km grid, modeling 

domain was selected in an attempt to balance location of areas of interest, such as ozone and fine 

particulate matter nonattainment areas. Processing time was also a factor in choosing a smaller 

12-km grid, modeling domain. 

The coarse 36-km horizontal grid domain covers the continental United States. This domain was 

used as the outer grid domain for MM5 modeling with the CMAQ_SOA domain nested within 

the MM5 domain. Figure 3.4.1-1 shows the MM5 horizontal domain as the outer most, blue grid 

with the CMAQ_SOA 36-km domain nested in the MM5 domain. 
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Figure 3.4.1-1. The MM5 and CMAQ_SOA 36-km Horizontal Domains 

To achieve finer spatial resolution in the VISTAS states, a one-way nested high resolution (12-

km grid resolution) was used. Figure 3.4.1-2 shows the 12-km grid, modeling domain for the 

VISTAS region. This is the modeling domain on which the attainment test results are based. 

Figure 3.4.1-2. VISTAS 12-km Modeling Domain 
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3.4.2 Vertical Modeling Domain 

The vertical grid used in the MM5 modeling primarily defines the CMAQ_SOA vertical 

structure. The MM5 model employed a terrain following coordinate system defined by pressure, 

using 34 layers that extend from the surface to the 100 millibars (mb). Table 3.4.1-1 lists the 

layer definitions for both MM5 and for CMAQ. A layer-averaging scheme is adopted for 

CMAQ to reduce the computational cost of the CMAQ simulations. A layer-averaging scheme 

was used to generate 19 vertical layers for CMAQ_SOA to reduce the computational cost of the 

CMAQ_SOA simulations. The effects of layer averaging were evaluated in conjunction with the 

modeling effort and were found to have a relatively minor effect on the model performance 

metrics when both the 34 layer and a 19 layer CMAQ_SOA models were compared to ambient 

monitoring data. Further discussion on the layer-averaging scheme can be found in Section 5 of 

the Modeling Protocol in Appendix D.1. 
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Table 3.4.1-1: Vertical Layer Definition For MM5 and CMAQ 

MM5 Simulation CMAQ 19 Layers

Layer Sigma Pressure 

(mb) 

Height 

(m) 

Depth 

(m) 

Layer Sigma Pressure 

(mb) 

Height 

(m) 

Depth 

(m) 

34 0.000 100 14662 1841 19 0.000 100 14662 6536

33 0.050 145 12822 1466 0.050 145 

32 0.100 190 11356 1228 0.100 190 

31 0.150 235 10127 1062 0.150 235 

30 0.200 280 9066 939 0.200 280 

29 0.250 325 8127 843 18 0.250 325 8127 2966

28 0.300 370 7284 767 0.300 370 

27 0.350 415 6517 704 0.350 415 

26 0.400 460 5812 652 0.400 460 

25 0.450 505 5160 607 17 0.450 505 5160 1712

24 0.500 550 4553 569 0.500 550 

23 0.550 595 3984 536 0.550 595 

22 0.600 640 3448 506 16 0.600 640 3448 986

21 0.650 685 2942 480 0.650 685 

20 0.700 730 2462 367 15 0.700 730 2462 633

19 0.740 766 2095 266 0.740 766 

18 0.770 793 1828 259 14 0.770 793 1828 428

17 0.800 820 1569 169 0.800 820 

16 0.820 838 1400 166 13 0.820 838 1400 329

15 0.840 856 1235 163 0.840 856 

14 0.860 874 1071 160 12 0.860 874 1071 160

13 0.880 892 911 158 11 0.880 892 911 158

12 0.900 910 753 78 10 0.900 910 753 155

11 0.910 919 675 77 0.910 919 

10 0.920 928 598 77 9 0.920 928 598 153

9 0.930 937 521 76 0.930 937 

8 0.940 946 445 76 8 0.940 946 445 76

7 0.950 955 369 75 7 0.950 955 369 75

6 0.960 964 294 74 6 0.960 964 294 74

5 0.970 973 220 74 5 0.970 973 220 74

4 0.980 982 146 37 4 0.980 982 146 37

3 0.985 986.5 109 37 3 0.985 986.5 109 37

2 0.990 991 73 36 2 0.990 991 73 36

1 0.995 995.5 36 36 1 0.995 995.5 36 36

0 1.000 1000 0 0 0 1.000 1000 0 0 

3.5 Baseline Emissions Inventory 

The CAAA revised many of the provisions of the CAA related to attainment of the NAAQS and 

the protection of visibility in mandatory Class I Federal areas (certain national parks and 

wilderness areas). These revisions established new emission inventory requirements applicable 

to certain areas that were designated nonattainment for certain pollutants. In the case of 

particulate matter, the emission inventory provisions are in the general provisions under 

Section 172(c)(3). 
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There are various types of emission inventories. The first is the actual base year inventory. This 

inventory is the base year emissions that correspond to the meteorological data used, which for 

this modeling effort is data from 2002. These emissions are used for evaluating the air quality 

model performance. 

The second type of inventory is the typical base year inventory. This inventory is similar to the 

actual base year inventory, except that for sources whose emissions change significantly from 

year to year, a more typical emission value is used. In this modeling effort, typical emissions 

were developed for the electric generating units (EGUs) and the wildland fire emissions. The air 

quality modeling runs using the typical base year inventory are used to calculate relative 

reduction factors used in the attainment demonstration test. 

The future year base inventory is the third type of inventory and is an inventory developed for 

some future year for which attainment of the fine particulate matter standard is needed. For this 

modeling project, the future year inventory will be 2009, the last complete year for which the 

standard must be attained. It is the future base year inventory that control strategies and 

sensitivities are applied to determine what controls might be needed in order to attain and 

maintain the annual PM2.5 standard. 

Within each type of emission inventory, there are five different emission inventory source 

classifications: stationary point and area sources, off-road and on-road mobile sources, and 

biogenic sources. Stationary point sources are those sources that emit greater than a specified 

tonnage per year, with data provided at the facility level. Electric generating utilities and 

industrial sources are the major categories for stationary point sources. 

Stationary area sources are those sources whose individual emissions are relatively small, but 

due to the large number of these sources, the collective emissions from the source category could 

be significant (i.e., dry cleaners, service stations, agricultural sources, fire emissions, etc.). 

These types of emissions are estimated on a countywide level. 

Non-road (or off-road) mobile sources are equipment that can move but do not use the roadways, 

i.e., lawn mowers, construction equipment, railroad locomotives, aircraft, etc. The emissions 

from these sources, like stationary area sources, are estimated on a countywide level. 

On-road mobile sources are automobiles, buses, trucks, and motorcycles that use the roadway 

system. The emissions from these sources are estimated by vehicle type and road type, and are 

summed to the countywide level. 

Biogenic sources are the natural sources like trees, crops, grasses and natural decay of plants. 

The emissions from these sources are estimated at the grid cell level and summarized to the 

county level. 

For each type of emission inventory and each source classification, the pollutants inventoried 

include VOC, NOx, PM2.5, coarse particulate (PM10), ammonia (NH3) and SO2. Table 3.5-1 

presents a summary of the actual and typical 2002 annual emissions from the various source 

sectors for the counties in the Hickory and Triad PM2.5 nonattainment areas. The full emission 
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summaries for all counties in North Carolina and all states in the VISTAS/ASIP region can be 

found in Appendix E. 

Table 3.5-1. 2002 Annual Emission Summaries 

2002 Annual Emissions Summaries For Catawba County (Hickory Nonattainment Area) 

 Point Non-road 

 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 

Actual 4083.70 19088.60 82320.10 5016.70 4240.10 4.98 1107.30 1619.70 99.70 90.40 86.50 1.40 

Typical 4083.70 19269.60 82371.70 5011.30 4238.90 5.00 1107.30 1619.70 99.70 90.40 86.50 1.40 

 Area Mobile 

 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 

Actual 5051.90 769.60 91.30 4513.40 1189.20 477.30 6040.40 7049.90 259.80 142.00 100.10 206.40 

Typical 5053.20 770.40 91.50 4516.20 1191.50 477.50 6040.40 7049.90 259.80 142.00 100.10 206.40 

Emissions reported as tons/year. 

2002 Annual Emission Summaries For Davidson County (Triad Nonattainment Area) 

 Point Non-road 

 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 

Actual 2791.30 3240.70 408.00 457.50 391.70 6.50 809.10 1545.10 101.70 77.30 73.20 0.90 

Typical 2791.30 3240.70 408.00 457.50 391.70 6.50 809.10 1545.10 101.70 77.30 73.20 0.90 

 Area Mobile 

 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 

Actual 4804.60 655.60 97.20 4464.10 1217.90 558.80 5072.00 6456.20 229.90 128.90 92.20 175.50 

Typical 4806.80 656.70 97.50 4468.80 1221.90 559.00 5072.00 6456.20 229.90 128.90 92.20 175.50 

Emissions reported as tons/year. 

2002 Annual Emission Summaries For Guilford County (Triad Nonattainment Area) 

 Point Non-road 

 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 

Actual 3931.80 218.70 282.20 221.60 135.00 10.60 3394.10 4408.00 376.30 358.90 344.10 3.70 

Typical 3931.80 218.70 282.20 221.60 135.00 10.60 3394.10 4408.00 376.30 358.90 344.10 3.70 

 Area Mobile 

 VOC NOx SO2 PM-10 PM-2.5 NH3 VOC NOx SO2 PM-10 PM-2.5 NH3 

Actual 9393.70 2295.80 231.70 9006.30 2332.30 585.20 12727.20 16815.50 675.20 331.40 227.20 538.10 

Typical 9393.60 2296.00 231.80 9006.40 2332.40 585.30 12727.20 16815.50 675.20 331.40 227.20 538.10 

Emissions reported as tons/year. 

In the sections that follow, a synopsis of the inventories used for each source classifications are 

discussed. The detail discussions of the emissions inventory development can be found in 

Appendix F. Further information on the emission inventory development for the entire southeast 

and the inventories used for other RPOs can be found in Appendix P. Discussion of other input 

requirements for SMOKE can also be found in Section 4.6 of the Modeling Protocol 

(Appendix D.1). 
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3.5.1 Stationary Point Sources 

Point source emissions are emissions from individual sources having a fixed location. Generally, 

these sources must have permits to operate, and their emissions are inventoried on a regular 

schedule. Large sources having the potential to emit at least 100 tons per year (tpy) of a criteria 

pollutant, 10 tpy of a single hazardous air pollutant (HAP), or 25 tpy total HAP are inventoried 

annually. Smaller sources have been inventoried less frequently. The point source emissions 

data can be grouped as EGU sources and other industrial point sources, also called non-electric 

generating units (non-EGUs). Appendix F.1 documents the point source modeling inventory 

development in more details 

3.5.1.1 Electric Generating Units 

The actual base year inventory for the EGU sources used 2002 continuous emissions monitoring 

(CEM) data reported to the USEPA’s Acid Rain program or 2002 hourly emissions data 

provided by stakeholders. These data provide hourly emissions profiles for SO2 and NOx that 

can be used in air quality modeling. Emissions profiles are used to estimate emissions of other 

pollutants based on measured emissions of SO2 and NOx. 

Emissions from EGU vary daily and seasonally as a function of variability in energy demand and 

utilization and outage schedules. Since emission from EGUs represent a significant portion of 

the emission inventory, a typical base year emissions inventory was developed to avoid 

anomalies in future year emissions due to variability in meteorology, economic and outage 

factors in 2002. This approach is consistent with the Attainment Modeling Guidance. To 

develop a typical year 2002 emissions inventory for EGU sources, each unit’s average CEM heat 

input for 2000 through 2004 was divided by the 2002 actual heat input to generate a unit specific 

normalizing factor. This normalizing factor was then multiplied by the 2002 actual emissions. 

