Attainment Demonstration 

Knoxville, Tennessee 

Annual PM2.5 Nonattainment Area 

(Anderson, Blount, Knox, Loudon, and Roane 

Counties) 

Prepared by: 

Tennessee Department of Environment and Conservation 

Division of Air Pollution Control 

9th Floor L&C Annex 

401 Church Street 

Nashville, TN 37243
i 

TABLE OF CONTENTS 

Page

LIST OF TABLES 

LIST OF FIGURES 

LIST OF ACRONYMS AND ABBREVIATIONS 

ACKNOWLEDGEMENTS vi

EXECUTIVE SUMMARY vii

1.0 INTRODUCTION .............................................................................................................. 1

2.0 PM2.5 CONCEPTUAL DESCRIPTION ............................................................................. 6

3.0 NOX INSIGNIFICANCE .................................................................................................. 25

3.1. Significance of Precursors Contributing to Fine Particulate Matter ............................ 25

3.2. Determination of NOX Insignificance .......................................................................... 26

3.3. Elements of NOX Insignificance Demonstration ......................................................... 26

3.4. NOX Emissions Source Categories .............................................................................. 27

3.5. Federal Reference Method Observations ..................................................................... 29

3.6. Speciated Trends Network Observations ..................................................................... 33

3.7. Speciated PM2.5 for Federal Reference Method Monitors ........................................... 34

3.8. Speciated Modeled Attainment Test ............................................................................ 36

3.9. NOX Sensitivity Modeling ........................................................................................... 38

3.10. Summary ...................................................................................................................... 44

3.11. Addendum to Section 3.0 ............................................................................................. 44

4.0 EMISSION INVENTORIES ............................................................................................ 45

5.0 CONTROL MEASURES ................................................................................................. 58

5.3a. Tier 2 Vehicle Standards ...................................................................................... 64

5.3b. Heavy-Duty Gasoline and Diesel Highway Vehicle Standards ........................... 64

5.3c. Statewide Motor Vehicle Anti-Tampering Rule .................................................. 64

5.3d. Stage I Vapor Recovery ........................................................................................ 65

6.0 RACT/RACM ANALYSIS .............................................................................................. 66

7.0 MOTOR VEHICLE EMISSIONS BUDGETS ................................................................ 69

7.1. Transportation Conformity .......................................................................................... 69

7.2. PM2.5 Motor Vehicle Emission Budget........................................................................ 70

7.3. Presumed Precursors for PM2.5 .................................................................................... 71

7.4. Onroad Mobile Source Precursor Significance and Insignificance ............................. 73

8.0 MODELED ATTAINMENT DEMONSTRATION ........................................................ 75

8.10c. Particulate Matter and Component Species ............................................................. 87

8.12a(i). Mean PM2.5 Baseline Design Values .............................................................. 103

8.12a(ii). Speciated Baseline Conditions .................................................................... 105

8.12b. Step #2: Relative Response Factor Calculation .................................................... 108

8.12c. Step #3: Future Year Quarterly Concentration Calculation .................................. 110

8.12d. Step #4: Future Year Annual Average Estimate ................................................... 111

9.0 WEIGHT OF EVIDENCE ANALYSIS ......................................................................... 113

10.0 CONTINGENCY MEASURES ................................................................................... 123

10.2. Contingency Measures for NOX ................................................................................ 125

REASONABLE FURTHER PROGRESS ............................................................................ 126
ii 

LIST OF TABLES 

Table 1- 1: Knoxville Area Design Values ............................................................................... 2

Table 2- 1: PM2.5 Monitored Major Components .................................................................... 7 

Table 2- 2: Component Concentrations Relative to total PM2.5 ............................................... 8 

Table 2- 3: Knoxville Speciation Monitor 47-093-1020 ......................................................... 9 

Table 2- 4: Knoxville Speciation Monitor 47-093-1020 ......................................................... 9 

Table 2- 5: Emission Inventory Summary for Knoxville Nonattainment Area ..................... 10 

Table 2- 6: Acid Rain Program Emissions Data, Three-Year Averages ............................... 14 

Table 2- 7: Linear Correlation Coefficients ........................................................................... 15 

Table 2- 8: CAIR Modeling Results – Projected PM2.5 Concentrations for Knox County ... 16 

Table 3- 1: 2002 Actual NOX Emissions for Counties in Knoxville, TN PM2.5 Nonattainment 

Area. ........................................................................................................................................ 25 

Table 3- 2: 2009 NOX Emissions for Counties in Knoxville, TN PM2.5 Nonattainment Area.

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

Table 3- 3: Tennessee NOX Emissions in 2002 and 2009. .................................................... 25 

Table 3- 4: Quarterly and Annual Average 2002 Base Design Values (DVB) for the FRM 

Monitors in the Knoxville, TN PM2.5 Nonattainment Area .................................................... 32 

Table 3- 5: Annual Average Speciated 2002 DVB and 2009 DVF for FRM Monitors in the 

Knoxville, TN Nonattainment Area ........................................................................................ 34 

Table 3- 6: Annual Average PM2.5 for ASIP 2009 Base G2 Future Design Values and for 

Tennessee Statewide 100% NOX Emissions Reduction for FRM Monitors in Knoxville, TN 

PM2.5 Nonattainment Area ...................................................................................................... 36 

Table 3- 7: Annual Average PM2.5 for ASIP Base G2 2009 Future Design Values and for 

Tennessee Statewide 70% NOX Emissions Reduction for FRM monitors in Knoxville, TN 

PM2.5 Nonattainment Area ...................................................................................................... 37 

Table 3- 8: Changes in Quarterly and Annual Speciated PM2.5 (μg/m3

) Between 2009 Future 

Design Values and Tennessee Statewide 100% NOX Emissions Reductions for FRM 
iii 

Monitors in Knoxville, TN PM2.5 Nonattainment Area .......................................................... 38 

Table 3- 9: Changes in Quarterly and Annual Speciated PM2.5 (μg/m3

) Between 2009 Future 

Design Values and Tennessee Statewide 70% NOX Emissions Reductions for FRM Monitors 

in Knoxville, TN PM2.5 Nonattainment Area ......................................................................... 39

Table 4- 1: Total 2009 Annual Vehicle Miles Traveled in the Knoxville PM2.5

Nonattainment Area Used in ASIP Attainment Modeling ..................................................... 46 

Table 4- 2: Diesel Sulfur Input Used in NONROAD ............................................................. 46 

Table 4- 3: 2002 SO2 Emissions ............................................................................................ 47 

Table 4- 4: 2002 PM2.5 Emissions ......................................................................................... 47 

Table 4- 5: Point Sources in the Knoxville Nonattainment Area with > 100 tons/year SO2

Emissions, Sorted by Rank (2002 Actual Emissions) ............................................................ 48 

Table 4- 6: Point Sources with > 100 tons/year PM2.5 Emissions ......................................... 49 

Table 4- 7: 2009 SO2 Emissions ............................................................................................ 50 

Table 4- 8: 2009 PM2.5 Emissions ......................................................................................... 51 

Table 4- 9: 2002-2009 SO2 Emission Reductions ................................................................. 52 

Table 4- 10: 2002-2009 SO2 Emission Reductions ............................................................... 52 

Table 4- 11: 2002-2009 PM2.5 Emission Reductions ............................................................. 53 

Table 4- 12: 2002-2009 PM2.5 Emission Reductions .............................................................. 53 

Table 4- 13: Statewide SO2 Emission Inventory for Tennessee ............................................ 54 

Table 4- 14: Statewide PM2.5 Emission Inventory for Tennessee ......................................... 54 

Table 5- 1: SO2 Emissions 2000-2006 (Acid Rain Program Data) ....................................... 56 

Table 5- 2: Year-to-Year Change in SO2 Emissions .............................................................. 56 

Table 5- 3: PM2.5 Contributions to Tennessee Nonattainment Counties ............................... 58 

Table 5- 4: CAIR Annual SO2 State Trading Budgets .......................................................... 59 

Table 5- 5: CAIR SO2 Controls at Tennessee Valley Authority EGUs ................................. 59 

Table 7- 1: Total 2009 Annual Vehicle Miles Traveled in the Knoxville PM2.5

Nonattainment Area ................................................................................................................ 66 
iv 

Table 7- 2: PM2.5 MVEB for 2009 ......................................................................................... 67 

Table 8- 1: Vertical Layer Definition for MM5 Simulations and Approach For Reducing 

CMAQ Layers By Collapsing Multiple MM5 Layers ............................................................ 78

Table 8- 2: Available VISTAS/ASIP Region 2002 Ambient Monitoring Data .................... 84

Table 8- 3: Fractional Bias and Fractional Error Model Performance Metrics ..................... 85

Table 8- 4: ASIP Model Performance Goals and Criteria for PM2.5 Components ................. 85

Table 8- 5: Regional Model Performance Evaluation Summary of Results .......................... 86

Table 8- 6: Quarterly and Annual Average Component-Specific Concentrations for the FRM 

Monitors in the Knoxville, TN PM2.5 Nonattainment Area .................................................. 104

Table 9- 1: 2009 Change in SO2 Emissions by Category ..................................................... 110 

Table 9- 2: 2009 Change in PM2.5 Emissions by Category ................................................. 111 

Table 9- 3: Additional SO2 Reductions Not Included in 2009 Emission Inventory ............ 111 

Table 9- 4: Qualitative Weighting of Evidence (Not Including Modeled Attainment 

Demonstration) ..................................................................................................................... 116 

LIST OF FIGURES 

Figure 1- 1: PM2.5 Final Nonattainment Designations, Effective April 5, 2005 ...................... 2 

Figure 1- 2: Map of Roane County Partial Nonattainment Area ............................................. 2 

