## 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, 2009The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 i (This page intentionally left blank)The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 ii 

### PREFACE
This document contains North Carolina's atta inment demonstration for the Hickory and Greensboro/Winston-Salem/High Point fine pa rticulate matter nonattain ment 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 iii 

### EXECUTIVE SUMMARY

INTRODUCTION

Fine particulate matter, also known as fine particles and PM 2.5 , refers to airborne particles less than or equal to 2.5 micrometers (μm) in diameter . Fine particles are tr eated as though they are a single pollutant, but they come from many different sources and are composed of many different compounds. PM 2.5 exposure adversely affects human h ealth, especially respiratory and cardiovascular systems. Individu als particularly sensitive to PM 2.5 exposure include children, people with heart and lung di sease, and older adults.

A variety of meteorological and geographic factors influence the concentration levels of fine particles, including both the regi onal and local distribution of urbanized areas, primary and precursor emissions sources, and natural features such as oceans and forests. PM 2.5 concentrations can also be high and exceed the national ambient air quality standards (NAAQSs) for fine particulate matter at any time of the y ear. Therefore, the United States Environmental Protection Agency (USEPA) mandate s the year round monitoring of PM 2.5 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 PM 2.5 (40 CFR 50.7), setting the standard at a 15.0 micrograms per cubic meter (μg/m 3 ) annual average and at a 65 μg/m 3 daily or 24-hour average. A violation of the annual PM 2.5 NAAQS occurs when the annual average PM 2.5 concentration averaged over a three consecutive year period is equal to or greater than 15.1 μg/m 3 . A violation of the daily PM 2.5 NAAQS occurs when the annual 98 th percentile of daily PM 2.5 concentration averaged over a three consecutive year period is equal to or greater than 66 μg/m 3 . The annual or daily PM 2.5 design value for a nonattainment area is the highest design value for any monitor in that area.

The USEPA designated areas as nonatta inment for the annual and daily PM 2.5 NAAQSs based upon air quality monitoring data measured dur ing 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 design ated as nonattainment for violating the annual PM 2.5 standard (Figure 1). All areas of North Carolina met the daily PM 2.5 standard. This PM 2.5 attainment demonstration submittal covers the Hickory PM 2.5 nonattainment area (Catawba County) and Greensboro/Wi nston-Salem/High Point PM 2.5 nonattainment area (referred to as the Triad area and consists of Davids on and Guilford Counties) with resp ect to the violations of the annual PM 2.5 standard.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 iv Figure 1. Annual PM 2.5 Nonattainment Boundaries for North Carolina

When the annual PM 2.5 concentrations in both nonattain ment areas are analyzed by the percentages of their individual component spec ies, the organic carbon (OC) and sulfate (SO 4 ) components each account for approximately one-third of the total PM 2.5 mass, the ammonium component makes up approximately ten percent of the total PM 2.5 mass, and the remaining nitrate (NO 3 ), elemental carbon, crustal material, and particle bound water components each contribute approximately five percent or less of the total PM 2.5 mass. The percentages of species contribution fluctuate throughout the year with the most significant changes to SO 4 and NO 3 . SO 4 is more pronounced in the summertime or warm season months than during the wintertime. NO 3 fluctuates from almost undetectable in the summertime to as much as ten percent contribution of the total PM 2.5 mass during the coldest portion of the winter.

The speciated analysis of the PM 2.5 concentrations in the Hickory and Triad PM 2.5 nonattainment areas demonstrates that the OC and SO 4 components are the most impor tant portions of the total PM 2.5 mass throughout the year. OC is predominatel y attributed to biogenic emissions sources. SO 4 is associated with sulfur dioxide (SO 2 ) emissions. When evaluated across North Carolina and also throughout both nonattainment areas and surrounding regions, the SO 2 is primarily from the point source sector . For this reason, SO 2 emissions controls from point sources are believed to be the most appropriate strategy for addressing the PM 2.5 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-r oad mobile sources emissions. The expected Federal and State control measures were modeled for the attainment year of 2009.

The Federal control measures that were modele d included the Tier 2 vehicle standards; the heavy-duty gasoline and diesel high way vehicle standards; low sulf ur gasoline and diesel fuels, large non-road diesel engines standards; the non-road spark-ignition e ngines and recreational engines standard; and the Clean Air Interstate Rule (CAIR). Due to the Court challenges ofThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 v 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 in cluded the Clean Air Bill, in which the vehicle emissions inspection and maintenance program was expanded from 9 counties to 48; the NO x SIP Call Rule, CAIR, and the Clean Smokestack s Act, which will significantly reduce SO 2 emissions from the large electrical generation units with implementation beginning prior to the 2009 attainment year and well in advance of the Federal Clean Ai r Interstate Rule. The Clean Smokestacks Act further requires the coal-fir ed power plants to meet an annual SO 2 emissions cap without an option of emissions trad ing from outside of North Carolina.

ATTAINMENT TEST RESULTS

A modeled attainment test was applied to the ai r quality modeling results to determine if the annual PM 2.5 NAAQS will be met by the attainment year 2009. The baseline period for the air quality modeling was centered on 2002 or the midpoi nt of the three years used for nonattainment designations.

For all FRM sites in the Hickory and Triad PM 2.5 nonattainment areas, the future annual PM 2.5 concentrations derived from the modeled a ttainment test were less than 15.0 μg/m 3 (Table 1). Therefore, the modeling assessment indicated th at both nonattainment areas will attain the annual PM 2.5 NAAQS by 2009.

Table 1. Current And Future Year Predicted Annual PM 2.5 Concentrations

County FRM Monitoring Site 2001-2003, Current Design Value (μg/m 3 ) 2009, Future Year Predicted Design Value (μg/m 3 ) 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 (N CDAQ) provided a strong set of supplemental analyses further supporting th at the Hickory and Triad PM 2.5 nonattainment areas will attain the annual PM 2.5 NAAQS by April 5, 2010. These analyses included evaluating the air quality modeling from an absolute percentage reduc tion perspective compared to the annual PM 2.5 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 m odeling attainment demonstra tion, in conjunction with the supplemental analyses, provides the necessary evidence that the Hickory and Triad PM 2.5 nonattainment areas will attain the annual PM 2.5 NAAQS by the April 5, 2010 attainment date and furthermore continue to maintain the daily PM 2.5 NAAQS. In fact, both nonattainment areas have already attained the 1997 annual PM2.5 stan dard with the 2006-2008 ambient air quality data, one year earlier than required.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 vi 

### 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 PM 2.5 in the North Carolina Nonattainment Areas ........................... 5 1.5 Clean Air Act Requirements ................................................................................................ . 6
2.0 SIGNIFICANCE OF PM 2.5 PRECURSOR POLLUTANTS 7 2.1 PM 2.5 Component Species Analysis ..................................................................................... 7 2.2 Attribution of Emissions Sources ......................................................................................... 9 2.3 Clean Air Fine Particulate Implementation Ru le Presumptions on Precursor Pollutants ... 12
3.0 ATTAINMENT DEMONSTRAT ION 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 .......................................................................................... 1 9 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 .............................................................................................. 2 6 3.5.2 Stationary Area Sources ............................................................................................... 2 7 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 Go als, 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 Pe rformance Summary .................................................................. 37The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 vii 5.0 CONTROLS APPLIED 39 5.1 Federal Control Measures .................................................................................................. . 39 5.1.1 Tier 2 Vehicle Standards .............................................................................................. 3 9 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 NO x SIP Call in Surrounding States ............................................................................ 40 5.1.6 Clean Air Interstate Rule.............................................................................................. 4 0 5.2 State Control Measures .................................................................................................... ... 41 5.2.1 Clean Air Bill .......................................................................................................... ..... 41 5.2.2 NO x 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.............................................................................................. 4 3
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 Additio nal Reductions in Emissions ...................................... 49 6.4 Unmonitored Area Analysis ............................................................................................... 5 1 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 PM 2.5 and NO x Motor Vehicle Emission Budgets ......................................... 61
9.0 REFERENCES 63The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 viii 

### LIST OF FIGURES

Figure 1. Annual PM 2.5 Nonattainment Boundaries for North Carolina ....................................... iv Figure 1.3-1. Annual PM 2.5 Nonattainment Boundaries for North Carolina .................................. 3 Figure 1.3-2. PM 2.5 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 PM 2.5 Speciation for 2004 ................................................................ 5 Figure 2.1-1. 2002 PM 2.5 Speciated Mass Contribution at Hickory Using SANDWICH .............. 8 Figure 2.1-2. 2002 PM 2.5 Speciated Mass Contribution at Lexington Using SANDWICH ........... 8 Figure 2.1-3. 2002 PM 2.5 Speciated Mass Contribution at Mendenhall Using SANDWICH ........ 9 Figure 2.2-1. Hickory PM 2.5 Nonattainment Area SO 2 Emissions in 2002 .................................. 10 Figure 2.2-2. Triad PM 2.5 Nonattainment Area SO 2 Emissions in 2002 ...................................... 11 Figure 2.2-3. North Carolina Total SO 2 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. Percenta ge of Cell in PM 2.5 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 PM 2.5 Average Concentrations for the FRM Monitors in the Hickory and Triad Nonattainment Areas ..................................................................................................... ...... 50 Figure 6.3.3-2. Annual SO 2 Emissions From EGUs In NC .......................................................... 51 Figure 6.4-1. PM 2.5 Monitors and Nonattainment Areas w ith Respect to the VISTAS 12km Grid Domain ........................................................................................................................ .................. 52 Figure 6.4-2. PM 2.5 Monitors and 2009 Modeled A ttainment Spatial Field ................................. 53The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 ix 

### LIST OF TABLES

Table 1. Current And Future Year Predicted Annual PM 2.5 Concentrations .................................. v
Table 1.3-1. PM 2.5 Concentrations and Design Values for the FRM monitors in the Hickory and Triad PM 2.5 Nonattainment Areas ................................................................................................... 4 Table 3.4.1-1: Vertical Layer Definition For MM5 and CMAQ .................................................. 23
Table 3.5-1. 2002 Annual Em ission Summaries .......................................................................... 25
Table 4.2.1-1. Established Model Perform ance Goals and Criteria for the PM 2.5 Component Species ....................................................................................................................... ................... 32
Table 5.2.1-1 OBDII Phase-in Effective Dates ............................................................................ 42 Table 6.2-1. Quarterly Mean and Annual Mean PM 2.5 Mass Estimates for 2009 ........................ 45
Table 6.3.1-1. Number of Cells within Concentrati on Bins. Increases (dec reases) 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 PM 2.5 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 PM 2.5 Nonattainment Areas ........................................................................................................... ......... 50 Table 8.4-1. County Level PM 2.5 Highway Mobile Emissions for 2009 ...................................... 61 Table 8.4-2. County Level NO X Highway Mobile Emissions for 2009 ....................................... 61 Table 8.4-3. County Level PM 2.5 MVEBs for 2009 ..................................................................... 62 Table 8.4-4. County Level NO x MVEBs for 2009 ....................................................................... 62The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 x 

### LIST OF APPENDICES

Appendix A: Policy and Memorandums

Appendix B: Stakeholders Correspondence Re garding Motor Vehicle Emissions Budgets

Appendix C: Air Quality Data

Appendix D: Mode ling 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 VOC s to PM2.5 Attainment in North Carolina

Appendix P: Supporting Documentat ion from VISTAS and ASIP

Appendix Q: Public Notice Report, Comments Received, and ResponsesThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 xi (This page intentionally left blank)The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 1 

### 1.0 INTRODUCTION

1.1 What is fine particulate matter?
Fine particulate matter, also known as fine particles and PM 2.5 , refers to airborne particles less than or equal to 2.5 micrometers (μm) in diameter . Fine particles are tr eated as though they are a single pollutant, but they come from many different sources and are composed of many different compounds. PM 2.5 exposure adversely affects human h ealth, especially respiratory and cardiovascular systems. Individu als particularly sensitive to PM 2.5 exposure include children, people with heart and lung di sease, and older adults.