The heat inputs for the period 2000 through 2004 were used because the modeling current design 

values use monitored data from this same 5-year period. If a unit was shut down for an entire 

year during the 2000 through 2004 period, the average of the years the unit was operational was 

used. If a unit was shut down in 2002, but not permanently shutdown, the emissions and heat 

inputs from 2001 (or 2000) were used in the normalizing calculations. For more information 

about typical 2002 EGU emissions, please reference to Section 2.1.4 (EGU Analysis) of 

Appendix F.1 (Point Source Emissions Inventory (EI) documentation). 

As part of the air quality modeling, VISTAS, in cooperation with the other eastern RPOs, 

contracted with ICF Resources, L.L.C., to generate future year emission inventories for the 

electric generating sector of the contiguous United States using the Integrated Planning Model 

(IPM). IPM is a dynamic linear optimization model that can be used to examine air pollution 

control policies for various pollutants throughout the contiguous United States for the entire 

electric power system. The dynamic nature of IPM enables projection of the behavior of the 

power system over a specified future period. Optimization logic in IPM determines the leastcost means of meeting electric generation and capacity requirements while complying with 

specified constraints including air pollution regulations, transmission bottlenecks, and plantspecific operational constraints. The versatility of IPM allows users to specify which constraints 

to exercise, and to populate IPM with their own datasets. For more discussion on how the IPM 

data was developed, please refer to Section 3.1.1 (Chronology of the Development of EGU 
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Projections) and Section 3.1.2 (VISTAS/MRPO IPM runs for EGU sources) of Appendix F.1 

(Point Source EI documentation). 

The IPM modeling runs took into consideration both The Clean Air Interstate Rule (CAIR) 

implementation and North Carolina’s Clean Smokestack Act (CSA) requirements for Duke 

Power and Progress Energy. The VISTAS States and stakeholders also provided changes for the 

following: 

• NOx post-combustion control on existing units 

• SO2 scrubbers on existing units 

• SO2 emission limitations 

• Particulate Matter (PM) controls on existing units 

• Summer net dependable capacity 

• Heat rate for existing units 

• SO2 and NOx control plans based on State rules or enforcement settlements 

For a detailed discussion about how IPM took consideration for federal, state and source-specific 

requirements, please also refer to Appendix F.1. 

3.5.1.2 Other Industrial Point Sources 

For the non-EGU sources, the same inventory is used for both the actual and typical base year 

emissions inventories. The non-EGU category uses annual emissions as reported under the 

CERR for the year 2002. These emissions are temporally allocated to month, day, and hour 

using source category code (SCC)-based allocation factors. 

The general approach for assembling future year data was to use recently updated growth and 

control data consistent with the USEPA’s CAIR analyses. This data was supplemented with 

state-specific growth factors and stakeholder input on growth assumptions. 

3.5.2 Stationary Area Sources 

Stationary area sources are sources whose individual emissions are relatively small, but due to 

the large number of these sources, the collective emissions could be significant (i.e., combustion 

of fuels for heating, structure fires, service stations, etc.). Emissions are estimated by 

multiplying an emission factor by some known indicator of collective activity, such as fuel 

usage, number of households, or population. Stationary area source emissions are estimated at 

the countywide level. 

A portion of the area source 2002 base year inventory for North Carolina was developed by the 

NCDAQ and provided to the VISTAS/ASIP contractor. The VISTAS/ASIP contractor 

calculated the remaining portion of the area source inventory. The sources estimated by the 

contractor include emissions from animal husbandry, wild land fires, and particulate matter from 

paved and unpaved roads. For the other states within the modeling domain, either state-supplied 

data or data reported under CERR for 2002 was used. 
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The actual base year inventory will serve as the typical base year inventory for all area source 

categories except for wild land fires. For wild land fires, a typical year inventory was used to 

avoid anomalies in wildfire activity in 2002 compared to longer-term averages. Development of 

a typical year fire inventory provided the capability of using a comparable data set for both the 

base year and future years. Thus, fire emissions remain the same for air quality modeling in both 

the base and any future years. The VISTAS Fire Special Interest Work Group used State records 

to ratio the number of acres burned over a longer term period (three or more years, as available 

from state records) to 2002. Based on these ratios, the 2002 acreage was then scaled up or down 

to develop a typical year inventory.

For categories other than wildland fires, the VISTAS/ASIP contractor generated the future base 

year emissions inventory used in the attainment demonstration modeling. Growth factors 

supplied from the states or the USEPA’s CAIR emission projections were applied to project the 

controlled emissions to the appropriate year. In some cases, the USEPA’s Economic Growth and 

Analysis System Version 5 growth factors were used if no growth factor was available from 

either the states or the CAIR growth factor files. Appendix F.2 provides a detailed discussion of 

the area source inventory. 

3.5.3 Off-Road Mobile Sources 

Off-road (or non-road) mobile sources are equipment that can move but do not use the roadways, 

such as construction equipment, aircraft, railroad locomotives, lawn and garden equipment, etc. 

For the majority of the non-road mobile sources, the emissions for 2002 were estimated using the 

USEPA’s NONROAD2005c model. For the three source categories not included in the 

NONROAD model, i.e., aircraft engines, railroad locomotives and commercial marine, more 

traditional methods of estimating the emissions were used. The same inventory is used for both 

the actual and typical base year emissions inventories. 

For the source categories estimated using the USEPA’s NONROAD model, the model growth 

assumptions were used to create the 2009 future year inventory. The NONROAD model takes 

into consideration regulations affecting emissions from these source categories. For the four 

largest airports in North Carolina, the Federal Aviation Administration’s Terminal Area Forecast 

was used to project growth in aircraft emissions. For the commercial marine, railroad 

locomotives and the remaining airport emissions, the VISTAS/ASIP contractor calculated the 

future growth in emissions using detailed inventory data (both before and after controls) for 1996 

and 2010, obtained from the CAIR Technical Support Document. When available, state-specific 

growth factors were used. Appendix F.2 provides a detailed discussion of the non-road mobile 

source inventory 

3.5.4 Highway Mobile Sources 

For onroad vehicles, the newest version of the MOBILE model, MOBILE6.2, was used. Key 

inputs for MOBILE include information on the age of vehicles on the roads, the average speeds 

on the roads, the mix of vehicles on the roads, any programs in place in an area to reduce 

emissions for motor vehicles (such as emissions inspection programs), and temperature. 

The MOBILE model takes into consideration regulations that affect emissions from this source 

sector. The same MOBILE run is used to represent the actual and typical year emissions for 
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onroad vehicles using input data reflective of 2002. The MOBILE model is then run for the 

2009 inventory using input data reflective of that year. The 2002 vehicle miles traveled (VMT), 

speeds, vehicle age and vehicle mix data were obtained from the North Carolina Department of 

Transportation (NCDOT). For urban areas in North Carolina that run travel demand models 

(TDMs), the VMT and speed data from TDMs were used. For a detailed discussion about the 

highway mobile source inventory development used in the attainment demonstration modeling, 

please refer to Appendix F.3. 

3.5.5 Biogenic Emission Sources 

Biogenic emissions were prepared with the SMOKE-BEIS3 (Biogenic Emission Inventory 

System 3 version 0.9) preprocessor. SMOKE-BEIS3 is a modified version of the Urban Airshed 

Model (UAM)-BEIS3 model. Modifications include use of MM5 data, gridded land use data, 

and improved emissions characterization. The emission factors that are used in SMOKE-BEIS3 

are the same as the emission factors as in UAM-BEIS3. The basis for the gridded land use data 

used by BEIS3 is the county land use data in the Biogenic Emissions Landcover Database 

version 3 (BELD3) provided by the USEPA. A separate land classification scheme, based upon 

satellite (AVHRR, 1 km spatial resolution) and census information aided in defining the forest, 

agriculture, and urban portions of each county. 

The base year biogenic emissions are used for the typical and future year modeling. This is a 

common practice in air quality modeling since the same meteorology is used for all the modeling 

years and the biogenic emissions are very dependent on the meteorology. Variation in these 

emissions could impact the control strategies needed to demonstrate attainment. Therefore, these 

emissions are kept constant. 
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4.0 MODEL PERFORMANCE EVALUATION 

There are many aspects of model performance. This section will focus primarily on the methods 

and techniques recommended by the USEPA for evaluating the performance of the air quality 

model. Before the air quality model can be fully evaluated, an understanding of the 

meteorological modeling performance is needed to understand potential biases and errors that 

may be passed from the meteorological model directly into the air quality model. The 

meteorological modeling evaluation is fully documented in Appendix I and is briefly 

summarized in Section 4.1. The air quality modeling evaluation is fully documented in 

Appendix J and is briefly summarized in Section 4.2. 

4.1 Meteorological Model Performance 

Generally speaking, the meteorological modeling performance was quite good at both the 36-km 

and 12-km grid resolutions. Synoptic features were routinely accurately predicted and the 

meteorological model showed considerable skill in replicating the state variables (e.g. 

temperature, mixing ratio, relative humidity, wind speed and direction, cloud cover, and 

precipitation). The meteorological modeling performance statistics fell within expected and 

acceptable ranges of error during the majority of the 2002 modeled year. 

The meteorological modeling performance for North Carolina was very similar to the 

performance for the VISTAS/ASIP region for the 12-km modeling domain. Again, large-scale 

meteorological patterns were accurately predicted. The meteorological model demonstrated 

substantial skill throughout the entire year and was especially skillful during the summertime 

season from May through September. 

For the North Carolina portion of the 12km modeling domain, the temperature bias was negative 

for the entire year. The months of April through September had an average bias closer to zero 

(- 0.1 Kelvin) than the fall and winter months. Overall, the diurnal pattern was captured very 

well, with only a slight cool bias in the daytime, and a slight warm bias overnight. 

Modeled mixing ratio followed observed trends fairly well. There was a slight low bias in the 

morning through the early afternoon, and a high bias in the late afternoon and at overnight. The 

bias values were generally near zero for most of the year (within ± 0.25 g/kg). Another 

atmospheric moisture parameter, relative humidity, also showed a high bias in the daytime with a 

low bias at night. Relative humidity biases tracked with temperature biases (higher in fall and 

winter, lower in spring and summer), as it is a function of temperature. Precipitation has a 

negative bias in the late fall (October through December) and a positive bias in the spring to 

summer period. Though the model has a tendency to overestimate the amount of spring and 

summertime precipitation, the spatial coverage of measurable precipitation is estimate fairly 

well. 

Wind speed had approximately 0.5 m/s (meters per second) high bias during the daytime hours, 

and approximately 1 m/s high bias at overnight. This high bias is in part due to the inability of 

the model to produce calm, or no wind condition. The models always have some level of winds 

present. This is further aggravated by the fact that observation networks have a “starting 

thresholds” for their wind speed instrumentation. The instruments need winds in excess of 
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1.34 m/s in order to register. As a result, wind speeds less than 1.34 m/s are reported as “calm”. 

When omitting calm observations, the positive bias improves to between 0.2 to 0.6 m/s. 

The meteorological model performance could have impact on the air quality model performance. 

For example, the low temp bias in winter could impact the nitrate chemistry and allow for more 

nitrate formation during this period. Moisture biases may impact secondary aerosol formation, 

though it is questionable to what extent this may happen. Additionally, the under prediction of 

precipitation in the late fall (October through December) may lead to over prediction of PM2.5. 