Figure 1- 3: Map of FRM Monitors in Knoxville Nonattainment Area .................................. 3 

Figure 2- 1: Regional Emissions Distribution and PM2.5 Gradients ...................................... 10 

Figure 2- 2: Tennessee Geographic Regions ......................................................................... 11 

Figure 2- 3: Shaded relief Imagery of Knoxville Nonattainment Area ................................. 12 

Figure 2- 4: Elevation of Knoxville PM2.5 Sites .................................................................... 12 

Figure 2- 5: Three-Year Wind Rose for Knoxville Region ................................................... 13 

Figure 2- 6: PM2.5 Trends for Knoxville (2000-2006) ........................................................... 15 

Figure 2- 7: Scatter Plot of Ambient Monitored Data and Tennessee SO2 Emissions .......... 15 

Figure 2- 8: Scatter Plot of Ambient Monitored Data and Regional SO2 Emissions ............ 15 
v 

Figure 2- 9: Wind Rose Analysis for High PM2.5 Days ......................................................... 17 

Figure 2- 10: General Trends of Ambient PM2.5 and Ozone, Knoxville, Tennessee............. 18 

Figure 2- 11: Comparison of Ambient PM2.5 and Ozone, Knoxville, Tennessee .................. 19 

Figure 2- 12: Comparison of PM2.5 Speciated Components, FRM Monitor 47-093-1020 .... 20 

Figure 2- 13: Comparison of PM2.5 Speciated Components (Winter Months Only), FRM 

Monitor 47-093-1020 .............................................................................................................. 21 

Figure 3- 1: Annual Average PM2.5 from 2000-2006 at Three Federal Reference Method 

Monitors in Knox County, TN. ............................................................................................... 26

Figure 3- 2: Quarterly and Annual Average PM2.5 in 2000 Through 2006 from Federal 

Reference Method Monitors in Knox County, TN PM2.5 Nonattainment Area. .................... 28 

Figure 3- 3: Quarterly and Annual Average PM2.5 in 2000 through 2006 from Federal 

Reference Method Monitors for Counties in the Knoxville, TN PM2.5 Nonattainment Area. 29 

Figure 3- 4: Quarterly and Annual Average Speciated PM2.5 Mass from Speciated Trend 

Network (STN) Monitor for 2002 through 2006 at Spring Hill Elementary School in 

Knoxville, TN (47-093-1020). ................................................................................................ 30 

Figure 3- 5: Quarterly and Annual Average 2002 Base Design Values (DVB) Calculated 

Using the SANDWICH Method and the 2000-2004 PM2.5 Data for the Spring Hill 

Elementary School FRM monitor (47-093-1020) in Knoxville, TN ...................................... 32 

Figure 3- 6: Annual Average PM2.5 2002 Base Design Values (DVB) and 2009 Future 

Design Values (DVF) for the FRM Monitors in the Knoxville, TN Nonattainment Area ..... 34 

Figure 3- 7: Atmospheric Aerosol Processes ......................................................................... 36 

Figure 3- 8: Annual Average Speciated Response to Tennessee Statewide 100% NOX

Reduction in 2009 for FRM Monitors in Knoxville, TN PM2.5 Nonattainment Area ............ 40 

Figure 3- 9: Annual Average Speciated Response to Tennessee Statewide 70% NOX

Reduction in 2009 for FRM Monitors in Knoxville, TN PM2.5 Nonattainment Area ............ 40 

Figure 5- 1: Tennessee and Regional SO2 Emissions ............................................................ 57 

Figure 5- 2: Change in SO2 Emissions at TVA Bull Run and Kingston, 2000-2006 ............ 57 

Figure 8- 1: MM5 Horizontal Domain (Blue) with Nested CMAQ 36-km Domain ............. 77 

Figure 8- 2: ASIP Region 12-km Grid ................................................................................... 77 

Figure 8- 3: IMPROVE, STN, CASTNet, NADP and SEARCH Monitoring Sites in the 

VISTAS/ASIP Region and VISTAS/ASIP 12-km grid. ......................................................... 84 
vi 

Figure 8- 4: Scatter Plots of Predicted and Observed Sulfate (SO4) Concentrations for 

January, April, July and October 2002, STN Sites in Tennessee and the CMAQ 2002 36 and 

12 km Base G2 Actual Base Case Simulation ........................................................................ 87 

Figure 8- 5: Scatter Plots of Predicted and Observed Nitrate (NO3) Concentrations for 

January, April, July and October 2002, STN Sites in Tennessee and the CMAQ 2002 36 and 

12 km Base G2 Actual Base Case Simulation ........................................................................ 88 

Figure 8- 6: Scatter Plots of Predicted and Observed Ammonium (NH4) Concentrations for 

January, April, July and October 2002, STN Sites in Tennessee and the CMAQ 2002 36 and 

12 km Base G2 Actual Base Case Simulation. ....................................................................... 89 

Figure 8- 7: Scatter Plots of Predicted and Observed Organic Matter Carbon (OCM) 

Concentrations for January, April, July and October 2002, STN Sites in Tennessee and the 

CMAQ 2002 36 and 12 km Base G2 Actual Base Case Simulation ...................................... 90 

Figure 8- 8: Scatter plots of Predicted and Observed Elemental Carbon (EC) Concentrations 

for January, April, July and October 2002, STN Sites in Tennessee and the CMAQ 2002 36 

and 12 km Base G2 Actual Base Case Simulation ................................................................. 91 

Figure 8- 9: Scatter Plots of Predicted and Observed Fine Particulate Mass (PM2.5) 

Concentrations for January, April, July and October 2002, STN Sites in Tennessee and the 

CMAQ 2002 36 and 12 km Base G2 Actual Base Case Simulation ...................................... 92 

Figure 8- 10: Scatter Plots of Predicted and Observed Fine Particulate Mass (PM2.5) 

Concentrations for January, April, July and October 2002, FRM Sites in Tennessee and the 

CMAQ 2002 36 and 12 km Base G2 Actual Base Case Simulation ...................................... 93 

Figure 8- 11: Soccer Plot of Monthly Fractional Bias versus Fractional Gross Error for PM2.5 

Mass at FRM Monitors in Tennessee for the CMAQ 12-km 2002 Base G2 Actual Base Case 

Simulation ............................................................................................................................... 94 
vii 

LIST OF ATTACHMENTS 

Attachment A Development document for emission inventories 

Attachment B Emission inventory summary 

Attachment C ASIP Modeling Protocol 

Attachment D MVEB Documentation 

Attachment E Air Quality Data 

Attachment F Model Performance Evaluation 

Attachment G Attainment Demonstration 

Attachment H Utility SO2 Correlations 

Attachment I Limited RACT Analysis 

Attachment J MM5 Report 

Attachment K CART Analysis Report 

Attachment L GEOS CHEM Report 

Attachment M CAIR SMAT Procedure 

Attachment N 2009 Best & Final Changes to Emission Inventory 

Attachment O Data for 2009 Base G4a PM2.5 Projections 

Attachment P Public Participation 

Attachment Q NOX Addendum 

LIST OF ACRONYMS AND ABBREVIATIONS 

AEB Actual Emissions Basis 

AIRS Aerometric Information Retrieval System 

AQS Air Quality System 

ASIP Association for Southeastern Integrated Planning 

BACT Best Available Control Technology 

BAMS Baron Advanced Meteorological Systems 

BC Boundary Condition 

BCON CMAQ model boundary condition processor 

CAA Clean Air Act 

CAIR Clean Air Interstate Rule 

CART Classification and Regression Tree 

CASTNET Clean Air Status and Trends Network 

CCTM CMAQ Chemical Transport Model 

CERR Consolidated Emissions Reporting Rule 

CFR Code of Federal Regulations 

CMAQ Community Multiscale Air Quality Model 

DON Degree of Neutralization 

DVC Current-Year Design Value 

DVF Future-Year Design Value 

EC Elemental Carbon 

EGU Electricity Generating Unit 

EPA Environmental Protection Agency 

FR Federal Register 

FRM Federal Reference Method 

GEOS-CHEM Global simulation model 
viii 

I/M Inspection and Maintenance 

IMPROVE Interagency Monitoring of Protected Environments 

IPM Integrated Planning Model 

KAT Knoxville Area Transit 

km Kilometer 

μg/m3 Micrograms per Cubic Meter 

μm Micrometer (or micron), 10-6 m 

LAER Lowest Achievable Emission Rate 

MM5 Mesoscale Meteorological Model 

MOBILE6.2 EPA's newest emissions factor model for onroad mobile sources

NADP National Acid Deposition Network 

NAAQS National Ambient Air Quality Standards 

NH3 Ammonia 

NH4 Ammonium Ion 

NLEV National Low Emission Vehicles 

NNSR Nonattainment New Source Review 

NONROAD EPA's model for generating emissions from nonroad engines (not 

including aircraft, marine and locomotives) 

NOX Nitrogen Oxides 

NO3 Nitrate Ion 

OC Organic Carbon 

OPP Other primary inorganic particulate matter (crustal) 