PM 2.5 can be liquid, solid, or can have a solid core surrounded by liquid. PM 2.5 can include material produced by combustion, photochemical reactions, and can contain salt from sea spray and soil-like particles. Partic les are distinguished based on th e method of formation. Primary particles are particles directly emitted into th e atmosphere and retain the same chemical composition as when they were released. Second ary particles are those formed through chemical reactions involving atmospheric oxygen, water vapor, hydroxyl radi cal, nitrates, sulfur dioxide (SO 2 ), oxides of nitrogen (NO x ), and organic gases from natu ral and anthropogenic sources. PM 2.5 can therefore be composed of varying am ount of different spec ies, 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 PM 2.5 and its precursors are coal-f ired power plants, industrial boilers and other combustion sources. Thes e emissions are often transported over large distances. Other sources of PM 2.5 emissions include mobile s ources, 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 regi onal and local distribution of urbanized areas, primary andThe 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. PM 2.5 concentrations can also be high and exceed the national ambient air quality standards (NAAQSs) for fine particulate matter at any time of the y ear. Therefore the United States Environmental Protection Agency (USEPA) mandate s the year round monitoring of PM 2.5 concentrations throughout the country ( 40 CFR 58.App. D, 4.7).

1.2 What is the National Am bient Air Quality Standard?
In 1997, the USEPA promulgated the primary (health) and secondary (welfare) NAAQSs for PM 2.5 (40 CFR 50.7), setting the standard at a 15.0 micrograms per cubic meter (μg/m 3 ) annual average and at a 65 μg/m 3 daily or 24-hour average. A violation of the annual PM 2.5 NAAQS occurs when the annual average PM 2.5 concentration averaged over a three consecutive year period is equal to or greater than 15.1 μg/m 3 . A violation of the daily PM 2.5 NAAQS occurs when the annual 98 th percentile of daily PM 2.5 concentration averaged over a three consecutive year period is equal to or greater than 66 μg/m 3 . The annual or daily PM 2.5 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 PM 2.5 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 nonatta inment for the annual and daily PM 2.5 NAAQSs based upon air quality monitoring data measured dur ing 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 design ated as nonattainment for violating the annual PM 2.5 standard (Figure 1.3-1). All areas of North Carolina met the daily PM 2.5 standard. This PM 2.5 attainment demonstration submittal covers the Hickory PM 2.5 nonattainment area (Catawba County) and Greensbor o/Winston-Salem/High Point PM 2.5 nonattainment area (referred to as the Triad area a nd consists of Davidson and Guilfor d Counties) with respect to the violations of the annual PM 2.5 standard.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 3 Figure 1.3-1. Annual PM 2.5 Nonattainment Boundaries for North Carolina

Figure 1.3-2 displays the distribution of the PM 2.5 monitoring sites acro ss North Carolina. A closer view of the PM 2.5 federal reference method (FRM) mo nitoring sites in the Hickory and Triad PM 2.5 nonattainment areas is found in Figure 1.3- 3. The Hickory monitoring site is the only FRM monitor in the Hickory PM 2.5 nonattainment area. There are two FRM monitoring sites, Lexington and Mendenhall, in the Triad PM 2.5 nonattainment area.

Figure 1.3-2. PM 2.5 Monitoring Sites In North CarolinaThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 4 Figure 1.3-3. PM2.5 FRM Monitoring Sites in th e Hickory and Triad Nonattainment Areas

Table 1.3-1 contains the quart erly and annual average PM 2.5 concentrations for the FRM monitors in the PM 2.5 nonattainment areas for the three-ye ar period used in the nonattainment designation determinations. Table 1.3-1 also presents the 2001-2003 PM 2.5 design value for the FRM monitors based on these quart erly and annual averages. The historic quarterly, yearly, and design value air quality data for the FRM monitors in both PM 2.5 nonattainment areas can be found in Appendix C.

Table 1.3-1. PM 2.5 Concentrations and Design Values for the FRM monitors in the Hickory and Triad PM 2.5 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

MendenhallThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 5 As mentioned in Section 1.1, PM 2.5 is composed of many species from varying sources. Figure 1.3-4 presents the North Ca rolina statewide averaged PM 2.5 speciation data from the speciation trends networ k (STN) monitors for th e year 2004. The figure presents sulfates (SO 4 ) and organic carbons (OC) as the main contributors to PM 2.5 , each with 29%; ammonium (NH 4 ) contributes 11%; nitrates (NO 3 ) contribute 7%; elemental carbon (E C) is approximately 4%; and crustal material is 3% of the total PM 2.5 mass. The “other” portion of the PM 2.5 that accounts for 17% of the mass can be attributed to water (H 2 O), sea salts, and other trace materials captured with the STN monitors.

Figure 1.3-4. North Carolina PM 2.5 Speciation for 2004

1.4 Major Contributors to PM 2.5 in the North Carolina Nonattainment Areas

When the annual PM 2.5 concentrations in both nonattain ment areas are analyzed by the percentages of their individual component spec ies, a similar distribution of components are found. The OC and SO 4 components each account for approximately one-third of the total PM 2.5 mass; NH 4 makes up approximately te n percent of the total PM 2.5 mass; and the remaining NO 3 , EC, crustal material, and partic le bound water components each c ontribute approximately five percent or less of the total PM 2.5 mass. Individual pl ots of the speciated PM 2.5 data (similar to Figure 1.3-4) from the three PM 2.5 monitoring locations in the nonattainment areas can be found in Appendix C.

The percentages of species contribution fluctuat e throughout the year with the most significant changes to SO 4 and NO 3 . SO 4 is more pronounced in the summertime or warm season months than during the wintertime. NO 3 fluctuates from almost undetectable in the summertime to as much as ten percent cont ribution of the total PM 2.5 mass during the coldest portion of the winter.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 6 The speciated analysis of the PM 2.5 concentrations in the Hickory and Triad PM 2.5 nonattainment areas demonstrates that the OC and SO 4 components are the most impor tant portions of the total PM 2.5 mass throughout the year. OC is predominately attributed to biogenic emissions sources. SO 4 is associated with SO 2 emissions. When evaluated across North Carolina and also throughout both nonattainment areas and surrounding regions, the SO 2 is primarily from the point source sector. For this reason, SO 2 emissions controls from point sources are believed to be the most appropriate strate gy for addressing the current PM 2.5 nonattainment issues for Hickory and the Triad.

Further details on th e nature of the PM 2.5 problem in both PM 2.5 nonattainment areas are discussed in Section 2 and can also be found in the Conceptual Descriptio n 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 genera l requirements for nonatta inment areas. These requirements are listed below and are disc ussed in more deta il 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 measuresThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 7 

### 2.0 SIGNIFICANCE OF PM 2.5 

### PRECURSOR POLLUTANTS As suggested in the Section 1.4, SO 2 emissions are believed to be the most appropriate strategy for addressing the 1997 PM 2.5 NAAQS for the Hickory and Triad nonattainment areas. This finding is based on several factors including:

• An analysis of the percentage contribution of the PM 2.5 component species annually and seasonally within the nonattainment areas

• Attribution of emissions sources to these PM 2.5 component species

• Clean Air Fine Particulate Implementation Rule presumptions on precursor pollutants

2.1 PM 2.5 Component Species Analysis
To fully understand the nature of the PM 2.5 nonattainment issues in the Hickory and Triad nonattainment areas, it is important to analy ze the percentage contri bution of the individual PM 2.5 component species, both from an annual pe rspective and seasonally throughout the year. Unfortunately, the FRM monitoring sites only pr ovide a total mass PM2.5 concentration and do not provide any information concerning the speci ated breakdown of various components. A separate PM 2.5 monitoring network, STN, does allow for the speciation of these components, but the STN PM 2.5 concentration data is not dir ectly comparable to the FRM PM 2.5 concentration data due to slight difference in the monitoring methodology. This creates an issue in using raw STN PM 2.5 data in an attainment demonstration, becau se it is not absolutely equivalent to the FRM PM 2.5 data of which the nonattainment is based and of which attainment will ultimately be evaluated.

To address this issue, Neil Frank with the US EPA developed an approach to use the raw STN PM 2.5 data to appropriately estimate the components of PM 2.5 as measured by the FRM monitors. The approach is termed the “ S ulfate, A djusted N itrate, D erived W ater, I nferred C arbonaceous material balance approac H ” 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 PM 2.5 component species relative to the total FRM PM 2.5 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, resp ectively. The speciated mass contributions displayed are for the 2002 baseline year. Figur es 2.1-1 through 2.1-3 illu strate 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 char ts representing the 2002 annual averaged speciated mass contributions.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 8 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 DayMass (μg m-3) Crustal EC OC H2O NH4 NO3 SO4

Figure 2.1-1. 2002 PM 2.5 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 DayMass (μg m-3) Crustal EC OC H2O NH4 NO3 SO4

Figure 2.1-2. 2002 PM 2.5 Speciated Mass Contribution at Lexington Using SANDWICHThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 9 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 DayMass (μg m-3) Crustal EC OC H2O NH4 NO3 SO4

Figure 2.1-3. 2002 PM 2.5 Speciated Mass Contribution at Mendenhall Using SANDWICH

From each of the three 2002 PM 2.5 speciated mass contribution pl ots, it is clear that SO 4 and OC are the dominant PM 2.5 components throughout the year. SO 4 is most pronounced during the summertime, but remains a reasonably important component of the total PM 2.5 mass in any of the seasons. NH 4 and H 2 O are less dominant than SO 4 and OC but are relatively consistent in each season. EC and crustal material are much less prevalent at any time of the year. Finally, NO 3 contributions are almost undetectable in the summe rtime to as much as ten percent contribution of the total PM 2.5 mass during the wintertime.

2.2 Attribution of Emissions Sources
Precursor pollutants to PM 2.5 can be emitted directly, such as in smoke from a fire, or they can form from chemical reactions of gases such as SO 2 , nitrogen dioxide and so me organic gases. Sources of these precursor pollutants include po wer plants, gasoline and diesel engines, wood combustion, and high-temperature industrial processe s such as smelters and steel mills. Other sources of the PM 2.5 precursor pollutants include mobile sources, area sources, biogenic, fires, windblown dust, and oceans.