Conversely the over prediction precipitation amounts in the April to September time frame may 

lead to under prediction of total PM2.5 concentrations. Also, the slightly higher modeled wind 

speeds could lead to additional dispersion of pollutants and ultimately to an under-prediction of 

PM2.5 in the modeling results. 

Overall, the NCDAQ believes that the meteorological model performance is adequate for this 

modeling exercise and should produce credible inputs for the air quality modeling for the 

attainment demonstration for the Hickory and Triad PM2.5 nonattainment areas. 

4.2 Air Quality Model Performance 

Model performance analysis was completed with the final emissions inventory for the entire 

VISTAS/ASIP 36km domain. For the full model performance evaluation for the 36-km domain, 

please see the ASIP Technical support Document in Appendix P. 

The remainder of the discussion of model performance presented here focuses on the comparison 

of observational data from the FRM and STN monitoring sites and model output data from the 

2002 actual annual air quality modeling. The evaluation primarily focuses on the air quality 

model’s performance with respect to individual components of PM2.5, as good model 

performance of the component species dictates good model performance of total or reconstituted 

fine particulate matter. Model performance of the total fine particulate matter will also be 

provided as a means to discuss the overall model performance for this Implementation Plan. 

The air quality model evaluation focused on both the FRM and STN monitors across the state. 

Designations were based on FRM monitors, and calculations of future design values are based on 

current design value information from these sites. Since future attainment demonstrations hinge 

on the model representing the FRM sites well, it follows that model performance for these sites 

should be evaluated. STN data was also evaluated as this data is used to speciate the FRM data 

so component based relative response factors can be calculated for each FRM monitoring site. 

More detailed information on the attainment test process is described in Appendix L. 

Only a brief summary of the model performance evaluation for the 12-km grid domain will be 

discussed in the subsections to follow. For the full model performance evaluation for the 12-km 

grid domain, please refer to Appendix J. A full model performance, including an analysis of 

model statistics, scatter plots, time series, and stacked bar charts for the 12-km VISTAS/ASIP 

domain, all North Carolina monitoring sites collectively, and individually for the monitoring 

sites within the nonattainment area, please refer to Appendix J. 
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4.2.1 Modeling Performance Goals, and Criteria 

In 2004, VISTAS/ASIP established model performance goals and criteria for components of fine 

particle mass (Table 4.2.1-1) based on previous model performance for ozone and fine particles. 

The Attainment Modeling Guidance for fine particulate matter at the time noted that PM models 

might not be able to achieve the same level of performance as ozone models. VISTAS’s 

evaluation considered several statistical performance measures and displays. Fractional bias and 

mean fractional error were selected as the most appropriate metrics to summarize model 

performance; other metrics were also calculated and are included for FRM and STN monitors in 

the full model performance evaluation found in Appendix J. 

Table 4.2.1-1. Established Model Performance Goals and Criteria 

for the PM2.5 Component Species 

Fractional Bias Mean Fractional 

Error 

Comment 

<15 percent <35 percent Goal for PM2.5 model performance based on ozone 

model performance, considered excellent performance 

<30 percent <50 percent Goal for PM2.5 model performance, considered good 

performance 

<60 percent <75 percent Criteria for PM2.5 model performance, considered 

average performance. Exceeding this level of 

performance indicates fundamental concerns with the 

modeling system and triggers diagnostic evaluation. 

An additional way to evaluate model performance statistics is to visualize performance based on 

these fractional bias and mean fractional error goals via “soccer plots” and “bugle plots”. The 

soccer plot is so named because the dotted lines resemble a soccer goal. The soccer plot is useful 

as both bias and error are shown on a single plot. As bias and error approach zero, the points are 

plotted closer to or within the “goal”, represented here by the dashed boxes. 

The bugle plot, named for the shape formed by the criteria and goal lines. The bugle plots are 

shaped as such because the goal and criteria lines are adjusted based on the average 

concentration of the observed species. As the average concentration becomes smaller, the 

criteria and goal lines become larger to adjust for the model’s poor ability to predict at low 

concentrations. 

The analysis of bugle plots demonstrated that greater emphasis should be placed on performance 

of those components with the greatest contribution to PM2.5 mass (e.g. SO4 and OC) and that 

greater bias and error could be accepted for components with smaller contributions to total PM2.5

mass (e.g. EC, NO3, and soil). The soccer plots and bugle plots have been included as suggested 

model performance evaluation displays in the Attainment Modeling Guidance. 
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4.2.2 Domain-Wide Model Performance 

As a summary of model performance, soccer and bugle plots for the all of the VISTAS STN and 

FRM monitors are included here. Plots have been developed for the average monthly modeled 

concentrations and the performance statistics for all of the PM2.5 component species (SO4, NO3, 

NH4, OC, and EC) and reconstructed PM2.5 total mass from the STN monitoring sites 

(Figures 4.2.2-1 and 4.2.2-2), as well as the total PM2.5 mass from the FRM monitoring sites 

(Figures 4.2.2-3 and 4.2.2-4). 

The soccer plots for monthly average component performance for all the VISTAS/ASIP STN 

sites shows generally good model performance for most species of PM2.5 and total PM2.5. The 

exception is the prediction of NO3 values, which most values fall outside the criteria goal 

(Figure 4.2.2-1). There are a few months that fall on the criteria level goal, which is better seen 

in the zoomed view presented in the image on the right in Figure 4.2.2-1. However, when the 

very low concentration of NO3 is taken into consideration, as presented in the bugle plots 

(Figures 4.2.2-2), NO3 performance largely falls within the criteria and goal model performance 

lines. One can still note a general tendency for under prediction in NO3, and other species in 

right hand image in Figure 4.2.2-2, which leads to a slight under prediction in total reconstructed 

PM2.5. 

Monthly total PM2.5 concentration performance at all the VISTAS/ASIP FRM monitors largely 

falls within goal level thresholds, with only three months falling just outside goal level 

performance (Figure 4.2.2-3). Figure 4.2.2-4 suggests a slight negative bias in PM2.5 prediction 

for most of the year, with mean fractional error values remaining within goal levels across the 

year. 

STN VISTAS Sites CMAQ 12km - 2002 Monthly

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STN VISTAS Sites CMAQ 12km - 2002 Monthly

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Figure 4.2.2-1. VISTAS STN Soccer Plots 

The image on the left is a soccer plot depicting both the mean fractional error and fractional bias for 

component concentration for all VISTAS STN monitoring sites. The image on the right is a zoomed 

view of the soccer plot on the left to better depict the area inside the criteria/goal lines. Each point 

represents a monthly value as compared to the model performance criteria (red box) and modeling 

performance goals (green box). 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

North Carolina Attainment Demonstration August 21, 2009 

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STN VISTAS Sites CMAQ 12km - 2002 Monthly

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STN VISTAS Sites CMAQ 12km - 2002 Monthly

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Figure 4.2.2-2. VISTAS STN Bugle Plots 

The image on the left is a bugle plot of the mean fraction bias for particulate matter and its 

component concentrations for all VISTAS STN monitoring sites. The image on the right is a bugle 

plot of mean fraction error for particulate matter and its component species for all VISTAS STN 

monitoring sites. Each point represents a monthly mean fraction bias value as compared to the 

model performance criteria (red lines) and modeling performance goals (green lines). 

FRM VISTAS Sites CMAQ 12km - 2002 Monthly

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FRM VISTAS Sites CMAQ 12km - 2002 Monthly

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Figure 4.2.2-3. VISTAS FRM Soccer Plots 

Soccer plots depicting both the mean fractional error and fractional bias for component 

concentration for all the VISTAS FRM Monitoring sites. The image on the right is a zoomed view of 

the soccer plot on the left to better depict the area inside the criteria/goal lines. Each point 

represents a monthly value as compared to the model performance criteria (red box) and modeling 

performance goals (green box). 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

North Carolina Attainment Demonstration August 21, 2009 

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FRM VISTAS Sites CMAQ 12km - 2002 Monthly

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FRM VISTAS Sites CMAQ 12km - 2002 Monthly

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Figure 4.2.2-4. VISTAS FRM Bugle Plots 

The image on the left is a bugle plot of the mean fraction bias for particulate matter and its 

component species concentrations for all the VISTAS FRM Monitoring sites. The image on the right 

is a bugle plot of mean fraction error for particulate matter and its component species for all the 

VISTAS FRM Monitoring sites. Each point represents a monthly mean fraction bias value as 

compared to the model performance criteria (red lines) and modeling performance goals (green 

lines). 

Overall, the general tendency is for the model to have some difficulty in predicting NO3, as the 

monthly average values tend to fall outside the criteria goals for performance in the soccer plots. 

Part of this under prediction lies in the fact that NO3 are generally found in low concentration 

across the southeast, and the model generally has difficulties representing any compound with 

low atmospheric concentrations. The bugle plots are more encouraging with NO3 performance, 

as these plot take into consideration the concentration of the component when evaluating 

performance. The bugle plots show all components and total PM2.5 falling within criteria level, 

or better, of model performance goals. The weaker performance of NO3 accounts for the slight 

negative bias in the both the total reconstructed PM2.5 mass from STN sites as well as FRM total 

PM2.5 data. 

4.2.3 Nonattainment Area Model Performance 

The statistical metrics were calculated for the Hickory (Catawba County) and Hattie Avenue 

(Forsyth County) STN monitors to demonstrate model performance for the components of PM2.5

in and near the PM2.5 nonattainment areas. Model performance statistics for the STN sites were 

calculated on a component and total PM2.5 basis for the entire base year. 

Model performance statistics were also calculated collectively for the FRM monitors within the 

VISTAS 12-km domain, as well as individually for the 3 FRM monitors in the nonattainment 

areas (Hickory, Lexington, and Mendenhall) to demonstrate the model’s ability to replicate total 

PM2.5 mass at these sites. Summaries and statistical tables for the STN monitoring sites and 

FRM monitoring sites can be found in Appendix J. 

As a summary of model performance at the nonattainment area level, the soccer and bugle plots 

for the Hickory STN (Figure 4.2.3-1 and 4.2.3-2) and FRM monitor (Figure 4.2.3-3 and 4.2.4-4) 

follow. Plots have been developed for the average monthly concentrations of PM2.5 and its 

component species at the STN sites, and for total PM2.5 from FRM monitors for all North 

Carolina STN sites collectively and other the monitoring sites within the PM2.5 nonattainment 

areas are included in Appendix J. 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

North Carolina Attainment Demonstration August 21, 2009 

36

Monthly average component concentration performance at the Hickory STN site is similar to 

overall 12-km VISTAS domain and North Carolina statewide model performance. Nitrate 

generally falls outside of suggested criteria model performance goals. Some under prediction of 

organic carbon values is present, but this is in line with the overall model performance seen 

across North Carolina. Overall, the PM2.5 model performance was within criteria level, if not 

within the goal level thresholds. 

STN Hickory CMAQ 12km - 2002 Monthly

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STN Hickory CMAQ 12km - 2002 Monthly

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Figure 4.2.3-1. Hickory STN Soccer Plots 

The image on the left is the soccer plot depicting both the mean fractional error and fractional bias 

for component concentration for the Hickory (37-035-0004) STN monitoring site. The image on the 

right is a zoomed view of the soccer plot on the left to better depict the area inside the criteria/goal 

lines. Each point represents a monthly value as compared to the model performance criteria (red 

box) and modeling performance goals (green box). 