PBW Particle Bound Water 

PM2.5 Fine Particulate Matter (Less Than 2.5 μm Diameter) 

ppm Parts per Million 

PSD Prevention of Significant Deterioration 

QAPP Quality Assurance Project Plan 

QA/QC Quality Assurance/Quality Control 

RACM Reasonably Available Control Measures 

RACT Reasonably Available Control Technology 

RBLC RACT-BACT-LAER Clearinghouse 

RFP Reasonable Further Progress 

RPO Regional Planning Organization 

RRF Relative Reduction Factor 

SANDWICH Sulfate, Adjusted Nitrate, Derived Water, Inferred Carbon Hybrid 

SCC Source Classification Code 

SCR Selective Catalytic Reduction 

SEARCH Southeastern Aerosol Research and Characterization 

SIP State Implementation Plan 

SMAT Speciated Modeled Attainment Test 

SMOKE Sparse Matrix Operator Kernel Emissions Modeling System 

SNCR Selective Noncatalytic Reduction 

SO2 Sulfur Dioxide 

SO4 Sulfate Ion 

STN Speciated Trends Network 

TAPCR Tennessee Air Pollution Control Regulations 
ix 

TDEC Tennessee Department of Environment and Conservation 

TDOT Tennessee Department of Transportation 

TEB Typical Emissions Basis 

TN Tennessee 

TOMS Total Ozone Mapping Spectrometer 

TVA Tennessee Valley Authority 

VISTAS Visibility Improvement State and Tribal Association of the Southeast 

VOC Volatile Organic Compounds 

WRAP Western Air Regional Partnership 
x 

ACKNOWLDEDGEMENTS 

Tennessee gratefully acknowledges the efforts of Pat Brewer and the ASIP workgroup for 

their assistance with this document. We would also like to thank the members of the North 

Carolina Department of Environment and Natural Resources, Division of Air Quality, for 

performing NOX zero-out modeling runs for Tennessee. 
xi 

EXECUTIVE SUMMARY 

The Knoxville, Tennessee PM2.5 nonattainment area includes Anderson, Blount, Knox, and 

Loudon Counties in their entirety, as well as the portion of Roane County that falls within the 

census block that includes the Tennessee Valley Authority’s Kingston Fossil Plant. Between 

2001 and 2003, air quality monitoring at several sites within this region indicated that the 

annual average PM2.5 concentrations exceeded the 15.0 μg/m3 National Ambient Air Quality 

Standard (NAAQS), and EPA designated the area as nonattainment for the annual PM2.5

NAAQS, effective April 5, 2005. 

Air quality modeling conducted for Tennessee by the Association for Southeastern Integrated 

Planning (ASIP) indicates that the Knoxville-area nonattainment counties will attain the 

NAAQS in 2009. The model results are based upon 2002-2009 emissions reductions from 

Knoxville area sources and are supported by downward trends in emissions, with concurrent 

improvements in air quality for the Knoxville area. Tennessee expects to attain the PM2.5

NAAQS in the Knoxville region based upon implementation of Federal measures, and no 

additional local controls are planned. 
1 

1.0 INTRODUCTION 

Fine particles in the atmosphere are comprised of a complex mixture of components. Common 

constituents include: sulfate (SO4); nitrate (NO3); ammonium; elemental carbon; a great variety 

of organic compounds; and inorganic “crustal” material, which includes metals, dust, sea salt, 

and other trace elements. Airborne particles generally less than or equal to 2.5 micrometers in 

diameter are considered to be ‘‘fine particles’’ (also referred to as PM2.5). ‘‘Primary’’ particles 

are emitted directly into the air as a solid or liquid particle (e.g., elemental carbon from diesel 

engines or fire activities, or condensable organic particles from gasoline engines). ‘‘Secondary’’ 

particles (e.g., sulfate and nitrate) form in the atmosphere as a result of various chemical 

reactions. 

EPA established air quality standards for PM2.5 based on evidence from numerous health studies 

demonstrating that serious health effects are associated with exposures to elevated levels of 

PM2.5. Epidemiological studies have shown statistically significant correlations between elevated 

PM2.5 levels and premature mortality. Other important effects associated with PM2.5 exposure 

include aggravation of respiratory and cardiovascular disease (as indicated by increased hospital 

admissions, emergency room visits, absences from school or work, and restricted activity days), 

changes in lung function and increased respiratory symptoms, as well as new evidence for more 

subtle indicators of cardiovascular health. Individuals particularly sensitive to PM2.5 exposure 

include older adults, people with heart and lung disease, and children. 

On July 18, 1997, EPA revised the NAAQS for particulate matter (PM) to add new standards for 

fine particles, using PM2.5 as the indicator. EPA established health-based (primary) annual and 

24-hour standards for PM2.5. The annual standard was set at a level of 15.0 micrograms per cubic 

meter, as determined by the 3-year average of annual mean PM2.5 concentrations. The 24-hour 

standard was set at a level of 65 micrograms per cubic meter, as determined by the 3-year 

average of the 98th percentile of 24-hour concentrations. Following a second review of the 

NAAQS in October 2006, the 24-hour PM2.5 standard was strengthened to a level of 35 

micrograms per cubic meter, based on the 3-year average of the 98th percentile of 24-hour 

concentrations, and the level of the annual standard remained unchanged. In both 1997 and 2006 

EPA established welfare-based (secondary) standards identical to the levels of the primary 

standards. EPA’s final PM2.5 designations for areas violating the 1997 standards were issued on 

December 17, 2004 and published in the Federal Register on January 5, 20051

. 

The nonattainment designation for an area initiates a process that requires affected States to 

develop an implementation plan that includes, among other things, a demonstration showing how 

it will attain the ambient standards by the attainment dates required in the CAA. To assist States 

with the development of implementation plans, EPA issued the fine particle implementation rule 

on April 25, 2007. This rule requires States to submit their SIPs to EPA by April 5, 2008, three 

years from the effective date of the designations. 

The Knoxville Tennessee PM2.5 nonattainment area includes Anderson, Blount, Knox, and 

Loudon in their entirety, as well as the portion of Roane County that falls within the census block 

that includes the Tennessee Valley Authority’s Kingston Fossil Plant. 

 

1 Federal Register / Vol. 70, No. 3 / Wednesday, January 5, 2005, page 944. 
2 

Figure 1- 1: PM2.5 Final Nonattainment Designations, Effective April 5, 2005 

Figure 1- 2: Map of Roane County Partial Nonattainment Area 
3 

For the calendar years 2001 to 2003, air quality monitoring at several sites within this region 

indicated that the highest annual average PM2.5 concentrations exceeded the 15.0 μg/m3

 NAAQS 

(Table 1- 1). EPA subsequently designated the area as nonattainment for the annual PM2.5

NAAQS, effective April 5, 2005. Air quality modeling data for the Knoxville area predicts that 

PM2.5 concentrations at these monitors will attain the NAAQS during the 2009 calendar year2. 

These areas are predicted to attain the PM2.5 NAAQS based on existing State and national 

measures, without additional local controls. 

Table 1- 1: Knoxville Area Design Values3

AIRS ID Address County 

PM2.5 Design Value in μg/m3

2002-2004 2003-2005 2004-2006 

47-093-0028 1000 Francis Road Knox 14.5 14.5 15.2 

47-093-1017 1613 Vermont Avenue Knox 15.7 15.6 15.6 

47-093-1020 4625 Mildred Drive Knox 15.1 15.1 15.2 

47-009-0011 2007 Sequoyah Avenue Blount 13.9 14.1 14.1 

47-145-0004 1002 North Roane Street Roane 13.6 14.2 14.5 

 

2 The PM2.5 implementation rule states that, since PM2.5 designations have an effective date of April 5, 2005, the initial 5-year attainment date for 

PM2.5 areas would be no later than April 5, 2010, based on air quality data from the three previous calendar years (i.e. 2007, 2008, and 2009) 

[Federal Register / Vol. 72, No. 79 / Wednesday, April 25, 2007, page 20600]. However, EPA’s Guidance on the Use of Models and Other 

Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze states: 

“The logic for requiring emissions reductions by the year (or season) immediately preceding the attainment year follows 

from language in the Clean Air Act. The Clean Air Act (172(a)(2)(C)) identifies a process by which attainment is expected 

to occur. Shortly after the attainment deadline, EPA is to evaluate whether areas have attained. If the area is clean for the 

last three years, then the area has met the attainment deadline. But if the area was above the standard for earlier 

years/seasons but has clean data for the single year/season immediately preceding the attainment date (and if the area has 

met planning requirements), the area is eligible for a 1-year extension of the attainment deadline. If the air is clean again 

the following year, the area is eligible for a second 1-year extension of the attainment deadline. The expectation is then that

the third year's data, in combination with data from years 1 and 2, will show attainment (This is commonly referred to as 

the “clean data policy”.) Therefore, emissions in the year preceding the attainment year should be at a level that is 

consistent with attainment. It also follows that the year preceding the attainment year should be modeled for attainment 

planning purposes.” [page 35] 

Thus, the PM2.5 attainment demonstration must demonstrate attainment of the NAAQS for a single year (2009), even if attainment is ultimately 

based on a three-year design value. 

3 Two monitors: 47-093-1013 (1403 Davanna Street in Knox County) and 47-105-0108 (130 Webb Drive in Loudon County) did not have 12 

quarters of complete data during the 2000-2004 baseline period and therefore were not addressed in the modeled attainment demonstration. 

Tennessee is including the data from the Loudon monitor in the weight of evidence section (Section 9.0) to demonstrate, based on the weight of 

evidence, that both monitors will attain the NAAQS in 2009. Monitor 47-093-1013 was operated April 2002 to February 2004 and shut down 

until March 2007. 
4 

Figure 1- 3: Map of FRM Monitors in Knoxville Nonattainment Area 

The Clean Air Fine Particle Implementation Rule (40 CFR 51 Subpart Z) was promulgated on 

April 25, 2007. This rule requires affected States to address nonattainment by adopting a 

federally enforceable State Implementation Plan (SIP). The SIP documents how an area will 

attain the NAAQS and generally contains four elements: emission inventory, modeled 

attainment demonstration, Reasonably Available Control Technology/Reasonably Available 

Control Measures (RACT/RACM) analysis, and adoption of controls. 40 CFR 51 Subpart Z 

specifies the following requirements for PM2.5 SIPs: 

• Affected States must submit the SIP no later than three years from the date of 

designation. 