The speciated analysis of the PM 2.5 concentrations in the Hickory and Triad PM 2.5 nonattainment areas presented above demonstrates that the OC and SO 4 components are the most important portions of the total PM 2.5 mass throughout the year at all three monitori ng locations. OC is predominately attributed to biogenic volat ile organic compound (VOC) emissions. SO 4 is associated with SO 2 emissions. NH 4 can have a variety of sources including both industrial and natural processes. What little NO 3 is present in the PM 2.5 nonattainment areas throughout the year are attributed to NO x from combustion sources. Of a ll these components and associated emission sources, SO 4 is the only dominant PM 2.5 component species found throughout the yearThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 10 that is attributed to a set of emissions source (SO 2 ) that are controllable through regulatory actions by the North Carolina Division of Air Quality (NCDAQ).

When evaluated throughout both nonattainme nt areas and across North Carolina, SO 2 is primarily from the point source sector. Figures 2.2-1 and 2.2-2 present the SO 2 emissions from the various source sectors in the Hickory and Triad PM 2.5 nonattainment areas, respectively. Both figures are presented on same vertical axis scales to illustrate th e 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 SO 2 emissions from all other source categories. When SO 2 emissions by source category are evaluated across North Caro lina (Figure 2.2-3), the point source emissions are 6 times larger than emissions containe d in either of the nonattainment area SO 2 emissions plots. Again, the magnitude of the point source sector completely masks the SO 2 emissions from all other source sectors.

Figure 2.2-1. Hickory PM 2.5 Nonattainment Area SO 2 Emissions in 2002The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 11 Figure 2.2-2. Triad PM 2.5 Nonattainment Area SO 2 Emissions in 2002

Figure 2.2-3. North Carolina Total SO 2 Emissions in 2002The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 12 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 PM 2.5 Implementation Rule, guides States as they develop state implementation plans in response to annual and/or daily PM 2.5 nonattainment. It esta blishes a hierarchy of precursor pollutants: SO 2 is always considered a precursor, NO x 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 si gnificant and insignificant precursor pollutants established in the PM 2.5 Implementation Rule in this attainment demonstration. Further discussion on the significant or insignificance of the various precu rsor pollutants is discussed in Appendix O.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 13 

### 3.0 ATTAINMENT DEMONSTRAT ION METHODS AND INPUTS The attainment modeling for the Hickory and Triad PM 2.5 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 PM 2.5 and ozone (O 3 ) modeling being done by the Association of Southeastern Integrated Planni ng (ASIP). VISTAS and ASIP are managed by the ten Southeast states (Alabama, Florida, Georgia, Kentucky, Mississippi, North Caro lina, South Carolina, Tennessee, Virginia and West Virginia). Sin ce the VISTAS/ASIP regional modeling utilized annual simulations and includes modeling for the attainment year required for the Hickory and Triad PM 2.5 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 eval uation that begins by se lection of the modeling system. VISTAS decided to use the following modeling system:

• Meteorological Model: The Pennsylvania St ate University/National Center for Atmospheric Research (PSU/NCAR) Meso scale Meteorological Model (MM5) is a nonhydrostatic, prognostic meteorological model r outinely used for urban- and regionalscale photochemical, fine particulate matte r, and regional haze regulatory modeling studies.

• Emissions Model: The Sparse Matrix Oper ator Kernel Emissions (SMOKE) modeling system is an emissions modeling system that generates hourly gridded speciated emission inputs of mobile, non-road mobile, area, poi nt, 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-Atmosphe re” photochemical grid model capable of addressing O 3 , 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 PM 2.5 and poor visibility are observed throughout the region. Once the hist orical year is selected, mete orological inputs are developed using the meteorological model. Emission inventor ies are also developed fo r the historical year and processed through the emissions model. These inputs are used in th e air quality model to predict ozone, PM 2.5 and visibility, with the results compar ed to the historic data. The model performance is evaluated by comparing the modele d predicted data to th e historic air quality data.

Once model performance is deemed adequate, typi cal baseline and future year emissions are processed through the emissions model. For th is demonstration, the baseline year was 2002, which corresponds with the same year as the hi storic 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 PM 2.5 nonattainment areas is April 5, 2010. TheThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 14 attainment date is set prior to the completion of the 2010 calendar year; th erefore the attainment of the NAAQS would have to be met by the e nd of 2009. These emissions are processed through the air quality model with the meteorological inputs . The air quality modeli ng results are used to determine a relative reduction in future PM 2.5 concentrations, which is used in the attainment demonstration.

The complete modeling protocol used by th e NCDAQ for this analysis can be found in Appendix D.1. For additional reference, the VI STAS/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 scient ifically appropriate for the intended application and be freely accessible to all stakeholders. Scie ntifically appropriate means that the models address important physical and chemical phenomen a in sufficient detail, using peer-reviewed methods. Freely accessible means that model form ulations and coding are freely available for review and that the models are available to stak eholders, and their consul tants, for execution and verification at little or no cost.

The following sections outline the criteria for select ing 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 modeli ng attainment de monstration.

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 evalua tions 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 attain ment 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, fineThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 15 particulate matter, visibility and acid deposition within a common platform. The original justification for the Models-3 development em erged from the challenges posed by the CAAA and the USEPA’s desire to develop an a dvanced modeling framework for “holistic” environmental modeling utilizing st ate-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 atmo spheric model is the ability to do oneatmospheric modeling. Since the NCDAQ will be using the same modeling exercise for the ozone and PM 2.5 attainment demonstration state impleme ntation plans (SIPs), as well as the regional haze SIP, having a model that can handle both ozone and particulat e matter is essential. A number of features in CMAQ’s theoretical formulation an d technical implementation make the model well suited for annual PM 2.5 modeling.

CMAQ contains three options for treating seconda ry 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 em issions can be converted to condensable gases that can then form SOA and then evaporat e back into condensable gases depending on atmospheric conditions.

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

• Three-dimensional hourly meteorological fi elds that will be generated by the CMAQ MCIP2.3 processing of the BAMS MM5 output

• Three-dimensional hourly emi ssions 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 demonstra tion, as well as a more detailed description of the CMAQ_SOA (CMAQ version with SOA modifi cation) 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 objectiv e, diagnostic, or pr ognostic 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 accura tely 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:The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 16 • 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 Bo undary Layer heights for AQ modeling

3.2.2.2 Overview of MM5 The non-hydrostatic MM5 model is a three-dime nsional, 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 worldw ide 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 ope rational and research models. In the non-hydrostatic MM5, the sigma levels are defined according to the initial h ydrostatically balanced reference state so that the sigma levels are also time-invariant. Th e gridded meteorological fields produced by MM5 are directly compatible with the input requirements of “one atmo sphere” 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 parameterizati ons 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 formul ation for stable and neutral environments and a modified first-order scheme for unstable regime s. 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 r eal-data cases from mesoscale threedimensional analyses performed at 12-hour interv als 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 analy ze standard surface and radiosonde observations, using the National Meteorological Center's spect ral analysis, as a first guess. The lateral boundary data are introduced using a relaxation tec hnique 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 repo rted in the literature (e.g., Emery et al., 1999;The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 17 Tesche et al., 2000, 2003) and ma ny have involved comparisons with other prognostic models such as the Regional Atmospheric Modeling Sy stem (RAMS) and the Systems Application International Mesoscale Model. The MM5 enjoys a far richer applicati on history in regulatory modeling studies compared with RAMS or other m odels. Furthermore, in evaluations of these models in over 60 recent regional scale air qual ity application studies since 1995, it has generally been found that the MM5 model tends to produc e somewhat better photochemical model inputs than alternative models.

The databases required for setting up, exerci sing, and evaluating the MM5 model for the 2002 season consist of various fi xed and variable inputs.

• Topography : High resolution (e.g., 30 sec to 5 min) topographic information derived from the Geophysical Data Center global data sets 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 resolu tion) following the procedures outlined by Stauffer and Seaman (1990). These 3-hour syno ptic-scale initializat ion data include the horizontal wind components (u and v), temperat ure, and relative humidity at the standard pressure levels, plus sea-level pressure and ground temperature. Here, ground temperature represents surface temperatur e 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 vari able. These temperatures are bi-linearly interpolated to each model domain and, wh ere necessary, filtered to smooth out irregularities.

• Clouds and Precipitation : While the non-hydrostatic MM5 treats cloud formation and precipitation directly through explicit, resolv ed-scale, and parameterized sub-grid scale processes, the model does not require prec ipitation or cloud input. The potential for precipitation and cloud formation enters th rough the thermodynamic and cloud processes formulations in the model. The only precipi tation-related input requ ired is the initial mixing ratio field that is developed from the National Weather Service (NWS) and National Meteorological Ce nter (NMC) datasets.

• Multi-Scale Four Dimensi onal 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 produ ced 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 demonstra tion, 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).The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 18 3.2.3 Selection of Emissions Processing System

3.2.3.1 Criteria The principal criterion for an emissions processi ng system is that it accurately prepares emissions files in a format suitable for the pho tochemical 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 Emissi ons (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 “f irst principles”. This means that, with the exception of mobile and biogenic so urces, its purpose is to provide an efficient, modern tool for converting emissions inventory data into the form atted emission files requ ired by an air quality simulation model. For mobile sources, SMOKE actually simulates emissions rates based on input mobile-source activity data, emission fact ors 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 algor ithms. Indeed, SMOKE is the fastest emissions processing tool currently available to the air quality modeling community. The sparse matrix approach utilized throughout SM OKE permits both rapid a nd flexible processing of emissions data. The processing is rapid because SMOKE utilizes a series of matrix calculations instead of less effici ent algorithms used in previous systems. The processing is flexible because the processing steps of tem poral projection, controls, chemical speciation, temporal allocation, and spatial allocation have been separate d into independent operations wherever possible. The results from these st eps are merged together at a final stage of processing.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 19 SMOKE contains a number of ma jor features that make it an attractive component of the modeling system. The model s upports a variety of input fo rmats from other emissions processing systems and models. It supports bot h gridded and county total land use scheme for biogenic emissions modeling. SMOKE can acco mmodate emissions files from up to 10 countries and any pollutant can be processed by the system.