STN Hickory CMAQ 12km - 2002 Monthly

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STN Hickory CMAQ 12km - 2002 Monthly

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Figure 4.2.3-2. Hickory STN Bugle Plots 

The image on the left is the bugle plot of the mean fraction bias for particulate matter and its 

component species concentrations for the Hickory (37-035-0004) STN monitoring site. The image on 

the right is the bugle plot of mean fraction error for particulate matter and its component species for 

the Hickory STN site. Each point represents a monthly mean fraction bias value as compared to the 

model performance criteria (red lines) and modeling performance goals (green lines). 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

North Carolina Attainment Demonstration August 21, 2009 

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FRM Hickory CMAQ 12km - 2002 Monthly

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FRM Hickory CMAQ 12km - 2002 Monthly

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Figure 4.2.3-3. Hickory FRM Soccer Plots 

The image on the left is the soccer plot depicting both error and bias for the light extinction due to 

particulate matter and its component species for the Hickory FRM monitoring site (37-035-0004). 

The image on the right is a zoomed view of the soccer plot on the left to better depict the area inside 

the criteria/goal lines. Each point represents a monthly mean fraction bias value as compared to the 

model performance criteria (red box) and modeling performance goals (green box). 

FRM Hickory CMAQ 12km - 2002 Monthly

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FRM Hickory CMAQ 12km - 2002 Monthly

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Figure 4.2.3-4. Hickory FRM Bugle Plots 

Bugle plot depicting the mean fractional bias for the light extinction due to particulate matter and its 

component species for the Hickory FRM monitoring site (37-035-0004). The image on the right is the 

bugle plot depicting the mean fraction error for the light extinction due to particulate matter and its 

component species for the Hickory FRM monitoring site. Each point represents a monthly mean 

fraction bias value as compared to the model performance criteria (red lines) and modeling 

performance goals (green lines). 

4.2.4 Air Quality Model Performance Summary 

Overall, the model performance for North Carolina through the 2002 baseline modeling year is 

reasonable good. For the most part, mean normalized bias and mean normalized gross error are 

within the recommended limits for good model performance for most of component species as 

well as total PM2.5 mass. Overall performance was good for sulfate and organic carbon, which 

are the largest constituents of PM2.5 for North Carolina. Nitrate performance was less than ideal, 

especially during the summer months. This is likely due to the generally low atmospheric 

concentrations seen in North Carolina. When the performance is weighted by the concentration, 

as in the bugle plots, the performance metrics indicate better model performance. The model 

also does a good job capturing PM2.5 component and total concentrations through various 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

North Carolina Attainment Demonstration August 21, 2009 

38

episode-clean out cycles (see Section 5, Appendix J). Overall, the NCDAQ believes that the 

model performance is well within the limits of acceptable performance established in the 

Attainment Modeling Guidance. 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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39

5.0 CONTROLS APPLIED 

Several control measures already in place or being implemented over the next few years will 

reduce stationary point, highway mobile, and non-road mobile sources emissions. The Federal 

and State control measures that have impacts on air quality in North Carolina were modeled for 

the attainment year and are discussed in the sections below. Although all the control listed 

below may not directly reduce PM2.5 concentrations in North Carolina, the modeling assessment 

in this submittal was based on one atmosphere modeling completed for ozone and fine 

particulate matter attainment demonstrations and regional haze plans. 

5.1 Federal Control Measures 

5.1.1 Tier 2 Vehicle Standards 

Federal Tier 2 vehicle standards will require all passenger vehicles in a manufacturer’s fleet, 

including light-duty trucks and Sport Utility Vehicles (SUVs), to meet an average standard of 

0.07 grams of NOx per mile. Implementation began in 2004, with full compliance required 2007. 

The Tier 2 standards will also cover passenger vehicles over 8,500 pounds gross vehicle weight 

rating (the larger pickup trucks and SUVs), which are not covered by the current Tier 1 

regulations. For these vehicles, the standards will be phased in beginning in 2008, with full 

compliance required by 2009. The new standards require vehicles to be 77% to 95% cleaner 

than those on the road today. The Tier 2 rule also reduced the sulfur content of gasoline to 30 

parts per million (ppm) starting in January of 2006. Most gasoline sold in North Carolina prior 

to January 2006 had a sulfur content of about 300 ppm. Sulfur occurs naturally in gasoline, and 

interferes with the operation of catalytic converters on vehicles, which results in higher NOx

emissions. Lower-sulfur gasoline is necessary to achieve the Tier 2 vehicle emission standards. 

5.1.2 Heavy-Duty Gasoline and Diesel Highway Vehicles Standards 

New USEPA standards designed to reduce NOx and VOC emissions from heavy-duty gasoline 

and diesel highway vehicles began to take effect in 2004. The second phase of the standards and 

testing procedures, which began in 2007, will reduce particulate matter from heavy-duty 

highway engines, and will also reduce highway diesel fuel sulfur content to 15 ppm since the 

sulfur damages emission control devices. The total program is expected to achieve a 90% 

reduction in PM emissions and a 95% reduction in NOx emissions for these new engines using 

low sulfur diesel, compared to existing engines using higher-content sulfur diesel. 

5.1.3 Large Non-road Diesel Engines Rule 

In May 2004, the USEPA promulgated new rules for large non-road diesel engines, such as those 

used in construction, agricultural, and industrial equipment, to be phased in between 2008 and 

2014. The non-road diesel rules also reduce the allowable sulfur in non-road diesel fuel by over 

99%. Non-road diesel fuel currently averages about 3,400 ppm sulfur. The rule limits non-road 

diesel sulfur content to 500 ppm by 2006 and 15 ppm by 2010. The combined engine and fuel 

rules would reduce NOx and PM emissions from large non-road diesel engines by over 90%, 

compared to current non-road engines using higher-content sulfur diesel.
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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5.1.4 Non-road Spark-Ignition Engines and Recreational Engines Standard 

The new standard, effective in July 2003, regulates NOx, hydrocarbons (HC) and carbon 

monoxide (CO) for groups of previously unregulated non-road engines. The new standard 

applies to all new engines sold in the United States and imported after these standards begins and 

applies to large spark-ignition engines (forklifts and airport ground service equipment), 

recreational vehicles (off-highway motorcycles and all-terrain-vehicles), and recreational marine 

diesel engines. The regulation varies based upon the type of engine or vehicle. 

The large spark-ignition engines contribute to ozone formation and ambient CO and PM levels in 

urban areas. Tier 1 of this standard was implemented in 2004 and Tier 2 started in 2007. Like 

the large spark-ignition, recreational vehicles contribute to ozone formation and ambient CO and 

PM levels. For the off-highway motorcycles and all-terrain-vehicles, the new exhaust emissions 

standard was phased-in. Fifty percent of model year 2006 engines had to meet the standard, and 

for model year 2007 and later, all of the engines have to meet the standard. Recreational marine 

diesel engines over 37 kilowatts are used in yachts, cruisers, and other types of pleasure craft. 

Recreational marine engines contribute to ozone formation and PM levels, especially in marinas. 

Depending on the size of the engine, the standard began phasing-in in 2006. 

When all of the non-road spark-ignition and recreational engine standards are fully implemented, 

an overall 72% reduction in HC, 80% reduction in NOx, and 56% reduction in CO emissions are 

expected by 2020. These controls will help reduce ambient concentrations of ozone, CO, and 

fine PM. 

5.1.5 NOx SIP Call in Surrounding States 

In October 1998, the USEPA made a finding of significant contribution of NOx emissions from 

certain states and published a rule that set ozone season NOx budgets for the purpose of reducing 

regional transport of ozone (63 FR 57356). This rule, referred to as the NOx SIP Call, required 

ozone season controls to be put on utility and industrial boilers, as well as internal combustion 

engines, in 22 states in the Eastern United States. A NOx emissions budget was set for each state 

and the states were required to develop rules that would assure that each state met its budget. A 

NOx trading program was established, allowing sources to buy credits to meet their NOx budget 

as opposed to actually installing controls. The emission budgets were to be met by the beginning 

of 2004. Even with the trading program, the amount of ozone season NOx emissions has 

decreased significantly in and around North Carolina. 

5.1.6 Clean Air Interstate Rule 

On May 12, 2005, the USEPA promulgated the “Rule To Reduce Interstate Transport of Fine 

Particulate Matter and Ozone (Clean Air Interstate Rule); Revisions to Acid Rain Program; 

Revisions to the NOx SIP Call”, referred to as CAIR. This rule established the requirement for 

States to adopt rules limiting the emissions of NOx and sulfur dioxide (SO2) and a model rule for 

the states to use in developing their rules. The purpose of the CAIR is to reduce interstate 

transport of precursors of fine particulate and ozone. 

The CAIR applies to (1) any stationary, fossil-fuel-fired boiler or stationary, fossil-fuel-fired 

combustion turbine serving at any time, since the start-up of a unit’s combustion chamber, a 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

North Carolina Attainment Demonstration August 21, 2009 

41

generator with nameplate capacity of more than 25 Megawatt hours (MW) producing electricity 

for sale and (2) for a unit that qualifies as a cogeneration unit during the 12-month period starting 

on the date that the unit first produces electricity and continues to qualify as a cogeneration unit, 

a cogeneration unit serving at any time a generator with nameplate capacity of more than 25 MW 

and supplying in any calendar year more than one-third of the unit’s potential electric output 

capacity or 219,000 MW, whichever is greater, to any utility power distribution system for sale. 

This rule provides annual state caps for NOx and SO2 in two phases, with the Phase I caps for 

NOx and SO2 starting in 2009 and 2010, respectively. Phase II caps become effective in 2015. 

The USEPA is allowing the caps to be met through a cap and trade program if a state chooses to 

participate in the program. When fully implemented, the CAIR will reduce SO2 emissions in the 

eastern United States by over 70 percent and NOx emissions by over 60 percent from 2003 

levels. Due to Court challenges of CAIR in 2008, the USEPA will be making changes to this 

program by 2011. However, the existing CAIR rules will remain in place until the USEPA 

promulgates changes to the program. 

5.2 State Control Measures 

North Carolina has adopted a number of regulations and legislation to address pollution issues 

across the State. These include the Clean Air Bill, the NOx SIP Call Rule, the CSA, the Open 

Burning Rule, and the CAIR. All of these regulations were modeled in the attainment 

demonstration. These regulations are summarized below and the actual regulations and 

legislation can be viewed in Appendix M. 

5.2.1 Clean Air Bill 

The 1999 Clean Air Bill expanded the vehicle emissions inspection and maintenance program in 

North Carolina from 9 counties to 48 counties between July 1, 2002 and January 1, 2006 (Figure 

7.2.1-1). Vehicles are tested using the onboard diagnostic system (OBDII) test, an improved 

method of testing for pollutant emissions. 

Figure 5.2.1-1. North Carolina’s OBDII Test Phase-in Map 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

North Carolina Attainment Demonstration August 21, 2009 

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The effective dates for the counties in the Hickory and Triad PM2.5 nonattainment area are listed 

in Table 5.2.1-1 below. 

Table 5.2.1-1 OBDII Phase-in Effective Dates 

County Date 

Catawba July 1, 2003 

Davidson July 1, 2003 

Guildford July 1, 2002 

5.2.2 NOx SIP Call Rule 

In response to the USEPA’s NOx SIP call, North Carolina adopted rules to control the emissions 

of NOx from large stationary combustion sources. These rules cover (1) fossil fuel-fired 

stationary boilers, combustion turbines, and combined cycle systems serving a generator with a 

nameplate capacity greater than 25 MW and selling any amount of electricity, (2) fossil fuelfired stationary boilers, combustion turbines, and combined cycle systems having a maximum 

design heat input greater than 250 million British thermal units per hour, and (3) reciprocating 

stationary internal combustion engines rated at equal or greater than 2400 brake horsepower 

(3000 brake horsepower for diesel engines and 4400 brake horsepower for dual fuel engines). 