• The SIP must identify and evaluate sources of PM2.5 direct emissions and PM2.5 

attainment plan precursors in accordance with §§51.1009 and 51.1010, as follows: 

- The SIP must address sulfur dioxide as a PM2.5 attainment plan precursor and evaluate 

sources of SO2 emissions in the State for control measures. 
5 

- The SIP must address NOX as a PM2.5 attainment plan precursor and evaluate 

sources of NOX emissions in the State for control measures, unless the State and 

EPA provide an appropriate technical demonstration for a specific area showing 

that NOX emissions from sources in the State do not significantly contribute to 

PM2.5 concentrations in the nonattainment area. 

- The SIP is not required to address VOC as a PM2.5 attainment plan precursor and 

evaluate sources of VOC emissions in the State for control measures, unless the 

State provides an appropriate technical demonstration for a specific area showing 

that VOC emissions from sources in the State significantly contribute to PM2.5 

concentrations in the nonattainment area, or unless EPA provides such a technical 

demonstration. 

- The SIP is not required to address ammonia as a PM2.5 attainment plan precursor 

and evaluate sources of ammonia emissions from sources in the State for control 

measures, unless the State provides an appropriate technical demonstration for a 

specific area showing that ammonia emissions from sources in the State 

significantly contribute to PM2.5 concentrations in the nonattainment area, or 

unless EPA provides such a technical demonstration. 

• Consistent with CAA §172(a)(2)(A), PM2.5 nonattainment areas must demonstrate 

attainment of the NAAQS no more than five years from the date of designation, unless an 

extension is granted. 

• The attainment demonstration must include inventory data, modeling results, and 

emission reduction analyses on which the State has based its projected attainment date. 

The attainment demonstration and supporting air quality modeling should be consistent 

with EPA's PM2.5 modeling guidance. 

• SIPs must include emission inventories for direct PM2.5 emissions and emissions of PM2.5 

precursors, as well as any additional emission inventory information needed to support an 

attainment demonstration. For purposes of defining the data elements for these 

inventories, the PM2.5 and PM2.5 precursor-relevant data element requirements under 40 

CFR 51 Subpart A shall apply. 

• SIPs must include provisions for reasonably available control measures (RACM), 

reasonably available control technology (RACT), and reasonable further progress (RFP), 

as necessary to demonstrate attainment. 

• SIPs must include specific contingency measures to be undertaken if the area fails to 

attain the PM2.5 NAAQS by its attainment date. The contingency measures must take 

effect without significant further action by the State or EPA. 
6 

2.0 PM2.5 CONCEPTUAL DESCRIPTION 

Development of a PM2.5 conceptual model is necessary for any analysis of PM2.5 attainment 

issues. EPA has suggested a series of questions4

 that, when answered, describe the nonattainment 

problem. They are: 

1. Is the nonattainment problem primarily a local one, or are regional factors important? 

2. What is the relative importance of measured primary and secondary components of PM2.5

measured at sites violating the NAAQS? 

3. What are the most prevalent components of measured PM2.5? 

4. Does the measured mix of PM2.5 components appear to roughly agree with mix of 

emission categories surrounding the monitoring sites? 

5. Do there appear to be any areas with large gradients of primary PM2.5 in monitored or 

unmonitored areas? 

6. Is there any indication of what precursor might be limiting formation of secondary 

particulate matter? 

7. Do monitored violations occur at locations subject to mesoscale wind patterns (e.g., at a 

coastline) which may differ from the general wind flow? 

8. Have there been any recent major changes in emissions of PM2.5 or its precursors in or 

near the nonattainment area? What? 

9. Are there discernible trends in design values or other air quality indicators which have 

accompanied a change in emissions? 

10. Is there any apparent spatial pattern to the trends in design values? 

11. What past modeling has been performed and what do the results suggest? 

12. Are there any distinctive meteorological measurements at the surface or aloft which 

appear to coincide with occasions with PM2.5 concentrations in excess of 15.0 μg/m3? 

13. Do periods with high measured particulate matter or components of particulate matter 

appear to track each other or any other measured pollutant? 

EPA’s guidance states that the responses to the preceding questions in this example may be used 

to construct an initial conceptual description of the nonattainment area’s PM2.5 problem. For 

example, questions 1, 2 and 3 can indicate whether the area’s nonattainment problem includes 

 

4 U. S. EPA, Guidance on the Use of Models and Other Analysis for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and 

Regional Haze, April 2007, pages 128-130. 
7 

significant local or regional components. Questions 11, 12 and 13 may be used to assess the 

relationship of ozone and particulate matter reductions, and whether it is appropriate to examine 

the effects of existing strategies to reduce ozone and national PM2.5 control measures before 

simulating additional control measures. Questions 4 and 5 can indicate whether a “local area 

analysis” is needed, and question 7 can suggest whether it is necessary to model with very small 

grid cells, at least for the secondary components of PM2.5. 

To bring the area into attainment, an understanding of the chemical and physical factors that 

influence PM2.5 in the area of interest and that potentially result in exceedances of the annual 

PM2.5 standard are needed. EPA’s questions have been used to develop a conceptual description 

for the Knoxville area’s PM2.5 problem, as follows: 

1. Is the nonattainment problem primarily a local one, or are regional factors important? 

The Knoxville area is affected by local emissions of PM2.5 precursors and by regional transport 

of emissions from upwind areas. The attainment demonstration modeling conducted for 

Tennessee by the Association for Southeastern Integrated Planning (ASIP)5 demonstrated that 

the area would attain the NAAQS with a mixture of controls for both local and regional sources. 

Large regional sources located within the Knoxville area are believed to impact local PM2.5

concentrations. 

2. What is the relative importance of measured primary and secondary components of PM2.5

measured at sites violating the NAAQS? 

PM2.5 is a mixture of primary components (directly emitted PM2.5) and secondary precursors that 

react in the atmosphere to form fine particulate matter. PM2.5 in the Knoxville area includes the 

following components: 

• Nitrates are formed from atmospheric reactions of NOX with ammonia. NOX is emitted 

from all combustion processes, including onroad and nonroad mobile sources, electric 

generation from fossil fuels, industrial and commercial fuel burning, and burning of 

vegetation. 

• Sulfates are formed from atmospheric reactions of SO2 with ammonia. Coal-fired electric 

utilities account for most SO2 emissions, with smaller quantities emitted by stationary and 

mobile sources that burn fuel oils. 

• Ammonia that reacts with NOX and SO2 is emitted from automobile catalysts, sewage 

treatment, and agriculture. 

• Organic carbon is a complex category that includes motor vehicle emissions, industrial 

5 In 2001, southeastern States began collaborative work on State Implementation Plans to address regional haze through the Visibility 

Improvement State and Tribal Association of the Southeast (VISTAS). VISTAS member States include Alabama, Georgia, Kentucky, 

Mississippi, North Carolina, South Carolina Tennessee, Virginia, and West Virginia, and the local programs within these States. 

The PM2.5 attainment demonstration builds upon the VISTAS work through the Association for Southeastern Integrated Planning (ASIP). The 

ASIP work group includes the original VISTAS members. The collaborative approach of VISTAS and ASIP allows member States to address 

regional issues, such as interstate transport, and to save labor by avoiding duplication of modeling efforts. 
8 

VOC emissions, and biogenic compounds. Toluene, xylene, and trimethyl benzene are 

considered to be the most significant industrial precursors for secondary organic aerosol 

(SOA). 

The major PM2.5 components measured at speciation monitor 47-093-1020 (Mildred Drive) are 

shown in Table 2- 1: 

Table 2- 1: PM2.5 Monitored Major Components 

Speciation Site 47-093-1020 

Year PM2.5

(μg/m3)

*

PM2.5

(μg/m3)

**

Nitrate 

(μg/m3) 

Sulfate 

(μg/m3) 

Organic 

Carbon 

(μg/m3) 

Elemental 

Carbon 

(μg/m3) 

Ammonium 

(μg/m3) 

2002 16.1 16.5 0.849 5.434 5.9668 0.57 1.641 

2003 14.3 15.9 0.914 5.217 6.321 0.724 1.595 

2004 14.9 13.4 1.152 3.865 5.9066 0.784 1.306 

2005 16.2 15.6 0.997 4.993 6.3168 0.848 1.569 

2006 14.4 15.5 0.806 4.473 6.1824 0.778 1.333 

* Federal Reference Method (FRM) sampler mass 

** Speciation sampler mass. The difference in FRM and speciation sampler results may result from the sample collection 

frequency of the respective monitors. The FRM sampler collects a daily sample, while the speciation sampler operates on a 

1:6 collection frequency (a sample is collected every six days). 

3. What are the most prevalent components of measured PM2.5? 

For the Knoxville region, the PM2.5 components are listed by percentage of total PM2.5 in Table 

2- 2. On an annual average basis, the most prevalent PM2.5 components for all years were, in 

order, organic carbon, sulfate, and ammonium. Nitrate tends to replace ammonium when 

individual daily sampled values are compared (Table 2- 3), but not when results are averaged 

(Table 2- 4). 