For additional information about the SM OKE 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 proj ect changes in air quality in res ponse 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 Goal s for Ozone, PM2.5, and Regional Haze (Attainment Modeling Guidance) identifies specific goals to consider wh en selecting one or more episodes for use in modeling to demonstrate the attainment of th e NAAQS. The USEPA recommends that episode selection derive from th ree principal criteria:

• Simulate a variety of me teorological conditions

• Model time periods in which observed con centrations are close to the appropriate baseline design value

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

• Model a sufficient number of days so that th e modeled attainment te st 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 th e most preferable, representati ve modeling year. These steps include the following:

• Representativeness of Meteorological Conditions: The VISTAS meteorological contractor (BAMS) identified important meteor ological characteristics and data sets in the VISTAS region directly relevant to the evaluation of candidate annual modeling episodes. This analysis is discussed in mo re 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 i nputs 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 PM 2.5 concentrations in 2002 we re representative of the five-year baseline period. The CART an alysis is discussed in more detail in Appendix P.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 20 • Data Availability: In parallel with the CART analysis , episode characterization analyses, collaborative investigations by VISTAS st ates (e.g., North Carolina, Georgia, and Florida) intensively studied the availability of PM 2.5 , meteorological, and emissions data and representativeness of a lternative baseline modeling periods from a regulatory standpoint. Additionally, 2002 was the year th at the USEPA was requiring states to provide emissions inventory data for th e Consolidated Emissions Reporting Rule (CERR), it made sense to use 2002 as the m odeling 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, th e episode selection process culminated in the selection of calendar year 2002 (1 January through 31 December) as the most current, representative, and pragmatic c hoice for modeling. All of the USEPA criteria for model year selection were directly consider ed in this process together wi th many other considerations (e.g., timing of new emissions or aerometric data de liveries 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 allo wed the larger outer domains to feed concentration da ta to the inner nested domain. One-way nesting is believed to be appropriate for the generally stagnant condi tions experienced during North Carolina’s poor air quality episodes. Two-way nesting was not co nsidered 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 loca tion of areas of interest, such as ozone and fine particulate matter nonattainment areas. Processi ng time was also a factor in choosing a smaller 12-km grid, modeling domain.

The coarse 36-km horizontal grid domain covers th e continental United States. This domain was used as the outer grid domain for MM5 mode ling with the CMAQ_SOA domain nested within the MM5 domain. Figure 3.4.1-1 shows the MM5 horiz ontal domain as the out er most, blue grid with the CMAQ_SOA 36-km domain nested in the MM5 domain.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 21 Figure 3.4.1-1. The MM5 and CMAQ_SOA 36-km Horizontal Domains

To achieve finer spatial resolution in the VIST AS states, a one-way ne sted 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 te st results are based.

Figure 3.4.1-2. VISTAS 12-km Modeling DomainThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 22 3.4.2 Vertical Modeling Domain The vertical grid used in the MM5 modeli ng primarily defines the CMAQ_SOA vertical structure. The MM5 model employed a terrain fo llowing 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 computationa l cost of the CMAQ simulations. A layer-averaging scheme was used to generate 19 vertical layers for CMAQ_SOA to reduce the computationa l cost of the CMAQ_SOA simulations. The effects of layer aver aging were evaluated in conjunction with the modeling effort and were found to have a rela tively 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 discus sion on the layer-averaging scheme can be found in Section 5 of the Modeling Protocol in Appendix D.1.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 23 Table 3.4.1-1: Vertical Layer De finition 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 pr ovisions of the CAA related to attainment of the NAAQS and the protection of visibility in mandatory Cla ss I Federal areas (certa in national parks and wilderness areas). These revisions established new emission inventory requirements applicable to certain areas that were designated nonattainme nt for certain pollutants. In the case of particulate matter, the emission inventory prov isions are in the ge neral provisions under Section 172(c)(3).The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 24 There are various types of emission inventories. Th e first is the actual base year inventory. This inventory is the base year emi ssions that correspond to the meteorological data used, which for this modeling effort is data from 2002. These emissions are used for ev aluating the air quality model performance.

The second type of inventory is th e typical base year inventory. Th is inventory is similar to the actual base year inventory, except that for sour ces 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 y ear inventory are used to calculate relative reduction factors used in the at tainment demonstration test.

The future year base inventory is the third type of inventory a nd 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 cont rols might be needed in order to attain and maintain the annual PM 2.5 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 prov ided at the facility level. Electric generating utilities and industrial sources are th e major categories for st ationary point sources.

Stationary area sources are those sources whose individual emissions ar e relatively small, but due to the large number of thes e sources, the collective emissions from the source category could be significant (i.e., dry cleaners, service stations, agricultural s ources, fire emissions, etc.). These types of emissions are es timated on a countywide level.

Non-road (or off-road) mobile s ources are equipment that can move but do not use the roadways, i.e., lawn mowers, construction equipment, railro ad locomotives, aircraft, etc. The emissions from these sources, like stationary area s ources, 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 es timated by vehicle type and road type, and are summed to the countywide level.

Biogenic sources are the natural sources like tree s, 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, NO x , PM 2.5 , coarse particulate (PM 10 ), ammonia (NH 3 ) and SO 2 . Table 3.5-1 presents a summary of the act ual and typical 2002 annual emi ssions from the various source sectors for the counties in the Hickory and Triad PM 2.5 nonattainment areas. The full emissionThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 25 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 Cata wba 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 i nventories used for each source classifications are discussed. The detail discussions of the emi ssions 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).The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 26 3.5.1 Stationary Point Sources

Point source emissions are emissions from indivi dual sources having a fixe d location. Generally, these sources must have permits to operate, and their emissions are inventoried on a regular schedule. Large sources having th e potential to emit at least 100 t ons per year (tpy) of a criteria pollutant, 10 tpy of a single hazardous air pollu tant (HAP), or 25 tpy total HAP are inventoried annually. Smaller sources have been inventorie d less frequently. The point source emissions data can be grouped as EGU sources and other industrial point sour ces, also called non-electric generating units (non-EGUs). Appendix F.1 doc uments the point source modeling inventory development in more details

3.5.1.1 Electric Generating Units The actual base year inventory for the EGU s ources 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 SO 2 and NO x that can be used in air quality mode ling. Emissions profiles are used to estimate emissions of other pollutants based on measured emissions of SO 2 and NO x . Emissions from EGU vary daily and seasonally as a function of variabil ity in energy demand and utilization and outage schedules. Since emission from EGUs repr esent a significa nt 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 Atta inment Modeling Guidance. To develop a typical year 2002 emi ssions inventory for EGU sources, each unit’s average CEM heat input for 2000 through 2004 was divided by the 2002 act ual heat input to gene rate 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 we re 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 averag e 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 no rmalizing calculations. For more information about typical 2002 EGU emissions, please refe rence to Section 2.1.4 (EGU Analysis) of Appendix F.1 (Point Source Emissi ons 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 gene rate future year emission inventories for the electric generating sector of the contiguous Unite d States using the Integrated Planning Model (IPM). IPM is a dynamic linear optimization mode l that can be used to examine air pollution control policies for various pollutants throughout the contiguous United St ates 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. Op timization logic in IPM determines the leastcost means of meeting electric generation and capacity requirements while complying with specified constraints including air pollution regulations, transm ission 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 Secti on 3.1.1 (Chronology of the Development of EGUThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 27 Projections) and Section 3.1.2 (V ISTAS/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 Sm okestack Act (CSA) requirements for Duke Power and Progress Energy. The VISTAS States a nd stakeholders also provided changes for the following:

• NO x post-combustion cont rol on existing units

• SO 2 scrubbers on existing units

• SO 2 emission limitations

• Particulate Matter (PM) controls on existing units

• Summer net dependable capacity

• Heat rate for existing units

• SO 2 and NO x control plans based on State ru les or enforcement settlements

For a detailed discussion about how IPM took consideration for fede ral, 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 us ed 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)-b ased 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 st akeholder input on growth assumptions.

3.5.2 Stationary Area Sources Stationary area sources are sources whose individua l 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 i ndicator of collective activity, such as fuel usage, number of households, or population. Stat ionary area source emissions are estimated at the countywide level.

A portion of the area source 2002 base year inve ntory for North Carolina was developed by the NCDAQ and provided to the VI STAS/ASIP contractor. Th e VISTAS/ASIP contractor calculated the remaining portion of the area source inventory. The sources estimated by the contractor include emissions from animal husbandr y, 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 und er CERR for 2002 was used.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 28 The actual base year inventory will serve as the t ypical base year inventor y for all area source categories except for wild land fires. For wild la nd fires, a typical year inventory was used to avoid anomalies in wildfire activ ity in 2002 compared to longer-term averages. Development of a typical year fire inventory provided the capabil ity 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 burne d over a longer term period (thr ee or more years, as available from state records) to 2002. Based on these rati os, the 2002 acreage was then scaled up or down to develop a typica l year inventory.

For categories other than wildland fires, the VIST AS/ASIP contractor generated the future base year emissions inventory used in the attain ment demonstration modeling. Growth factors supplied from the states or the USEPA’s CAIR em ission 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 gr owth 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 s ources 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 cate gories 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 y ear emissions inventories.

For the source categories estimated using the USEPA’s NONROAD model, the model growth assumptions were used to create the 2009 futu re year inventory. The NONROAD model takes into consideration regulations a ffecting emissions from these s ource categories. For the four largest airports in North Carolina, the Federal Aviation Administration’s Terminal Area Forecast was used to project growth in aircraft em issions. For the commercial marine, railroad locomotives and the remaining airport emissions, the VISTAS/ASIP contractor calculated the future growth in emissions using detailed invent ory 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 provide s 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 emi ssions inspection programs), and temperature.

The MOBILE model takes into consideration regulati ons that affect emissions from this source sector. The same MOBILE run is used to repres ent the actual and typical year emissions forThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 29 onroad vehicles using input da ta reflective of 2002. The MOBI LE model is then run for the 2009 inventory using input data re flective of that year. The 2002 vehicle miles traveled (VMT), speeds, vehicle age and vehicle mix data were ob tained from the North Carolina Department of Transportation (NCDOT). For ur ban areas in North Carolina th at 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 us ed in the attainment demonstration modeling, please refer to Appendix F.3.

3.5.5 Biogenic Emission Sources Biogenic emissions were prepared with th e 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 incl ude use of MM5 data, gridded land use data, and improved emissions characterization. The em ission factors that are used in SMOKE-BEIS3 are the same as the emission factors as in UAM-B EIS3. 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 th e USEPA. A separate land classification scheme, based upon satellite (AVHRR, 1 km spatial resolution) and cen sus information aided in defining the forest, agriculture, and urban por tions of each county.

The base year biogenic emissions are used for th e 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 depe ndent on the meteorology. Variation in these emissions could impact the control strategies need ed to demonstrate attainment. Therefore, these emissions are kept constant.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 30 

### 4.0 MODEL PERFORMA NCE EVALUATION There are many aspects of model performance. This section will focus primarily on the methods and techniques recommended by th e USEPA for evaluating the perf ormance 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 bias es and errors that may be passed from the meteorological model directly into the air quality model. The meteorological modeling evaluation is fully documented in Appendi x 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 sk ill in replicating the state variables (e.g. temperature, mixing ratio, relative humidity, wind speed and direction, cloud cover, and precipitation). The meteorological modeling perf ormance 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 th e 12-km modeling domain. Again, large-scale meteorological patterns were accurately predic ted. 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 mode ling domain, the temperature bias was negative for the entire year. The months of April thr ough September had an average bias closer to zero (- 0.1 Kelvin) than the fall and winter months. Ov erall, the diurnal patt ern 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 fair ly 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 ze ro 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 hum idity 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 pos itive 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 pe r second) high bias du ring 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. Th e models always have some level of winds present. This is further aggravated by the fact that observation netw orks have a “starting thresholds” for their wind speed instrumentati on. The instruments need winds in excess ofThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 31 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 pe riod. Moisture biases may imp act 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 l ead to over prediction of PM 2.5 . Conversely the over prediction pr ecipitation amounts in the April to September time frame may lead to under prediction of total PM 2.5 concentrations. Also, the slightly higher modeled wind speeds could lead to additional dispersion of pol lutants and ultimately to an under-prediction of PM 2.5 in the modeling results.