As part of the NOx SIP call, the USEPA rules established a NOx budget for sources in North 

Carolina and other states. 

Besides amending existing NOx rules and adopting new NOx rules specifically to address the 

USEPA NOx SIP call, the North Carolina rules also require new sources to control emissions of 

NOx. The objective of this requirement is (1) to aid in meeting the NOx budget for North 

Carolina for minor sources and (2) to aid in attaining and maintaining the ambient air quality 

standard for ozone in North Carolina. 

North Carolina’s NOx SIP Call rule was predicted to reduce summertime NOx emissions from 

power plants and other industries by 68% by 2006. In October 2000, the North Carolina 

Environmental Management Commission (EMC) adopted rules requiring the reductions. In 

2009, the North Carolina NOx SIP Call program was replaced with the North Carolina’s CAIR 

rule, which is discussed below in Section 5.2.5. 

5.2.3 Clean Smokestacks Act 

In June 2002, the North Carolina General Assembly enacted the CSA, which requires coal-fired 

power plants in North Carolina to reduce annual NOx emissions by 77% by 2009. These power 

plants must also reduce annual sulfur dioxide emissions by 49% by 2009 and by 73% by 2013. 

It is significant to note that this law sets a cap of NOx and SO2 emissions for the State, which the 

public utilities cannot meet by purchasing emissions credits. The CSA reduces NOx emissions 

beyond the requirements of the NOx SIP Call Rule. One of the first state laws of its kind in the 

nation, this legislation provides a model for other states in controlling multiple air pollutants 

from older coal-fired power plants. 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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5.2.4 Open Burning Bans 

The rule adopted by the EMC in June 2004 is aimed at reducing emissions that contribute to 

ozone and particle pollution when the air quality is expected to be poor. The ban is triggered on 

"air quality action days," when the NCDAQ or local air programs forecast Code Orange, Red or 

worse ozone conditions for a particular metro area. The following counties in the Hickory area 

are subject to this rule: Alexander, Catawba, Southeastern Burke and Southeastern Caldwell 

counties. The following counties in the Triad area are subject to this rule: Alamance, Caswell, 

Davidson, Davie, Forsyth, Guilford, Randolph, Rockingham and Stokes counties. 

5.2.5 Clean Air Interstate Rule 

In response to the USEPA’s CAIR, the NCDAQ developed a state CAIR. Under the USEPA’s 

rule, North Carolina has caps as follows: 

• Annual NOx: 62,183 tons for 2009-2014 and 

51,819 tons for 2015 and each year thereafter; 

• Ozone season NOx: 28,392 tons for 2009-2014 and 

23,660 tons for 2015 and each year thereafter; 

• Annual SO2: 137,342 tons for 2010-2014 and 

96,139 tons for 2015 and each year thereafter. 

The State’s NOx allocations have been distributed among the covered facilities. The USEPA 

will determine the SO2 allocations, which are based on the acid rain program. For the most part 

the proposed rules incorporate the USEPA’s model rule. The USEPA’s model rule for 

definitions; permitting; monitoring, reporting, and record keeping; trading and banking; 

designated representative; opt-in provision, and new source growth are incorporated by 

reference. 

The rule requires the EMC to periodically review the allocations in 2010 and every five years 

thereafter and to decide whether to reallocate. This rule does not preclude the EMC from 

adopting additional emission reduction requirements for covered sources if necessary to attain or 

maintain an ambient air quality standard. 

The EMC adopted North Carolina’s CAIR on March 9, 2006 and the rule became effective 

July 1, 2006. Due to the Court challenges of CAIR in 2008, the USEPA will be making changes 

to this program soon. However, the existing CAIR rules will remain in place until the USEPA 

promulgates changes to the program. 
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6.0 ATTAINMENT DEMONSTRATION 

An attainment demonstration consists of (a) analyses that estimate whether selected emissions 

reductions will result in ambient concentrations that meet the NAAQS, and (b) an identified set 

of control measures which will result in the required emissions reductions. The necessary 

emission reductions for both of these attainment demonstration components may be determined 

by relying on results obtained with air quality models. 

Section 3.0 of the Attainment Modeling Guidance recommends applying both a modeled 

attainment test and a subsequent screening test (or unmonitored area analysis) to the air quality 

modeling results to determine if the annual PM2.5 NAAQS will be met. Additional technical or 

corroboratory analyses may also be used as part of a “supplemental analysis” or a more stringent 

“weight of evidence” determination to supplement the modeled attainment test and to further 

support a demonstration of attainment of the annual PM2.5 NAAQS. 

This section does not present a modeled attainment test or a subsequent screening test with 

respect to the daily PM2.5 NAAQS, because all portions of North Carolina were initially 

designated as attaining the daily PM2.5 standard. Continued attainment of the daily PM2.5 

NAAQS is projected and assumed due to the widespread reductions in SO2 and NOx emissions 

already discussed in Section 5 and the modeling projections discussed later in this Section that 

demonstrate significant decreases in PM2.5 concentrations into the future. 

6.1 Attainment Test Introduction 

The purpose of a modeling assessment is to determine if control strategies currently being 

implemented (“on the books”) and proposed control strategies will lead to attainment of the 

NAAQS for PM2.5 by the attainment year of 2009. The modeling is applied in a relative sense, 

similar to the 8-hour ozone attainment test. However, the PM2.5 attainment test is more 

complicated and reflects the fact that PM2.5 has many components. In the test, ambient PM2.5 is 

divided into major components, with a separate relative response factor (RRF) and future design 

value (DVF) calculated for each of the PM2.5 components. Since the attainment test is calculated 

on a per species basis, the attainment test for PM2.5 is referred to as the Speciated Modeled 

Attainment Test (SMAT). In its entirety, SMAT consists of four basic steps. 

First, the observed quarterly mean PM2.5 and quarterly mean composition for each monitor is 

calculated. This is achieved by multiplying the monitored quarterly mean concentration of PM2.5

from FRM monitors by the monitored fractional composition of PM2.5 species for each quarter 

(e.g., (20% sulfate) x (15.0 μg/m3 PM2.5 mass) = 3.0 μg/m3 sulfate mass). 

The monitored quarterly mean concentration of PM2.5 from FRM monitors are the 5 year 

baseline design values (DVB) that are the result of averaging the 3 current design values (DVC) 

that straddle the modeling base year. The fractional composition of PM2.5 species is derived 

from STN monitoring site data that has been processed by the “sulfate, adjusted nitrate, derived 

water, inferred carbonaceous material balance approach”, or SANDWICH method, so STN and 

FRM masses are equivalent. The mean composition derived from the SANDWICH method 

includes the percent of PM2.5 that can be attributed to SO4, NO3, OC, EC, other primary 

inorganic particulates (or crustal materials), NH4, and particle bound water (PBW). 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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The second step is to use model results to derive component specific RRF for each monitor for 

each quarter. The RRF is basically the ratio of the model’s future projections to the baseline 

current projections. For each component, the future year modeled quarterly mean concentration 

predicted near the monitoring site divided by the base year modeled quarterly mean 

concentration predicted near the monitoring site. 

For the third step, the component specific RRFs are applied to the observed air quality 

concentrations to project quarterly species estimates. For each quarter, the current quarterly 

mean component concentration (step 1) are multiplied by the component-specific RRF obtained 

in step 2. This leads to an estimated future quarterly mean concentration for each component. 

The fourth step sums the quarterly components to get a quarterly mean PM2.5 value. These 

quarterly mean values are then averaged to produce a future year annual average PM2.5 estimate, 

or future design value (DVF), for each FRM monitoring site. This final value is then compared 

to the NAAQS (15.0 μg/m3

) to determine if attainment is reached. For a more detailed 

discussion of SMAT and the data at each step for the monitors in the nonattainment areas, see 

Appendix L. 

6.2 Attainment Test Results 

The goal of the SMAT process is to sum the quarterly mean PM2.5 components to get annual 

mean PM2.5 values. Table 6.2-1 displays the quarterly mean concentration and annual mean 

future design values (DVFs) estimates for 2009 for the FRM sites in the North Carolina PM2.5

nonattainment areas. 

Table 6.2-1. Quarterly Mean and Annual Mean PM2.5 Mass Estimates for 2009 

AIRS ID County Site Name Quarter 1 

Concentration

Quarter 2 

Concentration

Quarter 3 

Concentration

Quarter 4 

Concentration

2009 Annual 

DVF

37-035-0004 Catawba Hickory 12.4 13.3 15.2 11.4 13.1

37-057-0002 Davidson Lexington 12.7 14.0 14.5 12.2 13.4

37-081-0013 Guilford Mendenhall 10.2 11.7 13.9 10.2 11.5

These 2009 annual DVFs are the final product of the SMAT process and are then compared to 

the NAAQS (15.0 μg/m3) to determine if attainment goals will be reached. Since the values at 

the FRM site in both the nonattainment areas are less than 15.0 μg/m3

, all areas have passed the 

attainment test portion of the attainment demonstration. 

6.3 Supplemental Analyses 

The Attainment Modeling Guidance asserts that all attainment demonstrations should be 

accompanied by supplemental analysis that further supports the modeling conclusions. This 

supplemental analysis can include additional analyses of air quality, emissions and 

meteorological data, and consider modeling outputs other than the results of the attainment test. 

If the attainment test results fall short of the standard, the results of corroboratory analyses may 

be used in a weight of evidence determination (WOE) to show that attainment is likely despite 

modeled results, which may be inconclusive. 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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The Attainment Modeling Guidance defines the guidelines for supplemental analysis/WOE for 

the annual PM2.5 standard as follows: 

- Site with a DVF less than 14.5 μg/m3

 should submit basic supplemental analysis to 

confirm the outcome of the model attainment test. 

- Sites with a DVF between 14.5 and 15.5 μg/m3 should submit a weight of evidence 

demonstration to aggregate supplemental analysis to support the model attainment 

demonstration. 

- Sites with a DVF greater than or equal to 15.5 μg/m3 should consider additional control 

measure to ensure attainment, as more qualitative analysis is unlikely to attainment. 

All North Carolina PM2.5 nonattainment areas have DVFs lower than 14.5μg/m3, making the 

following section an examination of supplemental analysis to corroborate modeling results, 

rather than a WOE analysis to show attainment. 

6.3.1 Air Quality Modeling Metrics 

Section 7.1 of the Attainment Modeling Guidance suggests several additional modeling exercises 

that can be performed as part of supplemental analysis. One of the metrics that can be 

considered as part of this type of additional analysis is the calculation of the percent change in 

number of grid cells greater than or equal to 15 μg/m3

 within the nonattainment area. 

For the Hickory and Triad nonattainment areas, the cell counts of modeling data were tallied 

from both the 2002 baseline and the 2009 attainment year modeling run for a subset of the 

highest days from the base year. This was done in order to quantify the reduction of PM2.5 on 

our highest days through out the year, and not just based on a single annual average from the 

modeling. This subset of days included all days with a 24-hour PM2.5 concentration greater than 

30 μg/m3 at any of the monitoring sites in either nonattainment area, as well as the four days with 

the highest average daily values from each quarter. This selection process identified 28 days for 

presentation and coincides with the days used in the model performance evaluation (Appendix J) 

and in the model results section (Appendix K). A full listing of the days and the observed 24-

hour PM2.5 concentrations from the monitors in the nonattainment areas can be found in either 

Appendix J or Appendix K. 