 

Table 2- 2: Component Concentrations Relative to total PM2.5

Year 

Total 

PM2.5 Nitrate Sulfate 

Organic 

Carbon 

Elemental 

Carbon Ammonium "Other" 

2002 100.0% 5.1% 32.9% 36.2% 3.5% 9.9% 12.4% 

2003 100.0% 5.7% 32.8% 39.8% 4.6% 10.0% 7.1% 

2004 100.0% 8.6% 28.8% 44.1% 5.9% 9.7% 2.9% 

2005 100.0% 6.4% 32.0% 40.5% 5.4% 10.1% 5.6% 

2006 100.0% 5.2% 28.9% 39.9% 5.0% 8.6% 12.4% 

Total PM2.5 in this table is based on speciation sampler mass. "Other" includes PM2.5 that is not nitrate, sulfate, organic carbon, elemental 

carbon, or ammonia. 
9 

Table 2- 3: Knoxville Speciation Monitor 47-093-1020 

Highest Daily Sampled Values (μg/m3) 

Year First Max 2nd Max 3rd Max 4th Max 5th Max 

2002 15.8 

Sulfate 

9.9 

Organic Carbon 

4.5 

Ammonium Ion 

2.61 

Nitrate 

1.37 

Elemental Carbon 

2003 18.2 

Sulfate 

10.7 

Organic Carbon 

4.5 

Nitrate 

4.28 

Ammonium Ion 

2.2 

Elemental Carbon 

2004 10.7 

Sulfate 

9.5 

Organic Carbon 

3.23 

Nitrate 

3.02 

Ammonium Ion 

2.6 

Elemental Carbon 

2005 15.5 

Sulfate 

10.4 

Organic Carbon 

6.62 

Nitrate 

3.78 

Ammonium Ion 

2.06 

Elemental Carbon 

2006 11.0 

Sulfate 

10.8 

Organic Carbon 

4.09 

Nitrate 

3.02 

Ammonium Ion 

2.59 

Elemental Carbon 

Table 2- 4: Knoxville Speciation Monitor 47-093-1020 

Highest Average of the Daily Sampled Values (μg/m3) 

Year First Max 2nd Max 3rd Max 4th Max 5th Max 

2002 5.43 

Sulfate 

4.26 

Organic Carbon 

1.64 

Ammonium Ion 

0.85 

Nitrate 

0.57 

Elemental Carbon 

2003 5.22 

Sulfate 

4.52 

Organic Carbon 

1.60 

Ammonium Ion 

0.91 

Nitrate 

0.73 

Elemental Carbon 

2004 4.22 

Organic Carbon 

3.87 

Sulfate 

1.31 

Ammonium Ion 

1.15 

Nitrate 

0.78 

Elemental Carbon 

2005 4.99 

Sulfate 

4.51 

Organic Carbon 

1.57 

Ammonium Ion 

1.00 

Nitrate 

0.85 

Elemental Carbon 

2006 4.47 

Sulfate 

4.42 

Organic Carbon 

1.33 

Ammonium Ion 

0.81 

Nitrate 

0.78 

Elemental Carbon 

4. Does the measured mix of PM2.5 components appear to roughly agree with mix of 

emission categories surrounding the monitoring sites? 

The overall mix of PM2.5 components does not match the mix of precursor emissions in the 

surrounding area, primarily due to the large NOX component in the emission inventory. 

Speciation data for 2002 at the Mildred Drive monitor was compared with emission inventory 

data developed for Tennessee by the Association for Southeastern Integrated Planning (ASIP). 

Regional emissions for the nonattainment area were calculated by summing all counties for each 

emission category (area sources, nonroad, onroad, and actual or typical emissions from point 

sources) and calculating a grand total. 

The results of this analysis are shown in Table 2- 5, which indicates that there are significant 

NOX emissions within the region. However, NOX does not contribute significantly to PM2.5

formation (see Section 3.0 for additional information), and as indicated above in Table 2- 2, 

nitrate does not constitute a significant fraction of monitored PM2.5. 

When speciation data is compared with emission inventory data for other pollutants, there is 

rough agreement between sulfate concentrations at the Speciated Trends Network (STN) monitor 

(29-33% of total PM2.5 at the Mildred Drive monitor) and emissions of sulfur dioxide (about 
10 

34% of regional precursor emissions). Similar results are observed for ammonia, although there 

is greater variation in the fraction of speciated PM2.5 at the monitor (3-12%). Ammonia 

emissions in the nonattainment area were about 0.7% of total precursor emissions in 2002, 

suggesting that biogenic emissions or transport may be important during some years, while local 

anthropogenic emissions predominate in others. The organic carbon fraction of speciated PM2.5

(36-44% of total PM2.5 at the Mildred Drive monitor) is significantly higher than the 

corresponding emission inventory fraction of VOC, (about 14%) suggesting a significant 

biogenic influence for this pollutant. 

Table 2- 5: Emission Inventory Summary for Knoxville Nonattainment Area 

Regional Emissions in Tons/Year 

PM2.5 NOX SO2 VOC NH3 Total 

2002 Total (AEB)** 10,840 134,218 93,619 36,222 1,893 276,792 

2002 Total (TEB)** 10,536 127,244 90,891 36,210 1,886 266,768 

2002 % of Total (AEB) 3.9% 48.5% 33.8% 13.1% 0.7% 100.0% 

2002 % of Total (TEB) 3.9% 47.7% 34.1% 13.6% 0.7% 100.0% 

** AEB = "Actual Emissions Basis", TEB = "Typical Emissions Basis" 

5. Do there appear to be any areas with large gradients of primary PM2.5 in monitored or 

unmonitored areas? 

The spatial distribution of PM2.5 in the nonattainment area is illustrated by Figure 2- 1, which 

shows the design values of each county and their respective annual and daily 2004 to 2006 

design values. Figure 2- 1 indicates that the distribution of measured PM2.5 is reasonably 

uniform, with the numbers falling in the range of 14.1 to 15.6 μg/m3 for the controlling monitors 

in each county where PM2.5 monitoring is currently being conducted. The annual design values 

are further augmented by the daily average PM2.5 design values, which range from 30 to 33 

μg/m3 for the same area. The emissions data for the major contributing PM2.5 pollutants and/or 

precursors are also depicted in the slides, with the color variations denoting the relative emission 

density. Despite the variation in emissions density, the PM2.5 levels appear to be reasonably 

uniform, with little evidence of significant gradients. Although one county in the area does not 

have a PM2.5 monitor, it would be reasonable to conclude that the county is similar in PM2.5

ambient levels to the other adjacent counties. 
11 

Figure 2- 1: Regional Emissions Distribution and PM2.5 Gradients
12 

Figure 2- 1 (Continued) 
13 

Figure 2- 1 (Continued) 

6. Is there any indication of what precursor might be limiting formation of secondary 

particulate matter? 

The preceding comparison of monitoring and emission inventory data (Question #4) suggests 

that sulfate is the limiting precursor for secondary particulate formation. Nitrogen oxides do not 

appear to be a significant PM2.5 precursor and the organic carbon and ammonia fractions appear 

to have a significant biogenic component. The data suggest that reduction of anthropogenic SO2

emissions would have the greatest impact on PM2.5 concentrations in the Knoxville area. 

7. Do monitored violations occur at locations subject to mesoscale wind patterns (e.g., at a 

coastline) which may differ from the general wind flow? 

The Knoxville PM2.5 nonattainment area is located in a geographic region of the State known as 

the Valley and Ridge region. The Valley and Ridge covers 7,703 square miles and is situated 

between the Cumberland Plateau to the west and the Unaka Mountains to the east. The width of 

the region averages 45miles in width, ranging from as much as 70 miles along the Kentucky 

border to as little as 30 miles near the Georgia State Line. Twenty-seven counties of Tennessee 

are partially or completely located within this region. The topography of the Valley and Ridge 

consists of long linear ridges and parallel lowland valleys that trend in a northeast to southwest 

direction. The ridges usually have high elevations of 1,100 to 1,500 feet, while the adjacent 

valley floors vary from 700 feet to 1,000 feet. The ridges and valleys generally have high 

elevations in the northern part of the region; they are slightly less elevated to the south. 
14 

Figure 2- 2: Tennessee Geographic Regions 

The Knoxville nonattainment region is shown in Figure 2- 3 with the area PM2.5 monitors 

identified with yellow stars. The shaded relief imagery shows that the major portion of the area 

lies in a valley, with the Blue Ridge Mountains to the southeast and the Cumberland Plateau to 

the northwest. 

Figure 2- 3: Shaded relief Imagery of Knoxville Nonattainment Area 

The general elevation of the Knoxville non-attainment region is shown in Figure 2- 4, with the 

local elevation for the Knox county area ranging from about 800 to 1,900 feet. 
15 

Figure 2- 4: Elevation of Knoxville PM2.5 Sites 

The topography has a pronounced effect upon the prevailing wind direction. The mountains 

serve to modify the hot summer winds that are common to the plains to the west. In addition, 

they serve as a fixed incline plane, which lifts the warm, moist air flowing northward from the 

Gulf of Mexico and thereby, increases the frequency of afternoon thunderstorms. Relief from 

extremely high temperatures that such thunderstorms produce serves to reduce the number of 

extremely warm days in the valley. Daytime winds typically have a southwesterly component, 

while nighttime winds usually move from the northeast (Figure 2- 5). These winds are relatively 

light, averaging 6.9 mph for the year. 

Figure 2- 5: Three-Year Wind Rose for Knoxville Region 
16 

8. Have there been any recent major changes in emissions of PM2.5 or its precursors in or 

near the nonattainment area? What? 

As discussed in Section 5.0, SO2 emissions in Tennessee and surrounding States decreased by 

about 12.7% in Tennessee and surrounding States between 2000 and 2006. This change is 

consistent with a gradual decline in emissions since the emission caps under the Acid Rain 

Program became effective. 

NOX emissions from electric utilities declined by 38.1% during the same period, but this decline 

is believed to have made no significant impact on PM2.5 concentrations. The decline in NOX

emissions may be attributed to NOX reductions that occurred primarily during the summer ozone 

season in 2003 and subsequent years. As discussed in Section 3.0, ambient PM2.5 concentrations 

in the Knoxville region are relatively insensitive to NOX emissions, and seasonal variations in 

PM2.5 concentrations vary inversely with seasonal nitrate levels. 

9. Are there discernible trends in design values or other air quality indicators which have 

accompanied a change in emissions? 