Overall, the NCDAQ believes that the meteorologi cal model performance is adequate for this modeling exercise and should pr oduce credible inputs for the air quality modeling for the attainment demonstration for the Hickory and Triad PM 2.5 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 s upport 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 mo nitoring sites and model output data from the 2002 actual annual air quality modeling. The eval uation primarily focuses on the air quality model’s performance with respect to individual components of PM 2.5 , 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 mode l 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 m onitors, and calculations of futu re 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 ca n 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, a nd stacked bar charts fo r the 12-km VISTAS/ASIP domain, all North Carolina monitoring sites coll ectively, and individually for the monitoring sites within the nonattainment ar ea, please refer to Appendix J.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 32 4.2.1 Modeling Performance Goals, and Criteria
In 2004, VISTAS/ASIP established m odel performance goals and criteria for components of fine particle mass (Table 4.2.1-1) based on previous m odel performance for ozone and fine particles. The Attainment Modeling Guidance for fine particul ate 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 sta tistical 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 P erformance Goals and Criteria for the PM 2.5 Component Species
Fractional Bias Mean Fractional Error Comment

< 15 percent < 35 percent Goal for PM 2.5 model performance based on ozone model performance, considered excellent performance

< 30 percent < 50 percent Goal for PM 2.5 model performance, considered good performance

< 60 percent < 75 percent Criteria for PM 2.5 model performance, considered average performance. Exceeding this level of performance indicates fundamental concerns with the modeling system and trigge rs diagnostic evaluation.

An additional way to evaluate model performance statistics is to visualize performance based on these fractional bias and mean fr actional error goals vi a “soccer plots” and “bugle plots”. The soccer plot is so named because the dotted lines rese mble a soccer goal. The soccer plot is useful as both bias and error are shown on a single plot. As bias and e rror 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 criter ia lines are adjusted based on the average concentration of the observed species. As th e 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 PM 2.5 mass (e.g. SO 4 and OC) and that greater bias and error could be accepted for co mponents with smaller contributions to total PM 2.5 mass (e.g. EC, NO 3 , and soil). The soccer plots and bugle pl ots have been included as suggested model performance evaluation displays in the Attainment Modeling Guidance.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 33 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 performan ce statistics for all of the PM 2.5 component species (SO 4 , NO 3 , NH 4 , OC, and EC) and reconstructed PM 2.5 total mass from the STN monitoring sites (Figures 4.2.2-1 and 4.2.2-2) , as well as the total PM 2.5 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 pe rformance for most species of PM 2.5 and total PM 2.5 . The exception is the prediction of NO 3 values, which most values fa ll outside the criteria goal (Figure 4.2.2-1). There are a few months that fall on the criteria le vel 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 NO 3 is taken into consideration, as presented in the bugle plots (Figures 4.2.2-2), NO 3 performance largely falls within th e criteria and goal model performance lines. One can still note a general tendency for under prediction in NO 3 , and other species in right hand image in Figure 4.2.2-2, which leads to a slight under prediction in total reconstructed PM 2.5 . Monthly total PM 2.5 concentration performance at all th e 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 su ggests a slight negative bias in PM 2.5 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

0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 160.0 180.0 200.0

-180.0 -120.0 -60.0 0.0 60.0 120.0 180.0 Fractional BiasMean Fractional Error Sulfate
Nitrate
Ammon. Organics
EC
PM2.5
Criteria
Goal STN VISTAS Sites CMAQ 12km - 2002 Monthly

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0

-75.0 -25.0 25.0 75.0 Fractional BiasMean Fractional Error Sulfate
Nitrate
Ammon. Organics
EC
PM2.5
Criteria
Goal

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 monitori ng sites. The image on the right is a zoomed view of the soccer plot on the left to better depict the area inside th e criteria/goal lines. Each point represents a monthly value as compared to the mo del 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 34 STN VISTAS Sites CMAQ 12km - 2002 Monthly

-200.0 -150.0 -100.0 -50.0

0.0 50.0 100.0 150.0 200.0

0.0 4.0 8.0 12.0 16.0 20.0 Average Concentration ( μ g/m 3 )Mean Fractional Bias Sulfate
Nitrate Ammon. Organics EC
PM2.5 (+) Criteria (+) Goal (-) Goal (-) Criteria STN VISTAS Sites CMAQ 12km - 2002 Monthly

0.0 50.0 100.0 150.0 200.0

0.0 4.0 8.0 12.0 16.0 20.0 Average Concentration ( μ g/m 3 )Mean Fractional Error Sulfate
Nitrate
Ammon. Organics
EC
PM2.5
Criteria
Goal

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 VI STAS STN monitoring sites. The image on the right is a bugle plot of mean fraction error for particulate ma tter and its component species for all VISTAS STN monitoring sites. Each point rep resents 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

0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 160.0 180.0 200.0

-180.0 -120.0 -60.0 0.0 60.0 120.0 180.0 Fractional BiasMean Fractional Error

PM2.5

Criteria

Goal FRM VISTAS Sites CMAQ 12km - 2002 Monthly

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-75.0 -25.0 25.0 75.0 Fractional BiasMean Fractional Error

PM2.5

Criteria

Goal

Figure 4.2.2-3. VISTAS FRM Soccer Plots Soccer plots depicting both the mean fractional err or and fractional bias for component concentration for all the VISTAS FR M Monitoring sites. The image on the right is a zoomed view of the soccer plot on the left to better depict the ar ea inside the criteria/goal lines. Each point represents a monthly value as compared to the mo del 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 35 FRM VISTAS Sites CMAQ 12km - 2002 Monthly

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(+) Criteria
(+) Goal
(-) Goal
(-) Criteria FRM VISTAS Sites CMAQ 12km - 2002 Monthly

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PM2.5

Criteria

Goal

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 partic ulate matter and its component species for all the VISTAS FRM Monitoring sites. Each point rep resents 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 m odel to have some difficulty in predicting NO 3 , as the monthly average values tend to fall outside the crite ria goals for performance in the soccer plots. Part of this under prediction lies in the fact that NO 3 are generally found in low concentration across the southeast, and the model generally has difficulties representing any compound with low atmospheric concentrations. The bugl e plots are more encouraging with NO 3 performance, as these plot take into cons ideration the concentration of the component when evaluating performance. The bugle plots s how all components and total PM 2.5 falling within criteria level, or better, of model performance goa ls. The weaker performance of NO 3 accounts for the slight negative bias in the both the total reconstructed PM 2.5 mass from STN sites as well as FRM total PM 2.5 data.

4.2.3 Nonattainment Area Model Performance

The statistical metrics were calculated for th e Hickory (Catawba County) and Hattie Avenue (Forsyth County) STN monitors to demonstrat e model performance for the components of PM 2.5 in and near the PM 2.5 nonattainment areas. Model performance statistics for the STN sites were calculated on a component and total PM 2.5 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 Mend enhall) to demonstrat e the model’s ability to replicate total PM 2.5 mass at these sites. Summaries and statis tical tables for the STN monitoring sites and FRM monitoring sites can be found in Appendix J.

As a summary of model performance at the nonatta inment area level, the soccer and bugle plots for the Hickory STN (Figure 4.2.3-1 and 4.2.3-2) and FRM monitor (F igure 4.2.3-3 and 4.2.4-4) follow. Plots have been developed for the average monthly concentrations of PM 2.5 and its component species at the STN sites, and for total PM 2.5 from FRM monitors for all North Carolina STN sites collectively and othe r the monitoring sites within the PM 2.5 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 performa nce at the Hickory STN site is similar to overall 12-km VISTAS domain and North Caro lina statewide model performance. Nitrate generally falls outside of suggested criteria m odel 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 PM 2.5 model performance was within criteria level, if not within the goal level thresholds.

STN Hickory CMAQ 12km - 2002 Monthly

0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 160.0 180.0 200.0

-180.0 -120.0 -60.0 0.0 60.0 120.0 180.0 Fractional BiasMean Fractional Error Sulfate
Nitrate
Ammon. Organics
EC
PM2.5
Criteria
Goal STN Hickory CMAQ 12km - 2002 Monthly

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-75.0 -25.0 25.0 75.0 Fractional BiasMean Fractional Error Sulfate
Nitrate
Ammon. Organics
EC
PM2.5
Criteria
Goal

Figure 4.2.3-1. Hickor y STN Soccer Plots The image on the left is the soccer plot depicting both the mean frac tional error and fractional bias for component concentration for th e 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 mo nthly 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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0.0 50.0 100.0 150.0 200.0

0.0 4.0 8.0 12.0 16.0 20.0 Average Concentration ( μ g/m 3 )Mean Fractional Bias Sulfate
Nitrate Ammon. Organics EC
PM2.5 (+) Criteria (+) Goal (-) Goal (-) Criteria STN Hickory CMAQ 12km - 2002 Monthly

0.0 50.0 100.0 150.0 200.0

0.0 4.0 8.0 12.0 16.0 20.0 Average Concentration ( μ g/m 3 )Mean Fractional Error Sulfate
Nitrate
Ammon. Organics
EC
PM2.5
Criteria
Goal

Figure 4.2.3-2. Hickor y 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 (3 7-035-0004) STN monitoring site. The image on the right is the bugle plot of mea n fraction error for particulate ma tter and its component species for the Hickory STN site. Each point represents a mont hly 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 37 FRM Hickory CMAQ 12km - 2002 Monthly

0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 160.0 180.0 200.0

-180.0 -120.0 -60.0 0.0 60.0 120.0 180.0 Fractional BiasMean Fractional Error

PM2.5

Criteria

Goal FRM Hickory CMAQ 12km - 2002 Monthly

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-75.0 -25.0 25.0 75.0 Fractional BiasMean Fractional Error

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Criteria

Goal

Figure 4.2.3-3. Hickory FRM Soccer Plots The image on the left is the soccer plot depicting bo th 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) an d modeling performanc e goals (green box).

FRM Hickory CMAQ 12km - 2002 Monthly

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(+) Criteria
(+) Goal
(-) Goal
(-) Criteria FRM Hickory CMAQ 12km - 2002 Monthly

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PM2.5

Criteria

Goal

Figure 4.2.3-4. Hickor y FRM Bugle Plots Bugle plot depicting the mean fractional bias for th e light extinction due to particulate matter and its component species for the Hickory FR M 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 Hickor y FRM monitoring site. Each point represents a monthly mean fraction bias value as compared to the mode l performance criteria (red lines) and modeling performance goals (green lines).