Data was extracted for only the grid cells that contained portions of either of the PM2.5 

nonattainment areas. Figure 6.3.1-1 highlights the 50 cells that encompass the North Carolina 

PM2.5 nonattainment areas. 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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Figure 6.3.1-1. Area for which the Air Quality Metrics were Applied 

The cell counts were binned based on concentration ranges of 15 μg/m3 intervals to help 

illuminate the change in severity on the days in North Carolina with the highest PM2.5

concentrations. Figure 6.3.1-2 presents the cell count results both graphically and in tabular 

form. The graph clearly shows a striking increase in the number of days below 15 μg/m3. By 

2009, 41.57% of cells fall in the 0 –15 μg/m3 range, a substantial increase from the 17.21% in 

2002. Raw cell counts show a total of 341 cells shifted to the 0 – 15 μg/m3 range between 2002 

and 2009 (Table 6.3.1-1). 

Figure 6.3.1-2 also shows a decrease in the number of cells in the 15 – 30 μg/m3 bin (269 cell 

decrease) and the 30 - 45μg/m3

 bin (75 cell decrease). The number of cells in the 45 –60 range 

remain relatively constant from 2002 to 2009. A closer examination of the daily cell counts 

shows that all of the cells in the highest concentration category occur on the same day in both the 

2002 and 2009 modeling and are likely associated with a fire. Overall, the results from the air 

quality modeling metric are encouraging. The metric shows a substantial increase in the number 

of cells below 15 μg/m3

, and an increase in cells below 30μg/m3. 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

North Carolina Attainment Demonstration August 21, 2009 

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Concentration 2002 2009

0 - 15 17.21% 41.57%

15 - 30 70.21% 51.00%

30 - 45 12.29% 6.93%

45 - 60 0.29% 0.50%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2002 2009

Modeling Year

Percentage of Nonattainment Area

45 - 60

30 - 45

15 - 30

0 - 15

Figure 6.3.1-2. Percentage of Cell in PM2.5 Nonattainment Areas within Concentration 

Categories for 2002 and 2009. Table of Actual Values is Presented on the Right. 

Table 6.3.1-1. Number of Cells within Concentration Bins. Increases (decreases) in the 

Number of Cells within the Bins are Noted by Red (Blue) Coloration in the Last Column. 

Concentration 2002 2009 Difference

0 - 15 241 582 341

15 - 30 983 714 -269

30 - 45 172 97 -75

45 - 60 4 7 3

6.3.2 Other Modeling Results 

One way to acquire modeling sensitivity runs is to examine the modeling results from other 

RPOs or from USEPA modeling studies. Other modeling studies may use different physical and 

chemical modeling options for their meteorological and air quality modeling runs, which would 

provide a comparison or sensitivity based on these different options. 

An air quality modeling exercise that contained results for North Carolina PM2.5 nonattainment 

areas is the USEPA’s modeling for the CAIR. The Technical Support Document for the final 

CAIR, March 2005, provided modeling results with and without the implementation for the 

CAIR. Differences between the USEPA’s modeling and the attainment demonstration are: 1) the 

meteorology was for 2001, 2) the DVB was the weighted design values for the 1999-2003 period 

and 3) the modeling results were for 2010. The DVF was calculated using the CAIR SMAT 

tool, so methodologies between the CAIR DVF and the values presented in Section 6.4 are the 

same. These modeling results are listed in Table 6.3.2-1 below. 
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Table 6.3.2-1. USEPA’s CAIR Modeling Results 

Future Year Catawba County Davidson County

2010 14.07 14.36

2015 13.45 13.61

The USEPA’s results were for the highest monitor in a county where more than one monitor is 

located. The USEPA’s modeling results predicts that both the North Carolina nonattainment 

areas should be below the annual PM2.5 standard by 2010. Although this is one year later than 

the attainment year for these areas, the USEPA’s 2010 CAIR DVFs are 1 μg/m3

 higher than what 

the NCDAQ is showing in the attainment demonstration, but still support that both the North 

Carolina nonattainment areas will attain the annual PM2.5 standard by the attainment year of 

2009. 

6.3.3 Air Quality Trends and Additional Reductions in Emissions 

Since the annual PM2.5 designation in 2002, annual average concentrations of PM2.5 have 

decreased. PM2.5 concentrations hovered near the standard at the two nonattaining monitors 

through the middle portion of the decade, while the Mendenhall monitor has maintained values 

lower than the NAAQS since 2001. In 2007, the PM2.5 concentrations fell below the NAAQS at 

all monitoring sites in both nonattainment areas. Table 6.3.3-1 provides the annual average data, 

with Figure 6.3.3-1 providing a graphical representation of the data. 

Table 6.3.3-1. Annual Average PM2.5 Concentrations for the Past 10 Years 

Monitoring 

Site County AIRS ID Annual Averages 

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 

Hickory Catawba 3703500041 17.4 17.6 16.0 15.4 15.0 15.0 15.9 15.2 14.5 12.8 

Lexington Davidson 3705700021 17.3 18.0 16.5 15.9 15.2 15.2 15.4 15.1 14.6 13.7 

Mendenhall Guilford 3708100131 13.7 13.3 14.0 14.0 14.1 13.0 11.4 

         Average of 1st-4th Quarter For Each Year. Values in colored orange are in excess of the Annual PM2.5 NAAQS. 

Note: Mendenhall was not in operation from 1999 to 2001 

Note: There was an extended loss of monitoring data at the Mendenhall site during the 4th quarter of 

2006. The NCDAQ has performed an extensive data imputation study to estimate a 4th quarter 

average concentration such that an appropriate annual average concentration and design value could 

be calculated. This study, titled “Mendenhall PM2.5 Data Imputation for 4Q2006” can be found in 

Appendix C.3
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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Figure 6.3.3-1. Annual PM2.5 Average Concentrations for the FRM Monitors 

in the Hickory and Triad Nonattainment Areas 

With the improvement in annual average PM2.5 values, there has also been an improvement in 

PM2.5 design values. When one takes into account the period of record, PM2.5 design values have 

improved significantly over the last 10 years. Like with the annual averages, the three-year 

design values also began to hover near the level of the standard for both the Hickory and 

Lexington monitors during the middle portion of the decade. With the most recent design value 

period, 2006-2008, the PM2.5 design values have achieved attainment of the NAAQS at all three 

monitoring sites in the two nonattainment areas (See Table 6.3.3-2). 

Table 6.3.3-2. Three Year Design Values for the FRM Monitors 

in the Hickory and Triad PM2.5 Nonattainment Areas 

Monitoring 

Site County AIRS ID 

Design Values 

1999-

2001 

2000-

2002 

2001-

2003 

2002-

2004 

2003-

2005 

2004-

2006 

2005-

2007 

2006-

2008 

Hickory Catawba 3703500041 17.0 16.3 15.5 15.1 15.3 15.4 15.2 14.2 

Lexington Davidson 3705700021 17.2 16.8 15.8 15.4 15.2 15.2 15.1 14.5 

Mendenhall Guilford 3708100131 13.7 13.8 14.0 13.7 12.9 

         Average Over 12 Quarters. Negative & Underlined Indicate Altered Calculation 

Note: Both of the footnotes that apply to Table 6.3.3-1 are also applicable with this table.
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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The very recent attainment of the annual PM2.5 NAAQS at all of the monitoring sites can be 

directly attributed to the dramatic reduction of SO2 emissions throughout North Carolina due to 

coal-fired power plants compliance with the CSA Phase 1 SO2 emissions cap. From a peak in 

2005, the SO2 emissions from the EGUs within North Carolina have fallen by approximately 

55% or 275,282 tons per year (See Figure 6.3.3-2). Following the discussion found in Section 2, 

the assertion in this attainment demonstration that reductions in SO2 emissions within and 

surrounding both nonattainment areas would have the biggest impact on improving PM2.5

concentrations and associated design values has proven accurate. 

Figure 6.3.3-2. Annual SO2 Emissions From EGUs In NC 

6.4 Unmonitored Area Analysis 

The modeled attainment test does not address future air quality at locations where there is not a 

PM2.5 monitor nearby. To guard against the possibility that air quality levels could exceed the 

standard in areas with limited monitoring, Section 3.4 of the Attainment Modeling Guidance

suggests that additional review is necessary, particularly in nonattainment areas where the PM2.5 

monitoring network just meets or minimally exceeds the size of the network required. This 

review is intended to ensure that a control strategy leads to reductions in PM2.5 and its constituent 

pollutants at other locations that could have baseline (and future) design values exceeding the 

NAAQS, were a monitor deployed there. The test is called an “unmonitored area analysis”. The 

purpose of the analysis is to use a combination of model output and ambient data to identify 

areas that might exceed the NAAQS if monitors were located there. 
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The NCDAQ, along with Local and Tribal Programs, currently operates a network of 34 PM2.5

monitors. Twenty-nine of these monitors were established as State and Local Air Monitoring 

Stations (SLAMS). These SLAMS monitors were selected based on specific monitoring 

objectives (background concentration, area of highest concentration, high population, source 

impact, transport, and rural impact) as required by the USEPA and siting scales (micro, middle, 

neighborhood, urban, and regional) established by the USEPA. Of the remaining 8 monitors, 7 

are categorized as “Other” or “Special Purpose Monitors” that were established by NCDAQ to 

evaluate models, study PM2.5 formation and transport, and obtain a better understanding of PM2.5

in North Carolina. The remaining monitor is a Tribal monitor operated by the Eastern Band of 

Cherokee Nation. 

The NCDAQ believes that the density of its monitoring network more than adequately captures 

the full extent of the PM2.5 air quality concerns in North Carolina. With an average of one 

monitor per 3711 km2, this is one of the densest statewide PM2.5 monitoring networks in the 

southeast. A map of each PM2.5 monitor and its position relative to the NCDAQ/ASIP 12-km 

modeling grid is provided in Figure 6.4-1. As can been seen by the figure, the spatial coverage 

of the monitors, and their resulting “nearby” 3x3 arrays, covers the majority of the urban areas 

where PM2.5 tends to be higher. 

Figure 6.4-1. PM2.5 Monitors and Nonattainment Areas with Respect 

to the VISTAS 12km Grid Domain 

The adequacy of the NCDAQ PM2.5 monitoring network is further demonstrated when plotted 

against a projected spatial field of annual PM2.5 design values. Figure 6.4-2 presents the 2009 

future year PM2.5 design value modeling output from this attainment demonstration and the 

location of each PM2.5 monitor in and around North Carolina. This 2009 PM2.5 design value 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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53

spatial field was created by the USEPA’s Modeled Attainment Test Software (MATS). It is 

clear from the MATS analysis that all of the regions of higher, yet attaining, PM2.5 design values 

have numerous representative PM2.5 monitors. There are not any identified PM2.5 hotspots that 

would require any additional monitoring considerations in North Carolina. 

Figure 6.4-2. PM2.5 Monitors and 2009 Modeled Attainment Spatial Field 

6.5 Data Access 

The modeling input and output files are very large and it would not be reasonable to submit all of 

these files with the SIP attainment demonstration. These include all files used to process the 

emissions, meteorology and air quality models and any other files used to develop the modeling. 

To request access to these files please contact the Division of Air Quality, Attainment Planning 

Branch Supervisor at 919.733.3340. 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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7.0 CLEAN AIR ACT SECTION 172(c) REQUIREMENTS 

Section 172(c) of the CAA, as amended, contains the general requirements for nonattainment 

areas. These requirements are listed below and are discussed in more detail in the following 

chapter. 