Monitoring data for the Knoxville area indicates that ambient PM2.5 concentrations declined 

significantly between 1999 and 2006 (Figure 2- 6). The more recently monitored concentrations 

(from about 2004 to 2006) do indicate some variation in the annual average PM2.5 concentration, 

including some year-to-year increases. These changes (increases and decreases) tend to be well 

correlated with State and regional SO2 emissions from electric utilities, suggesting a strong 

regional component to PM2.5 nonattainment in the Knoxville area. 

As indicated in Section 5.0, regional emissions of sulfur dioxide have declined significantly 

between 1999 and 2006. Comparison of ambient monitoring data for the Knoxville area with 

utility SO2 emissions data from the Acid Rain Program (Table 2- 6) strongly suggests a linear 

relationship between ambient PM2.5 levels and local, State, and regional SO2 emissions (Table 2- 

7, Figure 2- 7, Figure 2- 8). Due to the complex mixture of precursor pollutants in ambient 

PM2.5, these data should be interpreted with some caution. However, the relatively high degree 

of linearity in these analyses appears to support a conclusion that a continuing decline in State 

and regional SO2 emissions between 1999 and 2006 resulted in a noticeable change in PM2.5

concentrations at the ambient monitors. 

Table 2- 6: Acid Rain Program Emissions Data, Three-Year Averages 

3-Year Period

3-Year Avg. SO2 Emissions (tons) 

Bull Run Kingston 

Bull Run + 

Kingston TN Total Region Total 

1999-2001 40,461 98,812 139,274 409,516 5,626,491 

2000-2002 42,937 88,271 131,208 374,021 5,207,694 

2001-2003 45,530 86,616 132,146 345,542 5,079,362 

2002-2004 39,554 81,539 121,092 326,615 5,090,458 

2003-2005 36,863 74,418 111,281 302,977 5,116,526 

2004-2006 31,375 62,247 93,623 276,334 4,964,058 

Data Source: US EPA Clean Air Markets Data and Maps (http://camddataandmaps.epa.gov) 

Regional States are: Alabama, Georgia, Illinois, Indiana, Kentucky, North Carolina, Ohio, Tennessee, and West Virginia. 
17 

Knoxville PM 2.5 Trends 1999 2006

11

12

13

14

15

16

17

18

19

20

21

22

23

Annual

Avg

1999

Annual

Avg

2000

Annual

Avg

2001

Annual

Avg

2002

Annual

Avg

2003

Annual

Avg

2004

Annual

Avg

2005

Annual

Avg

2006

ug/m 3 PM 2.5

47-093- 0028-1 1000 Francis Ro ad

47-093-1013-1 1403 Davanna Street

47-093-1017-1 1613 Vermo nt A venue

47-093-1020-1 4625 M ildred Drive

Figure 2- 6: PM2.5 Trends for Knoxville (2000-2006) 
18 

Figure 2- 7: Scatter Plot of Ambient Monitored Data and Tennessee SO2 Emissions 

Figure 2- 8: Scatter Plot of Ambient Monitored Data and Regional SO2 Emissions 
19 

Table 2- 7: Linear Correlation Coefficients6

Metric 47-093-0028-1 47-093-1017-1* 47-093-1020-1 All Monitors 

Bull Run 0.266 0.396 0.493 0.360 

Bull Run 

(2001-2006 Only) 0.024 0.863 0.731 0.441 

Kingston 0.707 0.828 0.800 0.773 

Bull Run + Kingston 0.609 0.738 0.746 0.686 

TN Total 0.838 0.922 0.912 0.891 

Region Total 0.880 0.942 0.814 0.894 

Correlation coefficients are calculated for three-year averages of SO2 emissions and three-year average ambient PM2.5

concentrations. 

FRM Monitor 47-093-1013-1 (1403 Davanna Street) was not analyzed, since only four data points were available for this location.

* Controlling monitor. 

10. Is there any apparent spatial pattern to the trends in design values? 

See item 9. From about 2004 to 2006, annual PM2.5 concentrations were relatively stable, 

compared to the more significant decreases that were observed from 1999 to 2004. 

11. What past modeling has been performed and what do the results suggest? 

EPA performed air quality modeling on Knoxville and other nonattainment areas in support of 

the 2005 Clean Air Interstate Rule7. EPA’s CMAQ model results indicated that PM2.5

concentrations would decrease as CAIR controls were implemented, but that PM2.5

concentrations would still exceed the NAAQS in the absence of additional controls (Table 2- 8). 

The difference in CAIR modeling results and the model results presented in this document may 

be due to the emission inventories used8, the assumed mixture of EGU controls9, or other factors. 

Monitoring data for the Knoxville area suggests that CAIR modeling underestimated the positive 

impact of Acid Rain program or other reductions, since the Knoxville area design values for 

2004-2006 (see Table 1- 1) are already below those predicted for the 2010 CAIR scenario. 

Table 2- 8: CAIR Modeling Results – Projected PM2.5 Concentrations for Knox County 

Projected Annual PM2.5 Concentration 

(μg/m3) 

2010 Base Case 17.44 

2010 with CAIR 16.16 

2015 Base Case 17.34 

2015 with CAIR 15.61 

 

6 Scatter plots for all metrics are available in Appendix E. 

7 For further discussion of CAIR modeling, see Federal Register / Vol. 70, No. 91 / Thursday, May 12, 2005 / Rules and Regulations, pages 

25233 – 25255. 

8 The CAIR rulemaking states that EPA used a 2001 base year emissions inventory to estimate future-year emissions for 2010 and 2015 (see 

Note 7, page 25237), while 2002 was used as a baseline year for ASIP modeling. 

9See Note 17 for additional discussion of ASIP’s development of 2009 EGU emission inventories and adjustments to Integrated Planning Model 

(IPM) results. 
20 

12. Are there any distinctive meteorological measurements at the surface or aloft which 

appear to coincide with occasions with PM2.5 concentrations in excess of 15.0 μg/m3

? 

Recent elevated PM2.5 data was analyzed to compare monitoring data with area surface wind 

patterns that were observed to occur during the sampling periods. From 2002 to 2006, there 

were 25 days in which ambient PM2.5 concentrations were 35 μg/m3

 or greater. The events were 

noted to have occurred during or very close to the third quarter of the year. Nine of the days 

evaluated occurred during 2005, the year with the largest number of event days in the dataset. 

Several days in 2005 with elevated PM2.5 were selected to evaluate the winds patterns present 

(Figure 2- 9). The wind roses developed for these selected dates with elevated levels of PM2.5

are consistent with the general wind patterns noted to occur in this region and do not generally 

reflect distinctive differences from other sampling days. 

Sampling 

Date

PM2.5 

FRM Avg.

7/2/2002 36.5

7/17/2002 45

8/10/2002 39.4

8/11/2002 41.4

8/12/2002 42

8/13/2002 38.2

6/26/2003 41.9

7/20/2003 37.8

8/20/2003 35.7

8/26/2003 44.2

8/27/2003 50

8/28/2003 40.1

7/22/2004 40.3

8/3/2004 35.5

6/22/2005 38.2

6/23/2005 35.1

6/25/2005 39.3

8/4/2005 36.4

8/11/2005 35.6

9/11/2005 35.9

9/12/2005 37.4

9/13/2005 35.5

9/14/2005 39.8

7/4/2006 46.9

8/18/2006 40.7

June 21 through June 26, 2005 Knoxville McGhee

Aug.  2 through Aug. 5, 2005 Knoxville McGhee

Figure 2- 9: Wind Rose Analysis for High PM2.5 Days 
21 

13. Do periods with high measured particulate matter or components of particulate matter 

appear to track each other or any other measured pollutant? 

Measured PM2.5 concentrations follow the same general trends as ozone concentrations. 

Ambient levels of ozone and PM2.5 tend to be highest in the summer months (Figure 2- 10), 

when the hot, stagnant conditions are conducive to accumulation of sulfate, as well as 

photochemical formation of ozone. Analysis of high ozone days (ambient ozone 0.080 ppm or 

higher) supports the general trend, and we find that daily average PM2.5 concentrations also tend 

to be high (20-40 μg/m3

 – Figure 2- 11). 

Comparison of individual speciated components at FRM Monitor 47-093-1020 shows the same 

trend (Figure 2- 12). Ambient PM2.5 concentrations track more strongly with sulfate than with 

any other precursor, although some correlation with nitrate and ammonia levels may occur 

during the winter months (Figure 2- 13). 