4.2.4 Air Quality Model Performance Summary Overall, the model performance for North Ca rolina through the 2002 baseline modeling year is reasonable good. For the most part, mean normali zed bias and mean normalized gross error are within the recommended limits for good model perf ormance for most of component species as well as total PM 2.5 mass. Overall performance was good fo r sulfate and organic carbon, which are the largest constituents of PM 2.5 for North Carolina. Nitrate pe rformance was less than ideal, especially during the summer months. This is likely due to the generally low atmospheric concentrations seen in North Ca rolina. When the pe rformance is weighted by the concentration, as in the bugle plots, the pe rformance metrics indicate better model performance. The model also does a good job capturing PM 2.5 component and total concentrations through variousThe 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, Appendi x J). Overall, the NCDAQ believes that the model performance is well within the limits of acceptable performanc e established in the Attainment Modeling Guidance.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 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 s ections below. Although all the control listed below may not directly reduce PM 2.5 concentrations in North Carolina, the modeling assessment in this submittal was based on one atmosphe re modeling completed for ozone and fine particulate matter attainment demons trations and regional haze plans.

5.1 Federal Control Measures

5.1.1 Tier 2 Vehicle Standards Federal Tier 2 vehicle standards will require al l passenger vehicles in a manufacturer’s fleet, including light-duty trucks and Sport Utility Vehi cles (SUVs), to meet an average standard of 0.07 grams of NO x per mile. Implementation began in 2004, with full compliance required 2007. The Tier 2 standards will al so cover passenger vehicles ove r 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 standard s will be phased in beginning in 2008, with full compliance required by 2009. The new standards re quire vehicles to be 77% to 95% cleaner than those on the road today. The Tier 2 rule al so reduced the sulfur c ontent 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 cont ent of about 300 ppm. Sulfur occurs naturally in gasoline, and interferes with the operation of catalytic converters on vehicl es, which results in higher NO x emissions. Lower-sulfur gasoline is necessary to achieve the Tier 2 vehi cle emission standards.

5.1.2 Heavy-Duty Gasoline and Diesel Highway Vehicles Standards

New USEPA standards designed to reduce NO x and VOC emissions from heavy-duty gasoline and diesel highway vehicles bega n to take effect in 2004. The se cond phase of the standards and testing procedures, which began in 2007, w ill reduce particulate matter from heavy-duty highway engines, and will also reduce highway di esel 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 NO x emissions for these new engines using low sulfur diesel, compared to existing engines using higher-cont ent sulfur diesel.

5.1.3 Large Non-road Diesel Engines Rule In May 2004, the USEPA promulgated new rules for la rge non-road diesel engines, such as those used in construction, agricultur al, and industrial equipment, to be phased in between 2008 and 2014. The non-road diesel rules al so reduce the allowable sulfur in non-road diesel fuel by over 99%. Non-road diesel fuel cu rrently averages about 3,400 ppm su lfur. The rule limits non-road diesel sulfur content to 500 ppm by 2006 and 15 ppm by 2010. Th e combined engine and fuel rules would reduce NO x 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 North Carolina Attainment Demonstration August 21, 2009 40 5.1.4 Non-road Spark-Ignition Engines and Recreational Engines Standard
The new standard, effective in July 2003, regulates NO x , hydrocarbons (HC) and carbon monoxide (CO) for groups of previously unregul ated non-road engines. The new standard applies to all new engines sold in the United Stat es and imported after thes e standards begins and applies to large spark-igniti on engines (forklifts and airp ort ground service equipment), recreational vehicles (off-highway motorcycles and all-terrain-veh icles), and recreational marine diesel engines. The regulation varies ba sed upon the type of engine or vehicle.

The large spark-ignition engines co ntribute to ozone formation and ambient CO and PM levels in urban areas. Tier 1 of this standard was impl emented in 2004 and Tier 2 started in 2007. Like the large spark-ignition, recreationa l 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 pe rcent of model year 2006 engines had to meet the standard, and for model year 2007 and later, all of the engines ha ve to meet the standard. Recreational marine diesel engines over 37 kilowatts are used in yachts , cruisers, and other type s of pleasure craft. Recreational marine engines contribu te to ozone formation and PM levels, especially in marinas. Depending on the size of the engine, th e 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 NO x , and 56% reduction in CO emissions are expected by 2020. These controls will help redu ce ambient concentrations of ozone, CO, and fine PM.

5.1.5 NO x SIP Call in Surrounding States
In October 1998, the USEPA made a fi nding of significant contribution of NO x emissions from certain states and published a rule that set ozone season NO x budgets for the purpose of reducing regional transport of ozone (63 FR 57356) . This rule, referred to as the NO x SIP Call, required ozone season controls to be put on utility and in dustrial boilers, as well as internal combustion engines, in 22 states in th e Eastern United States. A NO x emissions budget was set for each state and the states were required to develop rules th at would assure that each state met its budget. A NO x trading program was established, allowing sources to buy credits to meet their NO x budget as opposed to actually installing controls. The emission budgets were to be met by the beginning of 2004. Even with the trading prog ram, the amount of ozone season NO x 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 (C lean Air Interstate Rule); Revisions to Acid Rain Program; Revisions to the NO x SIP Call”, referred to as CAIR. This rule established the requirement for States to adopt rules limiting the emissions of NO x and sulfur dioxide (SO 2 ) and a model rule for the states to use in developing their rules. Th e purpose of the CAIR is to reduce interstate transport of precursors of fine particulate and ozone.

The CAIR applies to (1) any sta tionary, 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, aThe 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 th e 12-month period starting on the date that the unit first produces electricit y and continues to qualify as a cogeneration unit, a cogeneration unit serving at any time a generato r 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 NO x and SO 2 in two phases, with the Phase I caps for NO x and SO 2 starting in 2009 and 2010, respectively. Ph ase 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 fu lly implemented, the CAIR will reduce SO 2 emissions in the eastern United States by over 70 percent and NO x 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 incl ude the Clean Air Bill, the NO x SIP Call Rule, the CSA, the Open Burning Rule, and the CAIR. All of these re gulations were modeled in the attainment demonstration. These regulations are summar ized below and the ac tual regulations and legislation can be viewed in Appendix M.

5.2.1 Clean Air Bill The 1999 Clean Air Bill expanded the vehicle emissions inspecti on and maintenance program in North Carolina from 9 counties to 48 counties be tween 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 MapThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 42 The effective dates for the count ies in the Hickory and Triad PM 2.5 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 NO x SIP Call Rule In response to the USEPA’s NO x SIP call, North Carolina adopted rules to control the emissions of NO x from large stationary combustion sources. These rules cover (1) fossil fuel-fired stationary boilers, combustion turbines, and comb ined cycle systems serv ing a generator with a nameplate capacity greater than 25 MW and selli ng 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 Britis h 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 horsepow er for dual fuel engines). As part of the NO x SIP call, the USEPA rules established a NO x budget for sources in North Carolina and other states.

Besides amending existing NO x rules and adopting new NO x rules specifically to address the USEPA NO x SIP call, the North Carolina rules also re quire new sources to control emissions of NO x . The objective of this requiremen t is (1) to aid in meeting the NO x budget for North Carolina for minor sources and (2) to aid in a ttaining and maintaining the ambient air quality standard for ozone in North Carolina.

North Carolina’s NO x SIP Call rule was predicted to reduce summertime NO x emissions from power plants and other industries by 68% by 2006. In October 2000, the North Carolina Environmental Management Com mission (EMC) adopted rules re quiring the reductions. In 2009, the North Carolina NO x 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 NO x emissions by 77% by 2009. These power plants must also reduce annual sulfur di oxide emissions by 49% by 2009 and by 73% by 2013. It is significant to note th at this law sets a cap of NO x and SO 2 emissions for the State, which the public utilities cannot meet by purchasing emissions credits. The CSA reduces NO x emissions beyond the requirements of the NO x SIP Call Rule. One of the first state laws of its kind in the nation, this legislation provides a model for othe r states in controlling multiple air pollutants from older coal-fired power plants.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 43 5.2.4 Open Burning Bans

The rule adopted by the EMC in June 2004 is ai med at reducing emission s 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 lo cal air programs forecast Code Orange, Red or worse ozone conditions for a particular metro ar ea. 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 NO x : 62,183 tons for 2009-2014 and 51,819 tons for 2015 and each year thereafter;

• Ozone season NO x : 28,392 tons for 2009-2014 and 23,660 tons for 2015 and each year thereafter;

• Annual SO 2 : 137,342 tons for 2010-2014 and 96,139 tons for 2015 and each year thereafter.

The State’s NO x allocations have been distributed am ong the covered facilities. The USEPA will determine the SO 2 allocations, which are based on the acid rain program. For the most part the proposed rules incorporate the USEPA’s model rule. The USEP A’s model rule for definitions; permitting; monitoring, reporting, an d 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 revi ew 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 CA IR rules will remain in place until the USEPA promulgates changes to the program.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 44 

### 6.0 ATTAINMENT DEMONSTRATION An attainment demonstration consists of (a) anal yses 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 attainme nt demonstration components may be determined by relying on results obtained with air quality models.

Section 3.0 of the Attainment Modeling Guid ance 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 PM 2.5 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 a ttainment of the annual PM 2.5 NAAQS.

This section does not present a modeled attainment test or a subsequent screening test with respect to the daily PM 2.5 NAAQS, because all portions of North Carolina were initially designated as attaining the daily PM 2.5 standard. Continued a ttainment of the daily PM 2.5 NAAQS is projected and assumed due to the widespread reductions in SO 2 and NO x emissions already discussed in Section 5 a nd the modeling projections discusse d later in this Section that demonstrate significant decreases in PM 2.5 concentrations into the future.

6.1 Attainment Test Introduction
The purpose of a modeling assessment is to dete rmine if control strategies currently being implemented (“on the books”) and proposed control strategies will lead to attainment of the NAAQS for PM 2.5 by the attainment year of 2009. The mode ling is applied in a relative sense, similar to the 8-hour ozone attainment test. However, the PM 2.5 attainment test is more complicated and reflects the fact that PM 2.5 has many components. In the test, ambient PM 2.5 is divided into major components, w ith a separate relative response factor (RRF) and future design value (DVF) calculated for each of the PM 2.5 components. Since the atta inment test is calculated on a per species basis, the attainment test for PM 2.5 is referred to as the Speciated Modeled Attainment Test (SMAT). In its entiret y, SMAT consists of four basic steps.

First, the observed quarterly mean PM 2.5 and quarterly mean composition for each monitor is calculated. This is achieved by multiplying the monitored quarterly mean concentration of PM 2.5 from FRM monitors by the monito red fractional composition of PM 2.5 species for each quarter (e.g., (20% sulfate) x (15.0 μg/m 3 PM 2.5 mass) = 3.0 μg/m 3 sulfate mass).