Section 172(c) Nonattainment Plan Provisions

(1) Reasonable available control measures 

(2) Reasonable further progress 

(3) Actual emissions inventory and periodic emissions inventory 

(4) New source review 

(5) Permit requirements for new and modified sources 

(6) Other measures as may be necessary to provide attainment by specified attainment date 

(7) Compliance with Section 110(a)(2) 

(8) Equivalent techniques 

(9) Contingency measures 

7.1 Reasonable Available Control Measures 

Section 172(c)(1) of the CAA requires SIPs to provide for the implementation of all RACM to 

demonstrate attainment as expeditiously as practicable. A subset of RACM is reasonably 

available control technology (RACT), which relates specifically to stationary point sources. 

In April 2007, the USEPA promulgated the PM2.5 Implementation Rule. In this rule the UESPA 

established what would be required for RACM and RACT for PM2.5 nonattainment areas. The 

USEPA stated that if a state projects that an area will attain the standard within 5 years of 

designation as a result of existing measures (i.e. projected to have a design value of 14.5 or 

lower), then the State may conduct a limited RACT and RACM analysis that does not involve 

additional air quality modeling. Additionally, if a state could not achieve significant emissions 

reductions during 2008 due to time needed to implement the potential measures or other relevant 

factors, then the state could conclude that there are no further RACM for the nonattainment area 

that would advance the attainment date by one year or more. 

The predicted design values for the Hickory and Triad nonattainment areas are 13.1 μg/m3

 and 

13.4 μg/m3

, respectively, well below the annual PM2.5 standard; therefore, the NCDAQ may 

conduct a limited RACT and RACM analysis. A couple of RACM type measures have already 

been implemented by the NCDAQ. First is the CSA that was passed in 2002 by the North 

Carolina General Assembly. This legislation capped SO2 emissions from coal-fired power 

plants, with implementation beginning as early as 2006. Another is the NCDAQ open burning 

rule. With the adoption of the revisions to the open burning rule in 2004, open burning during 

code Orange or higher air quality action days was prohibited. The prohibition of open burning 

will reduce fine particulate matter on days that are forecasted to have elevated PM2.5

concentrations. Copies of these measures are included in Appendix M. 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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55

Additional RACM measures could not be implemented during 2008. It would take at least two 

years to complete rule making and another eighteen months to two years for implementation of 

control measures. There are no other RACM available to advance the attainment date. 

7.2 Reasonable Further Progress

In the PM2.5 Implementation Rule, the USEPA maintained that an area that demonstrates 

attainment by 2010 would be considered to have satisfied the RFP requirement and need not 

submit any additional material to satisfy this requirement. The USEPA will view the attainment 

demonstration as demonstrating that the area is making reasonable further progress toward 

attainment. 

7.3 Actual Emissions Inventory 

Section 172(c)(3) requires the development of a comprehensive, accurate current inventory of 

actual emissions from all sources in the nonattainment area. Such inventory is due two years 

after the effective date of the PM2.5 nonattainment designations, i.e., April 5, 2007. The NCDAQ 

met this requirement through the submittal of the 2002 emission inventories under the CERR for 

the North Carolina counties in this nonattainment area. 

The NCDAQ submitted statewide emissions for area, non-road mobile and highway mobile 

sources. For stationary point sources, The NCDAQ submitted inventories for those counties 

without a local program. The final 2002 emission inventories used in the attainment 

demonstration went through the public hearing process with the full attainment demonstration, 

which included any updates or revisions that were necessary since the CERR submittal. 

7.4 Periodic Emissions Inventory 

Section 172(c)(3) requires periodic inventory submittals. The NCDAQ plans to meet this 

requirement through the CERR and the recently promulgated Air Emissions Reporting 

Requirements (AERR) submittals. As such, the NCDAQ submitted the 2005 emissions 

inventory June 1, 2007 and will submit the 2008 emissions inventory on or before June 1, 2010. 

Similar to the 2002 CERR submittal, the CERR and AERR submittals will include point sources 

for all but those counties with local programs, and statewide area, non-road mobile and highway 

mobile sources. 

7.5 Permit Program Requirements 

Sections 172(c)(5) requires a permit program consistent with the requirements of Section 173. 

On November 30, 2005, the NCDAQ submitted amendments to the nonattainment new source 

review (NNSR) rules contained in 15A NCAC 2D .0531 to the USEPA for review and approval. 

These rules adopted the new offset requirement. Further, on March 16, 2007, the NCDAQ 

submitted amendments to 15A NCAC 2D .0530 Prevention of Significant Deterioration (PSD) 

permitting rules to the USEPA. The NCDAQ believes that the adoption and submittal of the 

NNSR and the PSD rules meet the “prevention of significant deterioration” requirement of 

Section 110(a)(2)(D)(i) since major sources in North Carolina are subject to PSD and NNSR 

programs. Finally, the NCDAQ adopted an Emissions Banking Rule, 15A NCAC 2D .2300 to 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

North Carolina Attainment Demonstration August 21, 2009 

56

establish a bank where sources could place their shutdown credits, as well as credits achieved 

through installing controls that go above and beyond what is required. The NCDAQ believes it 

has met the permit program requirements for a PM2.5 nonattainment area. 

7.6 Other Measures 

Section 172(c)(6) requires the nonattainment SIPs to include enforceable limitation and other 

control measures, along with schedules for compliance as needed to demonstrate attainment. 

Section 5.0 of this document discusses in detail the Federal and State measures that were 

modeled to show attainment. Appendix M contains the rules and compliance schedules. 

7.7 Compliance with Section 110(a)(2) 

Section 172(c)(7) requires nonattainment SIPs to meet the applicable provisions of Section 

110(a)(2). On October 2, 2007, the USEPA provided guidance on SIP elements required under 

Section 110(a)(1) and (2) for the 8-hour ozone and PM2.5 NAAQSs. Regarding the 1997 PM2.5

NAAQSs, all SIP elements are adequately covered. 

7.8 Equivalent Techniques 

The NCDAQ believes that the procedures for modeling, emissions inventory and planning 

follow the USEPA guidance and is not requesting approval for equivalent techniques, as 

envisioned under Section 172(c)(8). 

7.9 Contingency Measures 

Section 172(c)(9) requires that the nonattainment SIP contain specific measures that would take 

effect upon a State’s failure to attain the PM2.5 standard in a given area. These contingency 

measures must be fully adopted rules or control measures that are ready to be implemented 

quickly upon failure to meet the standard by the attainment date. 

In the PM2.5 Implementation Rule, the USEPA stated that the measures should provide for 

emission reductions equivalent to about one year of reductions needed for RFP. However, since 

North Carolina is able to model attainment of the PM2.5 NAAQS within five years of 

designation, RFP is not required. The USEPA’s guidance to the NCDAQ was to have 

contingency measures that amounted to one-seventh of the emission reductions that occurred 

between the base year 2002 and the attainment year 2009, or approximately one year’s worth of 

emission reductions. Another suggestion was to do sensitivity modeling to determine 

approximately the level of emission reductions needed to model 15.0 μg/m3

 and use one-seventh 

of this emission reduction level to determine the amount of contingency measures needed. 

The NCDAQ’s attainment demonstration includes expected emission reductions due to the CSA 

legislation. These emission reductions went well beyond what was needed to attain the annual 

PM2.5 NAAQS of 15.0μg/m3

, evident by the predicted future design values being greater than 

1.5 μg/m3

 below the standard. Therefore, the NCDAQ thought it was unreasonable to require 

contingency measures of one-seventh of the SO2 emission reduction modeled when the State had 

already reduced a significant amount of the precursor pollutants throughout the State. 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

North Carolina Attainment Demonstration August 21, 2009 

57

Additionally, the NCDAQ did not believe it was a wise use of State resources to perform further 

modeling to determine the approximate level of emissions needed to just attain the standard 

when both nonattainment areas have already attained the annual PM2.5 NAAQS. 

Therefore, the NCDAQ has documented the expected 2009 utility emissions, based on the latest 

CSA compliance plans, which go beyond what was modeled in the attainment demonstration, as 

well as the estimated emission reductions expected between 2009 and 2010. All of these 

emission reductions will take place without further action from the State. Since the purpose of 

the contingency measures is to provide for the implementation of measures in the event an area 

fails to attain the NAAQS and the areas have already attained the standard, the NCDAQ believes 

it has met the spirit of this requirement. 

Since the most significant man-made emissions contributor to PM2.5 formation in North Carolina 

is the precursor pollutant SO2, the NCDAQ has elected to have only SO2 contingency measures. 

The USEPA has stated in the Implementation Rule that the reductions from SO2 emissions could 

be from not only the nonattainment area but also emissions within a distance that may be up to 

200 kilometers (km) from the nonattainment area. The NCDAQ elected to go outside the 

nonattainment area for contingency measures. The exact regions of influence that were used are 

discussed in detail in Appendix N. 

The contingency plan relies on the already adopted CSA. As stated earlier, this legislation will 

require SO2 emission reductions from coal-fired power plants. For several coal-fired electric 

generating units subject to the CSA, the SO2 controls came on-line either during 2009 or 2010. 

Full implementation of these units was not modeled in the attainment demonstration, therefore 

they are reductions above what was needed to show attainment and would be implemented 

without further action from the State or the USEPA. Additionally, when the attainment 

demonstration modeling project started, the latest compliance plan for CSA was the 2006 plan. 

The utilities companies now have a better understanding of what the SO2 emissions will be in 

2009 and are reflected in the 2009 CSA compliance plan. The difference between the emissions 

modeled and the current expectations for the 2009 emissions are further emission reductions that 

are expected to occur that were not modeled as part of the attainment demonstration. 

The 2002 baseline emissions for the two nonattainment areas’ regions of influence were 215,080 

and 401,290 tons of SO2 per year for the Hickory and Triad areas, respectively. The NCDAQ 

has determined that SO2 emissions will be reduced beyond what was modeled by an additional 

46,000 tons per year in the Hickory area and 43,000 tons per year in the Triad area. This results 

in a twenty-two percent and eleven percent reduction from the 2002 baseline SO2 emissions in 

the Hickory and Triad areas, respectively. The analysis of the emission reductions is included in 

Appendix N. 

Based on the significant reductions that are expected between what was modeled for the 

attainment demonstration and what is expected to occur between 2009 and 2010, the NCDAQ 

believes that the existing control measures required by the CSA is sufficient to satisfy the 

contingency measures requirement. 
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8.0 MOTOR VEHICLE EMISSIONS BUDGETS 

8.1 Transportation Conformity 

The purpose of transportation conformity is to ensure that Federal transportation actions 

occurring in a nonattainment area do not hinder the area from attaining and/or maintaining the 

annual PM2.5 standard. This means that the level of emissions estimated by the NCDOT or the 

metropolitan planning organizations for the Transportation Implementation Plan and Long Range 

Transportation Plan must not exceed the motor vehicle emission budgets (MVEBs) as defined in 

this attainment demonstration SIP. 

The NCDAQ consults with the transportation partners as one of the requirements in developing 

the attainment demonstration SIP and setting MVEBs. The NCDAQ sent out a request for 

comments on setting the geographic extent of the MVEBs to all of the transportation partners. In 

the letter, NCDAQ expressed its preference for setting county level budgets and some of the 

reasons why NCDAQ believed county level budgets were appropriate. Additionally, the 

NCDAQ consulted the partners for the data used in the development of the MVEBs, as well as 

the data used in the attainment demonstration modeling. These correspondences and the 

responses received from the transportation partners can be found in Appendix B. 

8.2 Pollutants to be Considered 

40 CFR 93.119(f)(7) through (10) identifies the pollutants for PM2.5 for which regional emissions 

analysis needs to be performed for transportation conformity purposes. Only primary, or direct, 

PM2.5 tailpipe emissions must be considered for transportation conformity regional emissions 

analysis. The precursor pollutants NOx, VOC, SO2 and ammonia, as well as reentrained road 

dust only need to be considered if the NCDAQ and/or the USEPA has deemed the pollutant as a 

significant contributor to the overall PM2.5 nonattainment problem. 