Comparisons of PM2.5 and Ozone In the Knoxville NAA

0

10

20

30

40

50

60

2/28/2002

5/29/2002

8/27/2002

11/25/2002

2/23/2003

5/24/2003

8/22/2003

11/20/2003

2/18/2004

5/18/2004

8/16/2004

11/14/2004

2/12/2005

5/13/2005

8/11/2005

11/9/2005

2/7/2006

5/8/2006

8/6/2006

Max Daily PM 2.5 ug/m 3

0

0.02

0.04

0.06

0.08

0.1

0.12

Max Daily Ozone 8 Hour PPM 

PM 2.5 VALUE

8 Hour Ozone PPM

Figure 2- 10: General Trends of Ambient PM2.5 and Ozone, Knoxville, Tennessee 
22 

Comparisons of PM2.5 and Ozone In the Knoxville NAA

(Ozone Days >=0.080 PPM)

0

10

20

30

40

50

60

5/24/2002

6/3/2002

6/12/2002

6/20/2002

7/8/2002

7/23/2002

8/4/2002

8/10/2002

8/13/2002

8/23/2002

9/7/2002

6/24/2003

7/18/2003

8/26/2003

7/21/2004

5/12/2005

5/19/2005

7/24/2005

8/12/2005

9/21/2005

7/3/2006

7/20/2006

8/1/2006

Max Daily PM 2.5 ug/m 3

0

0.02

0.04

0.06

0.08

0.1

0.12

Max Daily Ozone 8 Hour PPM 

PM 2.5 VALUE

8 Hour Ozone PPM

Figure 2- 11: Comparison of Ambient PM2.5 and Ozone, Knoxville, Tennessee 

High Ozone Days (>= 0.080 ppm) 
23 

Knoxville Region Speciated Components Comparison

05

1015202530354045

7/7/2002

10/7/2002

1/7/2003

4/7/2003

7/7/2003

10/7/2003

1/7/2004

4/7/2004

7/7/2004

10/7/2004

1/7/2005

4/7/2005

7/7/2005

10/7/2005

1/7/2006

4/7/2006

7/7/2006

10/7/2006

u

g /m 3

PM2.5 Mass Collocated FRM 470931020 SULFATE

Knoxville Region Speciated Components Comparison

05

1015202530354045

7/7/2002

10/7/2002

1/7/2003

4/7/2003

7/7/2003

10/7/2003

1/7/2004

4/7/2004

7/7/2004

10/7/2004

1/7/2005

4/7/2005

7/7/2005

10/7/2005

1/7/2006

4/7/2006

7/7/2006

10/7/2006

ug/m 3

PM2.5 Mass Collocated FRM 470931020 NITRATE

Knoxville Region Speciated Components Comparison

05

1015202530354045

7/7/2002

10/7/2002

1/7/2003

4/7/2003

7/7/2003

10/7/2003

1/7/2004

4/7/2004

7/7/2004

10/7/2004

1/7/2005

4/7/2005

7/7/2005

10/7/2005

1/7/2006

ug/m3

PM2.5 Mass Collocated FAMMONIUM

Knoxville Region Speciated Components Compariso

05

1015202530354045

7/7/2002

10/7/2002

1/7/2003

4/7/2003

7/7/2003

10/7/2003

1/7/2004

4/7/2004

7/7/2004

10/7/2004

1/7/2005

4/7/2005

7/7/2005

10/7/2005

1/7/2006

ug/m3

PM2.5 Mass Collocated Organic Carbon Mass (kElemental Carbon

Figure 2- 12: Comparison of PM2.5 Speciated Components, FRM Monitor 47-093-102
24 

Knoxville Region Speciated Components Comparison

05

10152025

October 2002 2006

ug/m3

PM2.5 Mass Collocated FRM 470931020 AMMONIUMNITRATESULFATE

Knoxville Region Speciated Components Comparison

02468

101214161820

November 2002 2006

ug/m 3

PM2.5 Mass Collocated FRM 470931020 AMMONIUMNITRATESULFATE

Knoxville Region Specia

05

10152025

Dece

ug/m 3

PM2.5 Mass AMMONIUMNITRATESULFATE

Knoxville Region Speciated Components Comparison

02468

101214161820

January 2002 2006

ug/m3

PM2.5 Mass Collocated FRM 470931020 AMMONIUMNITRATESULFATE

Knoxville Region Speciated Components Comparison

05

1015202530

February 2002 2006

ug/m 3

PM2.5 Mass Collocated FRM 470931020 AMMONIUMNITRATESULFATE

Knoxville Region Speciate

02468

101214161820

Marc

ug/m 3

PM2.5 Mass CoAMMONIUMNITRATESULFATE

Figure 2- 13: Comparison of PM2.5 Speciated Components (Winter Months Only), FRM Monitor 
25 

3.0 NOX INSIGNIFICANCE10

As indicated in Section 1.0, the PM2.5 Implementation Rule requires States to address NOX as a 

PM2.5 attainment plan precursor and evaluate sources of NOX emissions in the State for control 

measures, unless the State and EPA provide an appropriate technical demonstration for a specific 

area showing that NOX emissions from sources in the State do not significantly contribute to 

PM2.5 concentrations in the nonattainment area11. As indicated in the following paragraphs, 

Tennessee believes that NOX emissions do not significantly contribute to PM2.5 concentrations in 

the Knoxville nonattainment area. 

3.1. Significance of Precursors Contributing to Fine Particulate Matter 

The United States Environmental Protection Agency (EPA) revised the National Ambient Air 

Quality Standards (NAAQS) for particulate matter in 1997 establishing fine particulates 

(particulate matter with aerodynamic diameter ≤ 2.5 micrometers or PM2.5) as a benchmark. The 

revised NAAQS for particulate matter set a daily standard of 65 μg/m3 and an annual standard of 

15.0 μg/m3

. The daily PM2.5 standard was more recently revised in 2006 by lowering it to 35 

μg/m3 based on a review of the air quality criteria and the NAAQS, but the annual PM2.5

standard was retained at 15.0 μg/m3. Both of these revisions to the NAAQS for particulate 

matter are published in 40 CFR 50.7 and 40 CFR 50, Appendix N. 

Areas designated as “nonattainment” for fine particulate matter by the USEPA must submit 

formal implementation plans detailing how attainment will be met as outlined in the Clean Air 

Act (CAA). These implementation plans must outline the measures that will be taken to curtail 

the concentrations of various pollutants that are assumed to have significant contributions to 

nonattainment for fine particulate matter, including sulfur dioxide (SO2), nitrogen oxides (NOX), 

and primary PM2.5. 

EPA, in 72 FR 20586, requires states to “evaluate and consider control strategies for sources of 

SO2, direct PM2.5, and NOX emissions in all nonattainment areas.” However, the rule does allow 

States to make technical demonstrations to reverse the inclusion of NOX as precursor of PM2.5, or 

deem the precursor insignificant, based on geographical regions, emissions, etc. This eliminates 

the need to examine NOX control measures for purposes of reducing PM2.5 concentrations. 

The two remaining precursor species that contribute PM2.5, ammonia (NH3) and volatile organic 

carbons (VOCs) have been deemed as insignificant contributors to the total mass of PM2.5 by the 

USEPA. With regards to NH3, 72 FR 20586 states NH3 “is presumed not to be a PM2.5

attainment plan precursor, meaning that the State is not required to address [NH3] in its 

attainment plan or evaluate sources of [NH3] emissions for reduction measures.” Likewise, the 

 

10 This section was adapted from NOX Insignificance Demonstration, Knoxville, TN PM2.5 Nonattainment Area. Pat Brewer, January 2008. 

11 The preamble to the implementation rule states: “Demonstrations to reverse the presumptions for ammonia, VOC, or NOX are to be based on 

the weight of evidence of available information, and any demonstration by the State must be approved by EPA. The State must demonstrate that 

based on the sum of available technical and scientific information, it would be appropriate for a nonattainment area to reverse the presumptive 

approach for a particular precursor. The demonstration should include information from multiple sources, including results of speciation data 

analyses, air quality modeling studies, chemical tracer studies, emission inventories, or special intensive measurement studies to evaluate specific 

atmospheric chemistry in an area.” [Federal Register / Vol. 72, No. 79 / Wednesday, April 25, 2007 / Rules and Regulations 20596-20597]
26 

final rule for VOCs states that “States are not required to address VOC in PM2.5 implementation 

plans and evaluate control measures for such pollutants unless the State or EPA makes a 

technical demonstration that emissions of VOCs from sources in the State significantly 

contribute to PM2.5 concentrations in a given nonattainment area.” 

The State of Tennessee agrees with EPA’s presumptive exclusion of NH3 and VOC with regards 

to the PM2.5 implementation plan. Therefore, emission controls for NH3 and VOC are not 

considered as a part of Tennessee’s PM2.5 attainment demonstration plan. 

3.2. Determination of NOX Insignificance 

NOX is assumed to be precursor for PM2.5 unless the state can demonstrate that NOX is not a 

significant contributor to PM2.5 attainment. The USEPA has provided suggested guidelines for 

producing the technical demonstrations necessary to determine the significance of a pollutant 

towards attaining the PM2.5 standard. These suggested analyses include: 

1. Emission Inventories 

2. Monitoring or Data Analysis 

3. Speciation Information 

4. Modeling Information 

This document presents Tennessee’s analyses demonstrating that NOX is insignificant to PM2.5

attainment in the Knoxville, TN nonattainment area. Data are included that address each of the 

four categories of evidence that the EPA suggests be included in the demonstration. 

3.3. Elements of NOX Insignificance Demonstration 

The NOX insignificance demonstration includes the following elements: 

• Annual emissions inventories for 2002 and 2009 are presented by source category for 

each county in the Knoxville nonattainment area and for the State total. NOX emissions 

in the Knoxville nonattainment area are projected to decrease by 58% between 2002 and 

2009. 

• An analysis of total PM2.5 mass is provided for the Federal Reference Method (FRM) 

monitors in the Knoxville, TN PM2.5 nonattainment areas. These data are presented as 

both quarterly and annual averages and indicate that the Knoxville area is already 

demonstrating PM2.5 values that attain the annual standard of 15 μg/m3

. 

• An analysis is provided of speciated data available from the Speciated Trends Network 

(STN) monitor in Knoxville, TN. These data demonstrate that NO3 is an extremely small 

component of total PM2.5. 

• Results of the SANDWICH method (measured Sulfate, Adjusted Nitrate, Derived Water, 

Inferred Carbonaceous mass Hybrid Material Balance Approach) to speciate the PM2.5

mass for the FRM monitors in the Knoxville nonattainment area demonstrate that NO3
27 

and associated ammonium and particle bound water account for less than 2% of the total 

PM2.5. 

• The Speciated Modeled Attainment Test (SMAT) method is applied to 2009 modeling 

results to project the change in speciated PM2.5 mass for the FRM monitors as a result of 

emissions changes between 2002 and 2009. The speciated modeling results project that 

the Knoxville nonattainment area will attain the annual PM2.5 standard in 2009 and 

demonstrate that NO3 will be an insignificant contribution to PM2.5 in the Knoxville area 

in 2009. 