The monitored quarterly mean concentration of PM 2.5 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 ye ar. The fractional composition of PM 2.5 species is derived from STN monitoring site data th at has been processed by the “sul fate, adjusted nitrate, derived water, inferred carbonaceous material balance approach”, or SANDWICH method, so STN and FRM masses are equivalent. The mean com position derived from the SANDWICH method includes the percent of PM 2.5 that can be attributed to SO 4 , NO 3 , OC, EC, other primary inorganic particulates (o r crustal materials), NH 4 , and particle bound water (PBW).The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 45 The second step is to use model results to deri ve 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 compone nt specific RRFs are applied to the observed air quality concentrations to project quarterly species esti mates. For each quarter, the current quarterly mean component concentration (step 1) are mu ltiplied 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 PM 2.5 value. These quarterly mean values are then averaged to produce a future year annual average PM 2.5 estimate, or future design value (DVF), for each FRM monito ring site. This final value is then compared to the NAAQS (15.0 μg/m 3 ) 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 PM 2.5 components to get annual mean PM 2.5 values. Table 6.2-1 displays the quarter ly mean concentration and annual mean future design values (DVFs) estimates for 2009 for the FRM sites in the North Carolina PM 2.5 nonattainment areas.

Table 6.2-1. Quarterly Mean and Annual Mean PM 2.5 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 th e SMAT process and are then compared to the NAAQS (15.0 μ g/m 3 ) to determine if attainment goals will be reached. Since the values at the FRM site in both the nonattain ment areas are less than 15.0 μ g/m 3 , all areas have passed the attainment test portion of th e 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 additiona l analyses of air quality, emissions and meteorological data, and consider modeling outputs ot her 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 (W OE) to show that attainment is likely despite modeled results, which may be inconclusive.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 46 The Attainment Modeling Guidance defines the gu idelines for supplemental analysis/WOE for the annual PM 2.5 standard as follows:

- Site with a DVF less than 14.5 μ g/m 3 should submit basic supplemental analysis to confirm the outcome of the model attainment test.

- Sites with a DVF between 14.5 and 15.5 μ g/m 3 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 μ g/m 3 should consider additional control measure to ensure attainment, as more qual itative analysis is unlikely to attainment.

All North Carolina PM 2.5 nonattainment areas have DVFs lower than 14.5 μ g/m 3 , making the following section an examination of supplemen tal 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 supplementa l analysis. One of the metrics that can be considered as part of this type of additional analysis is the calc ulation of the percent change in number of grid cells grea ter than or equal to 15 μ g/m 3 within the nonattainment area.

For the Hickory and Triad nonattainment areas, th e cell counts of modeling data were tallied from both the 2002 baseline and the 2009 attainme nt year modeling run for a subset of the highest days from the base year. This wa s done in order to quantify the reduction of PM 2.5 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 PM 2.5 concentration greater than 30 μ g/m 3 at any of the monitoring sites in either nonatta inment 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 PM 2.5 concentrations from the monitors in th e nonattainment areas can be found in either Appendix J or Appendix K.

Data was extracted for only the grid cells th at contained portions of either of the PM 2.5 nonattainment areas. Figure 6.3.1-1 highlights th e 50 cells that encompass the North Carolina PM 2.5 nonattainment areas.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 47 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 μ g/m 3 intervals to help illuminate the change in severity on the da ys in North Carolina with the highest PM 2.5 concentrations. Figure 6.3.1-2 pr esents the cell count results bot h graphically and in tabular form. The graph clearly shows a striking increase in the number of days below 15 μ g/m 3 . By 2009, 41.57% of cells fall in the 0 –15 μ g/m 3 range, a substantial increase from the 17.21% in 2002. Raw cell counts show a total of 341 cells shifted to the 0 – 15 μ g/m 3 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 μ g/m 3 bin (269 cell decrease) and the 30 - 45 μ g/m 3 bin (75 cell decrease). The numb er 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 concen tration 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 metr ic shows a substantial increase in the number of cells below 15 μ g/m 3 , and an increase in cells below 30 μ g/m 3

.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 48 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 YearPercentage of Nonattainment Area

45 - 60
30 - 45
15 - 30
0 - 15

Figure 6.3.1-2. Percentage of Cell in PM 2.5 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 Concentr ation 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 th eir meteorological and air qual ity 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 PM 2.5 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. Th e DVF was calculated us ing the CAIR SMAT tool, so methodologies between th e CAIR DVF and the va lues presented in Section 6.4 are the same. These modeling results are listed in Table 6.3.2-1 below.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 49 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 PM 2.5 standard by 2010. Although this is one year later than the attainment year for these areas, the USEPA’s 2010 CAIR DVFs are 1 μ g/m 3 higher than what the NCDAQ is showing in the attainment demons tration, but stil l support that both the North Carolina nonattainment areas will attain the annual PM 2.5 standard by the attainment year of 2009.

6.3.3 Air Quality Trends and Additional Reductions in Emissions

Since the annual PM 2.5 designation in 2002, annual average concentrations of PM 2.5 have decreased. PM 2.5 concentrations hovered near the sta ndard at the two nona ttaining monitors through the middle portion of the decade, while th e Mendenhall monitor has maintained values lower than the NAAQS since 2001. In 2007, the PM 2.5 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 graphi cal representation of the data.

Table 6.3.3-1. Annual Average PM 2.5 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 4 th quarter of 2006. The NCDAQ has performed an extensiv e data imputation study to estimate a 4 th 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.3The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 50 Figure 6.3.3-1. Annual PM 2.5 Average Concentrations for the FRM Monitors in the Hickory and Triad Nonattainment Areas

With the improvement in annual average PM 2.5 values, there has also been an improvement in PM 2.5 design values. When one takes in to account the period of record, PM 2.5 design values have improved significantly over the la st 10 years. Like with the annual averages, the three-year design values also began to hover near the le vel of the standard fo r both the Hickory and Lexington monitors during the middle portion of th e decade. With the most recent design value period, 2006-2008, the PM 2.5 design values have achieved atta inment of the NAAQS at all three monitoring sites in the two nonatta inment areas (S ee Table 6.3.3-2).

Table 6.3.3-2. Three Year Design Values for the FRM Monitors in the Hickory and Triad PM 2.5 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 North Carolina Attainment Demonstration August 21, 2009 51 The very recent attainment of the annual PM 2.5 NAAQS at all of the monitoring sites can be directly attributed to th e dramatic reduction of SO 2 emissions throughout North Carolina due to coal-fired power plants compliance with the CSA Phase 1 SO 2 emissions cap. From a peak in 2005, the SO 2 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 SO 2 emissions within and surrounding both nonattainment areas would ha ve the biggest impact on improving PM 2.5 concentrations and associated design values has proven accurate.

Figure 6.3.3-2. Annual SO 2 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 PM 2.5 monitor nearby. To guard against the possibil ity that air quality le vels could exceed the standard in areas with limited monitoring, Se ction 3.4 of the Attainment Modeling Guidance suggests that additional review is n ecessary, particularly in nonattainment areas where the PM 2.5 monitoring network just meets or minimally exceed s the size of the network required. This review is intended to ensure that a co ntrol strategy leads to reductions in PM 2.5 and its constituent pollutants at other locations that could have ba seline (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 combinati on of model output and ambient data to identify areas that might exceed the NAAQS if monitors were located there.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 52 The NCDAQ, along with Local and Tribal Progr ams, currently operates a network of 34 PM 2.5 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 concentrat ion, 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 PM 2.5 formation and transport, and ob tain a better unde rstanding of PM 2.5 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 mon itoring network more than adequately captures the full extent of the PM 2.5 air quality concerns in North Ca rolina. With an average of one monitor per 3711 km 2 , this is one of the densest statewide PM 2.5 monitoring networks in the southeast. A map of each PM 2.5 monitor and its position relativ e to the NCDAQ/ASIP 12-km modeling grid is provided in Figure 6.4-1. As ca n been seen by the figure, the spatial coverage of the monitors, and their resulting “nearby” 3x3 arrays, covers the majori ty of the urban areas where PM 2.5 tends to be higher.

Figure 6.4-1. PM 2.5 Monitors and Nonattainment Areas with Respect to the VISTAS 12km Grid Domain

The adequacy of the NCDAQ PM 2.5 monitoring network is furthe r demonstrated when plotted against a projected spatial field of annual PM 2.5 design values. Figure 6.4-2 presents the 2009 future year PM 2.5 design value modeling output from th is attainment demonstration and the location of each PM 2.5 monitor in and around North Carolina. This 2009 PM 2.5 design valueThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 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, PM 2.5 design values have numerous representative PM 2.5 monitors. There are not any identified PM 2.5 hotspots that would require any additional monitoring considerations in North Carolina.

Figure 6.4-2. PM 2.5 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 file s 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 North Carolina Attainment Demonstration August 21, 2009 54 

### 7.0 CLEAN AIR ACT SECT ION 172(c) REQUIREMENTS Section 172(c) of the CAA, as amended, contai ns the general require ments 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 pr ovide 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 requi res SIPs to provide for the implementation of all RACM to demonstrate attainment as expeditiously as pr acticable. A subset of RACM is reasonably available control technol ogy (RACT), which relates specifically to stationary point sources.

In April 2007, the USEPA promulgated the PM 2.5 Implementation Rule. In this rule the UESPA established what would be requi red for RACM and RACT for PM 2.5 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 implem ent the potential measures or other relevant factors, then the state could conclude that there are no furt her RACM for the nonattainment area that would advance th e attainment date by one year or more.

The predicted design values for the Hickor y and Triad nonattainment areas are 13.1 μg/m 3 and 13.4 μg/m 3 , respectively, well below the annual PM 2.5 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 SO 2 emissions from coal-fired power plants, with implementation beginning as ear ly 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 qual ity action days was prohibited. The prohibition of open burning will reduce fine particulate matter on days that are forecasted to have elevated PM 2.5 concentrations. Copies of these me asures are included in Appendix M.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 55 Additional RACM measures could not be implem ented during 2008. It would take at least two years to complete rule making and another eight een 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 PM 2.5 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 re quirement. The USEPA will view the attainment demonstration as demonstrating that the area is making reasonable fu rther 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 nonattai nment area. Such inventory is due two years after the effective date of the PM 2.5 nonattainment desi gnations, 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. Th e final 2002 emission inventories used in the attainment demonstration went through the public hearing pr ocess with the full atta inment 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 recen tly promulgated Air Emissions Reporting Requirements (AERR) submittals. As su ch, 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 a nd AERR submittals will include point sources for all but those counties with local programs, and statewide area, non-ro ad 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 amen dments 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 require ment. Further, on March 16, 2007, the NCDAQ submitted amendments to 15A NCAC 2D .0530 Pr evention of Significant Deterioration (PSD) permitting rules to the USEPA. The NCDAQ be lieves 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 s ubject to PSD and NNSR programs. Finally, the NCDAQ adopted an Em issions Banking Rule, 15A NCAC 2D .2300 toThe 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 be yond what is required. The NCDAQ believes it has met the permit program requirements for a PM 2.5 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 compli ance 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 c ontains the rules and compliance schedules.