The PM2.5 precursor NOx is presumed to be a significant contributor to the PM2.5 nonattainment 

problem by the USEPA. The NCDAQ has determined that NOx is a relatively minor contributor 

to the PM2.5 concentrations in North Carolina. However, the NCDAQ is not asserting that NOx

is an insignificant precursor for the 1997 PM2.5 standard. Therefore, the NCDAQ will establish 

county level MVEBs for NOx for all three PM2.5 nonattainment counties. 

For the purpose of this attainment demonstration, VOC and ammonia are presumed to be 

insignificant contributors to the PM2.5 nonattainment problem by the USEPA. The NCDAQ 

agrees with the USEPA that both VOC and ammonia are insignificant contributors to the PM2.5

nonattainment problem in North Carolina. The discussion of the insignificance of these 

precursors is presented in Section 2.0 and in Appendix O. Additionally, the NCDAQ has 

determined that reentrained road dust is not a significant contributor to the overall PM2.5

nonattainment problem. This is discussed further in Appendix F.3. 

The PM2.5 precursor SO2 could not be deemed insignificant to the overall PM2.5 nonattainment 

problem since sulfate is such a large fraction of the PM2.5 composition. However, the NCDAQ 

has determined that SO2 emitted by the mobile source sector is insignificant. The USEPA in its 

Federal Register notice for PM2.5 does not address the mobile sector in its listing of significant 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

North Carolina Attainment Demonstration August 21, 2009 

59

sources of SO2 emissions. North Carolina agrees with the following statements addressing SO2

from on-road mobile emissions as published in the May 6, 2005 Federal Register, 70 FR 24283: 

While speciated air quality data show that sulfate is a relatively significant component 

(e.g., ranging from nine to 40 percent) of PM2.5 mass in all regions of the country, 

emissions inventory data and projections show that on-road emissions of SOx constitute a 

‘‘de minimis’’ (i.e., extremely small) portion of total SOx emissions. Emissions inventory 

data for 1999 for the 372 potential PM2.5 nonattainment counties for PM2.5 (based on 

1999–2001 air quality data) show that on-road sources were responsible for only two 

percent of total SOx emissions. 

Furthermore, EPA has already adopted two regulations that will greatly reduce 

emissions of SOx from on-road sources by the time such regulations are both in full effect 

in 2009. .........This regulation will reduce the sulfur content of diesel fuel by 

approximately 97 percent nationally when fully effective. 

Although sulfate is a significant component to the PM2.5 nonattainment problem in North 

Carolina, the majority of the SO2 emissions in 2009 come from the stationary point source sector 

with the mobile source sector only contributing one half of one percent (0.05 %). This is 

consistent with what the USEPA stated above. The discussion about the significance of mobile 

source SO2 emissions can be found in Appendix F.3. For the reasons discussed, the NCDAQ has 

determined that mobile source SO2 emissions are insignificant to the PM2.5 nonattainment 

problem. 

To summarize so far, the NCDAQ has determined that the precursor pollutants VOC, ammonia 

and mobile source SO2, as well as reentrained road dust are insignificant contributors to the 

overall PM2.5 nonattainment problem in North Carolina. Therefore, the NCDAQ is not 

establishing MVEBs for these pollutants. 

An affirmative insignificance finding from the USEPA only relieves the transportation partners 

from a regional emissions analysis for these pollutant emissions for these areas and does not 

relieve them of the other transportation conformity requirements. The transportation partners 

will need to note the insignificance finding for these pollutants (if found adequate and approved 

by the USEPA) in future conformity determinations. 

The only mobile source pollutant left to be addressed for transportation conformity purposes is 

direct PM2.5 emissions. 

8.3 Highway Mobile Source Direct PM2.5 Emissions 

40 CFR 93.109(k) in the Transportation Conformity Rule Amendments for the new 8-hour ozone 

and fine particulate matter NAAQSs addresses areas with insignificant motor vehicle emissions 

as follows, 

Notwithstanding the other paragraphs in this section, an area is not required to satisfy a 

regional emissions analysis for §93.118 and/or §93.119 for a given pollutant/precursor 

and NAAQS, if EPA finds through the adequacy or approval process that a SIP 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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60

demonstrates that regional motor vehicle emissions are an insignificant contributor to 

the air quality problem for that pollutant/precursor and NAAQS. The SIP would have to 

demonstrate that it would be unreasonable to expect that such an area would experience 

enough motor vehicle emissions growth in that pollutant/precursor for a NAAQS 

violation to occur. 

The rule suggests that such a finding would be based on a number of factors, including the 

percentage of motor vehicle emissions in the context of the total SIP inventory, the current state 

of air quality as determined by monitoring data for that NAAQS, the absence of SIP motor 

vehicle control measures, and historical trends and future projections of the growth of motor 

vehicle emissions. 

The NCDAQ believes strongly that the primary PM2.5 emissions from mobile sources do not 

contribute significantly to the PM2.5 nonattainment problem. However, the USEPA has indicated 

they will not approve a SIP that does not set MVEBs for primary PM2.5 for the Triad. Therefore, 

the NCDAQ will establish county level MVEBs for primary PM2.5 for the Triad PM2.5

nonattainment counties. The sections that follow discuss the insignificance of PM2.5 emissions 

Mobile Source PM2.5 Emissions Insignificant

The NCDAQ has examined the sources of PM2.5 emissions and their contribution to PM2.5 

formation in the nonattainment counties. This was accomplished using the 2009 emissions 

inventories developed for the attainment demonstration modeling. The percent contribution of 

primary PM2.5 from mobile sources is 1.6 % and 4.8 % for the Hickory and Triad nonattainment 

areas, respectively. 

Additionally, the NCDAQ performed sensitivity modeling in order to address the language of 

Section 93.109(k) in the Transportation Conformity Rule Amendments; “The SIP would have to 

demonstrate that it would be unreasonable to expect enough motor vehicle emissions growth in 

that pollutant/precursor for a NAAQS violation to occur”. The primary PM2.5 emissions from 

on-road mobile sources were doubled in the nonattainment areas, therefore, simulating a 

doubling of the VMT. The results of the emissions sensitivities showed such similar results that 

looking at just the difference between two air quality model simulations, one with base case 

emissions and another with reduced emissions inputs, showed no change. In both nonattainment 

areas, the modeling future design value increased by less than 0.1 μg/m3

.

Based on the analysis discussed in detail in Appendix F.3, the NCDAQ steadfastly believes that 

the on-road mobile PM2.5 emissions are insignificant contributors to the PM2.5 nonattainment 

problem. The NCDAQ considers it unreasonable to expect that the PM2.5 nonattainment areas 

will experience enough motor vehicle PM2.5 emissions growth for a future PM2.5 violation to 

occur due to mobile source direct PM2.5 emissions. 

Due to above analysis and agreement from the USEPA, budgets for direct PM2.5 will not be set 

for the Hickory non-attainment area. An affirmative insignificance finding from the USEPA 

only relieves the transportation partners from a regional emissions analysis for PM2.5 emissions 

for this area and does not relieve them of the other transportation conformity requirements. The 
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North Carolina Attainment Demonstration August 21, 2009 

61

transportation partners will need to note the PM2.5 insignificance finding (if found adequate and 

approved by the USEPA) in future conformity determinations. 

8.4 Establishing PM2.5 and NOx Motor Vehicle Emission Budgets 

As part of the consultation process on setting MVEBs, the NCDAQ sent out a request for 

comment on setting the geographic extent of the MVEBs to all of the transportation partners. In 

the letter, the NCDAQ expressed its preference for setting county level budgets and some of the 

reasons why the NCDAQ believed county level budgets were appropriate. With respect to the 

PM2.5 nonattainment areas, the comments received were in agreement with the NCDAQ. 

Additionally, the NCDAQ consulted the partners for the data used in the development of the 

MVEBs, as well as the data used in the attainment demonstration modeling. These 

correspondences and the responses received from the transportation partners can be found in 

Appendix B. 

MVEBs will be set for the attainment year 2009. By the time the MVEBs are found adequate or 

approved by the USEPA, the next transportation conformity regional emissions analysis should 

be for years 2009 and beyond. Therefore, MVEBs will not be set for the baseline year 2002. 

Although the emissions are usually expressed in terms of tons, the MVEBs will be set in terms of 

kilograms (kg). The reason for this assertion is because the MOBILE model generates the 

emissions factors in grams per mile. In past conformity exercises, there have been some issues 

with conversion to tons, as well as concerns with how the MVEBs were rounded. Setting 

MVEBs in kilograms will avoid these issues in future conformity determinations. 

Tables 8.4-1 and 8.4-2 below display the Triad highway mobile PM2.5 and the Triad and Hickory 

highway mobile NOX emissions expressed in tons per year and the corresponding kilograms per 

year values for 2009. These two tables are for reference purposes only and are not the tables 

presenting the 2009 MVEBs, which is discussed next. 

Table 8.4-1. County Level PM2.5 Highway Mobile Emissions for 2009 

County MVEB 

(Tons/year) 

MVEB 

(Kilograms/year) 

Davidson 78.4 71,152 

Guilford 181.1 164,286 

Table 8.4-2. County Level NOX Highway Mobile Emissions for 2009 

County MVEB 

(Tons/year) 

MVEB 

(Kilograms/year) 

Catawba 3183.4 2,887,955 

Davidson 4780.2 4,336,567 

Guilford 11,034.9 10,010,856 
The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 

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62

The NCDAQ will set MVEBs, for transportation conformity purposes, as county budgets for 

2009. Tables 8.4-3and 8.4-4 below present the Triad PM2.5 and the Triad and Hickory NOX

MVEBs in kilograms per year, by county. Upon the USEPA’s affirmative adequacy finding for 

these county level sub-area MVEBs, these MVEBs will become the applicable MVEBs for each 

county. Please see Appendix F.3, Section 4 for a detailed discussion on the planning 

assumptions and methodology used to develop these budgets. 

Table 8.4-3. County Level PM2.5 MVEBs for 2009 

County MVEB 

(Kilograms/year) 

Davidson 71,152 

Guilford 164,286 

Table 8.4-4. County Level NOx MVEBs for 2009 

County MVEB 

(Kilograms/year) 

Catawba 2,887,955 

Davidson 4,336,567 

Guilford 10,010,856 
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9.0 REFERENCES 

Douglas, S., et al. Characterization of Meteorology and Its Relationships to Fine Particle Mass 

and Visibility in the VISTAS Region, Final Report. ICF International. December 2006. 

Frank, N. H. Retained Nitrate, Hydrated Sulfates, and Carbonaceous Mass in Federal Reference 

Method Fine Particulate Matter for Six Eastern U.S. Cities. J. Air & Waste Manage. Assoc. 2006

56:500–511. 

Stauffer, D. R. and N. L. Seaman, 1990: Use of four-dimensional data assimilation in a 

limited-area mesoscale model. Part I: Experiments with synoptic-scale data. Mon. Wea. 

Rev., 118, 1250-1277. 

Tesche, T.W., et al. Operational Evaluation of the MM5 Meteorological Model Over the 

Continental United States: Protocol for Annual and Episodic Evaluation. Office of Air Quality 

Planning and Standards. AG-TS-90/158. July 2002. 

USEPA Guidance on the Use of Models and Other Analyses for Demonstrating Attainment of 

Air Quality Goals for Ozone, PM2.5, and Regional Haze. EPA -454/B-07-002. April 2007.