7.7 Compliance with Section 110(a)(2)
Section 172(c)(7) requires nonattai nment SIPs to meet the appli cable provisions of Section 110(a)(2). On October 2, 2007, the USEPA provid ed guidance on SIP elements required under Section 110(a)(1) and (2) fo r the 8-hour ozone and PM 2.5 NAAQSs. Regarding the 1997 PM 2.5 NAAQSs, all SIP elements are adequately covered.

7.8 Equivalent Techniques
The NCDAQ believes that the procedures fo r modeling, emissions inventory and planning follow the USEPA guidance and is not requestin g approval for equivalent techniques, as envisioned under Section 172(c)(8).

7.9 Contingency Measures
Section 172(c)(9) requires that th e nonattainment SIP contain speci fic measures that would take effect upon a State’s failure to attain the PM 2.5 standard in a given area. These contingency measures must be fully adopted rules or contro l measures that are ready to be implemented quickly upon failure to meet the st andard by the attainment date.

In the PM 2.5 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 PM 2.5 NAAQS within five years of designation, RFP is not required. The USEP A’s guidance to the NCDAQ was to have contingency measures that amounted to one-seven th of the emission reductions that occurred between the base year 2002 and the attainment year 2009, or appr oximately one year’s worth of emission reductions. Another suggestion wa s to do sensitivity modeling to determine approximately the level of emission reductions needed to model 15.0 μ g/m 3 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 PM 2.5 NAAQS of 15.0 μ g/m 3 , evident by the predicted future design values being greater than 1.5 μ g/m 3 below the standard. Therefore, the NC DAQ thought it was unreasonable to require contingency measures of one-seventh of the SO 2 emission reduction modeled when the State had already reduced a sign ificant 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 be lieve it was a wise use of State resources to perform further modeling to determine the approximate level of em issions needed to just attain the standard when both nonattainment areas have already attained the annual PM 2.5 NAAQS.

Therefore, the NCDAQ has documented the expect ed 2009 utility emissions, based on the latest CSA compliance plans, which go beyond what was m odeled in the attainment demonstration, as well as the estimated emission reductions e xpected 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 al ready attained the standard, the NCDAQ believes it has met the spirit of this requirement.

Since the most significant man-ma de emissions contributor to PM 2.5 formation in North Carolina is the precursor pollutant SO 2 , the NCDAQ has elected to have only SO 2 contingency measures. The USEPA has stated in the Implementation Rule that the reductions from SO 2 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 CS A. As stated earlier, this legislation will require SO 2 emission reductions from coal-fired powe r plants. For several coal-fired electric generating units subject to the CSA, the SO 2 controls came on-line either during 2009 or 2010. Full implementation of these units was not modele d in the attainment de monstration, 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 late st compliance plan for CSA was the 2006 plan. The utilities companies now have a better unders tanding 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 200 9 emissions are further emission reductions that are expected to occur that were not modeled as part of the attain ment demonstration.

The 2002 baseline emissions for the two nonattain ment areas’ regions of influence were 215,080 and 401,290 tons of SO 2 per year for the Hickory and Tr iad areas, respectively. The NCDAQ has determined that SO 2 emissions will be reduced beyond wh at 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 pe rcent reduction from the 2002 baseline SO 2 emissions in the Hickory and Triad areas, respectively. The anal ysis 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.The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 58 

### 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 th e area from attaining and/or maintaining the annual PM 2.5 standard. This means that the level of emissions estimated by the NCDOT or the metropolitan planning organizations for the Tran sportation 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 partne rs 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 MV EBs to all of the trans portation partners. In the letter, NCDAQ expressed its preference for setting county level budgets and some of the reasons why NCDAQ believed county level budg ets were appropriate. Additionally, the NCDAQ consulted the partners for the data used in the developm ent of the MVEBs, as well as the data used in the attainment demonstra tion modeling. These correspondences and the responses received from the transportati on partners can be found in Appendix B.

8.2 Pollutants to be Considered
40 CFR 93.119(f)(7) through (10) id entifies the pollutants for PM 2.5 for which regional emissions analysis needs to be performed for transportatio n conformity purposes. Only primary, or direct, PM 2.5 tailpipe emissions must be considered for transportation conformity regional emissions analysis. The precursor pollutants NO x , VOC, SO 2 and ammonia, as well as reentrained road dust only need to be considered if the NCDAQ a nd/or the USEPA has deemed the pollutant as a significant contributo r to the overall PM 2.5 nonattainment problem.

The PM 2.5 precursor NO x is presumed to be a significant contributor to the PM 2.5 nonattainment problem by the USEPA. The NCDAQ has determined that NO x is a relatively minor contributor to the PM 2.5 concentrations in North Carolina. Howe ver, the NCDAQ is not asserting that NO x is an insignificant precursor for the 1997 PM 2.5 standard. Therefore, the NCDAQ will establish county level MVEBs for NO x for all three PM 2.5 nonattainment counties.

For the purpose of this attainment demonstr ation, VOC and ammonia are presumed to be insignificant contributors to the PM 2.5 nonattainment problem by the USEPA. The NCDAQ agrees with the USEPA that both VOC and ammo nia are insignificant contributors to the PM 2.5 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 contribut or to the overall PM 2.5 nonattainment problem. This is di scussed further in Appendix F.3.

The PM 2.5 precursor SO 2 could not be deemed insignificant to the overall PM 2.5 nonattainment problem since sulfate is such a large fraction of the PM 2.5 composition. However, the NCDAQ has determined that SO 2 emitted by the mobile source sector is insignificant. The USEPA in its Federal Register notice for PM 2.5 does not address the mobile sect or in its listing of significantThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 59 sources of SO 2 emissions. North Carolina agrees with the following statements addressing SO 2 from on-road mobile emissions as published in the May 6, 2005 Federa l Register, 70 FR 24283:

While speciated air quality data show that sulf ate is a relatively significant component (e.g., ranging from nine to 40 percent) of PM 2.5 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 em issions. Emissions inventory data for 1999 for the 372 potential PM 2.5 nonattainment counties for PM 2.5 (based on 1999–2001 air quality data) show that on-road s ources were responsible for only two percent of total SOx emissions.

Furthermore, EPA has already adopted tw o regulations that will greatly reduce emissions of SOx from on-road sources by the ti me 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 signif icant component to the PM 2.5 nonattainment problem in North Carolina, the majority of the SO 2 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 a bout the significance of mobile source SO 2 emissions can be found in Appendix F.3. For the reasons discussed, the NCDAQ has determined that mobile source SO 2 emissions are insignificant to the PM 2.5 nonattainment problem.

To summarize so far, the NCDAQ has determined that the precursor po llutants VOC, ammonia and mobile source SO 2 , as well as reentrained road dust ar e insignificant cont ributors to the overall PM 2.5 nonattainment problem in North Caro lina. 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 po llutant emissions for these areas and does not relieve them of the other transp ortation conformity requirements. The transportation partners will need to note the insignifi cance finding for these pollutants (if found adequate and approved by the USEPA) in future conformity determinations.

The only mobile source pollutant left to be addr essed for transportation conformity purposes is direct PM 2.5 emissions.

8.3 Highway Mobile Source Direct PM2.5 Emissions
40 CFR 93.109(k) in the Transpor tation Conformity Rule Amendm ents for the new 8-hour ozone and fine particulate matter NAAQSs addresses ar eas with insignificant motor vehicle emissions as follows, Notwithstanding the other paragraphs in this se ction, 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 SIPThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 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 emi ssions in the context of the tota l 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 PM 2.5 emissions from mobile sources do not contribute significantly to the PM 2.5 nonattainment problem. However, the USEPA has indicated they will not approve a SIP that does not set MVEBs for primary PM 2.5 for the Triad. Therefore, the NCDAQ will establish county level MVEBs for primary PM 2.5 for the Triad PM 2.5 nonattainment counties. The sections that follow discuss the insignificance of PM 2.5 emissions

Mobile Source PM 2.5 Emissions Insignificant

The NCDAQ has examined the sources of PM 2.5 emissions and their contribution to PM 2.5 formation in the nonattainment counties. This was accomplished using the 2009 emissions inventories developed for the attainment demons tration modeling. The percent contribution of primary PM 2.5 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 Transporta tion 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 PM 2.5 emissions from on-road mobile sources were doubled in the nonattainment areas, th erefore, 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 i nputs, showed no change. In both nonattainment areas, the modeling future design value increased by less than 0.1 μ g/m 3

. Based on the analysis discussed in detail in Appendix F.3, the NCDAQ steadfastly believes that the on-road mobile PM 2.5 emissions are insignificant contributors to the PM 2.5 nonattainment problem. The NCDAQ considers it unreasonable to expect that the PM 2.5 nonattainment areas will experience enough motor vehicle PM 2.5 emissions growth for a future PM 2.5 violation to occur due to mobile source direct PM 2.5 emissions.

Due to above analysis and agreement from the USEPA, budgets for direct PM 2.5 will not be set for the Hickory non-attainment area. An affi rmative insignificance finding from the USEPA only relieves the transportation partners fr om a regional emissions analysis for PM 2.5 emissions for this area and does not relieve them of the other tr ansportation conformity requirements. TheThe Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 61 transportation partners will need to note the PM 2.5 insignificance finding (if found adequate and approved by the USEPA) in futu re conformity determinations.

8.4 Establishing PM 2.5 and NO x Motor Vehicle Emission Budgets
As part of the consultation process on se tting MVEBs, the NCDAQ sent out a request for comment on setting the geographic extent of the MV EBs to all of the trans portation 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 PM 2.5 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 w ill not be set for the baseline year 2002.

Although the emissions are usually expressed in term s of tons, the MVEBs w ill be set in terms of kilograms (kg). The reason for this asserti on is because the MOBILE model generates the emissions factors in grams per mile. In past conf ormity exercises, there have been some issues with conversion to tons, as well as concerns with how th e MVEBs were rounded. Setting MVEBs in kilograms will avoid these issues in future conformity determinations.

Tables 8.4-1 and 8.4-2 below displa y the Triad highway mobile PM 2.5 and the Triad and Hickory highway mobile NO X emissions expressed in tons per ye ar 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 PM 2.5 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 NO X 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 10,010,856The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 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 PM 2.5 and the Triad and Hickory NO X MVEBs in kilograms per year, by county. Upon the USEPA’s affirmative adequacy finding for these county level sub-area MVEBs, these MVEB s 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 PM 2.5 MVEBs for 2009
County MVEB (Kilograms/year) Davidson 71,152 Guilford 164,286

Table 8.4-4. County Level NO x MVEBs for 2009

County MVEB (Kilograms/year) Catawba 2,887,955 Davidson 4,336,567 Guilford 10,010,856The Hickory and Greensboro/Winston-Salem/High Point, NC PM2.5 North Carolina Attainment Demonstration August 21, 2009 63 

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