• The results from 2009 sensitivity modeling runs are presented to further demonstrate the 

insignificance of NOX emissions to PM2.5 attainment in the Knoxville, TN nonattainment 

area. 

3.4. NOX Emissions Source Categories 

Table 3- 1, Table 3- 2, and Table 3- 3 outline NOX emissions by source category for each of the 

counties in the Knoxville PM2.5 nonattainment area and for Tennessee as a whole. The tables 

provide ASIP Base G2 2002 actual emissions and 2009 emission projections. The 2009 

projections take into account implementation of emissions controls to meet existing and 

proposed regulations. 

In 2002 point sources in Anderson and Roane Counties dominate NOX emissions in the 

Knoxville nonattainment area. Coal-fired power plants in these two counties installed NOX

controls under the NOX SIP call and as demonstrated in Table 3- 2, by 2009 NOX emissions from 

point sources in the Knoxville nonattainment area will be reduced by 78% (37,500 tons). 

Onroad mobile emissions are highest in urban Knox County. Between 2002 and 2009, NOX

emissions from onroad mobile in the Knoxville nonattainment area are projected to decrease by 

39% (11,500 tons) due to EPA rules for cleaner fuels and cleaner engines. NOX emissions from 

nonroad engines are projected to decrease by 11% (900 tons) between 2002 and 2009 while NOX

emissions from area sources are projected to increase slightly (50 tons). The cumulative NOX

emissions reductions for the Knoxville nonattainment area between 2002 and 2009 is 58% 

(50,000 tons). These reductions support the demonstration that NOX emissions will continue to 

be an insignificant contribution to the PM2.5 nonattainment issues in the Knoxville nonattainment 

area. 
28 

Table 3- 1: 2002 Actual NOX Emissions for Counties in Knoxville, TN PM2.5

Nonattainment Area 

County Point Onroad Nonroad Area Total

Anderson 17,253 3,267 1,128 252 21,900

Blount 387 2,720 1,301 164 4,572

Knox 2,183 19,059 4,845 175 26,262

Loudon 2,309 4,273 1,231 57 7,869

Roane* 25,679 235 17 2 25,933

Total 47,811 29,555 8,521 650 86,536

2002 NOx Emissions, annual tons per year

Roane County emissions are for a partial county including point source emissions for Kingston Steam plant 

and onroad, nonroad, and area emissions for Kingston census track only.

Table 3- 2: 2009 NOX Emissions for Counties in Knoxville, TN PM2.5 Nonattainment Area 

County Point Onroad Nonroad Area Total

Anderson 3,178 2,168 921 259 6,525

Blount 421 1,964 1,149 168 3,702

Knox 2,204 11,042 4,377 208 17,831

Loudon 1,321 2,633 1,101 59 5,115

Roane* 3,238 137 16 2 3,393

Total 10,362 17,945 7,563 696 36,567

2009 NOx Emissions, annual tons per year

Roane County emissions are for a partial county including point source emissions for Kingston Steam plant 

and onroad, nonroad, and area emissions for Kingston census track only.

Tennessee Statewide total NOX emissions demonstrate similar decreasing trends between 2002 

and 2009 (Table 3- 3). Statewide NOX emissions are projected to be reduced 33% between 2002 

and 2009. Point source reductions between 2002 and 2009 are larger in the Knoxville 

nonattainment area than statewide because the two coal-fired power plants are located in the 

Knoxville nonattainment area installed NOX controls between 2002 and 2009. Point source NOX

emissions are projected to be reduced by 43% statewide. Changes for onroad, nonroad, and area 

source NOX emissions between 2002 and 2009 are similar in the Knoxville nonattainment area 

and statewide. 

Table 3- 3: Tennessee NOX Emissions in 2002 and 2009 

TN NOX emissions tons per year 

Point Onroad Nonroad Area Total 

2002 216,481 238,577 96,827 17,831 571,719 

2009 124,289 151,912 86,641 18,485 383,336 
29 

3.5. Federal Reference Method Observations

The Federal Reference Method (FRM) PM2.5 monitors provide a record of PM2.5 concentrations 

in the Knoxville, TN area since 2000. Figure 3- 1 shows annual average PM2.5 at the three FRM 

monitors located in Knox County from 2000 through 2006. 

Annual average PM2.5 decreased from 2000 to 2004 and then has been level or increased slightly. 

In 2006 PM2.5 was at or slightly above the annual standard of 15 μg/m3. Trends for the FRM 

monitors in Blount and Roane Counties show similar downward trends. Both these monitors 

currently attain the annual PM2.5 standard. 

FRM Annual Average Fine Particle Mass - Knoxville, TN

0

5

10

15

20

25

1999 2000 2001 2002 2003 2004 2005 2006

Fine Particle Mass 

μ g/m3

47-093-0028

47-093-1017

47-093-1020

Figure 3- 1: Annual Average PM2.5 from 2000-2006 at Three Federal Reference Method 

Monitors in Knox County, TN 

Quarterly and annual average PM2.5 concentrations for 2000 through 2006 from the Federal 

Reference Method (FRM) monitors in Knox County, TN are illustrated in Figure 3- 2; data from 

FRM monitors in neighboring counties in the Knoxville nonattainment area are illustrated in 

Figure 3- 3. Trends are very similar at the 6 monitors. PM2.5 mass is highest in the summer 

months. Quarterly averages are higher in 2000 and 2001 than in more recent years, a trend that 

appears at several other monitoring sites in the southeastern US. Higher values may be due to a 

combination of higher emissions, meteorological conditions in those years, and/or initial 

problems with instrument deployment and calibration. Several forest fires in TN, NC, and KY in 

November 2000 likely contributed to the relative high average PM2.5 for the fourth quarter of 

2000. After 2000, highest quarterly values are in the third, summer, quarter and lowest values are 

in the first and fourth quarters. By 2004, annual average PM2.5 at all sites meets or is slightly 

above the annual standard of 15 μg/m3

. 
30 

Two additional FRM monitors sited in the Knoxville, TN PM2.5 nonattainment area, Knox 

County monitor 47-093-1013 and Loudon County monitor 47-105-0108, have incomplete data 

for the 2000-2004 baseline period that do not meet EPA criteria for 12 complete quarters of data. 

These monitors are not included in this NOX insignificance analysis but review of available data 

indicates that trends are represented by results for the reported monitors. 
31 

Figure 3- 2: Quarterly and Annual Average PM2.5 in 2000 through 2006 from Federal 

Reference Method Monitors in Knox County, TN PM2.5 Nonattainment Area

Knoxville/Knox County (Bearden Middle School), TN (47-093-0028)

FRM Mass

0

5

10

15

20

25

30

1234 1234 1234 1234 1234 1234 1234 1234

1999 2000 2001 2002 2003 2004 2005 2006

PM2.5 (μg/m3)

Quarterly Averages Annual Average

Knoxville/Knox County (Rule High School), TN (47-093-1017)

FRM Mass

0

5

10

15

20

25

30

1234 1234 1234 1234 1234 1234 1234 1234

1999 2000 2001 2002 2003 2004 2005 2006

PM2.5 (μg/m3)

Quarterly Averages Annual Average

Knoxville/Knox County (Spring Hill Elem. School), TN (47-093-1020)

FRM Mass

0

5

10

15

20

25

30

1234 1234 1234 1234 1234 1234 1234 1234

1999 2000 2001 2002 2003 2004 2005 2006

PM2.5 (μg/m3)

Quarterly Averages Annual Average
32 

 

Figure 3- 3: Quarterly and Annual Average PM2.5 in 2000 through 2006 from Federal 

Reference Method Monitors for Counties in the Knoxville, TN PM2.5 Nonattainment Area

Maryville/Blount County, TN (47-009-0011)

FRM Mass

0

5

10

15

20

25

30

1234 1234 1234 1234 1234 1234 1234 1234

1999 2000 2001 2002 2003 2004 2005 2006

PM2.5 (μg/m 3

)

Quarterly Averages Annual Average

Loudon/Loudon County, TN (47-105-0108)

FRM Mass

0

5

10

15

20

25

30

1234 1234 1234 1234 1234 1234 1234 1234

1999 2000 2001 2002 2003 2004 2005 2006

PM2.5 (μg/m3)

Quarterly Averages Annual Average

Harriman/Roane County, TN (47-145-0004)

FRM Mass

0

5

10

15

20

25

30

1234 1234 1234 1234 1234 1234 1234 1234

1999 2000 2001 2002 2003 2004 2005 2006

PM2.5 (μg/m 3

)

Quarterly Averages Annual Average
33 

3.6. Speciated Trends Network Observations 

There is only one Speciated Trend Network (STN) monitor in the Knoxville nonattainment area 

and this monitor is collocated at Spring Hill Elementary School with a FRM monitor (47-093-

1020). Quarterly average speciated mass values for the STN monitor are illustrated in Figure 3- 

4. 

Knoxville, TN (47-093-1020)

Annual Average and Quarterly Speciated PM2.5 Mass

0

5

10

15

20

25

12341234123412341234

2002 2003 2004 2005 2006

STN Mass (μg/m3)

Soil

LAC

POM

NO3

NH4

SO4

Ann. Avg.

Figure 3- 4: Quarterly and Annual Average Speciated PM2.5 Mass from Speciated Trend 

Network (STN) Monitor for 2002 through 2006 at Spring Hill Elementary School in 

Knoxville, TN (47-093-1020). 

PM2.5 observations are separated into several components: sulfate (SO4), nitrate (NO3), 

ammonium (NH4), particulate organic matter (POM), elemental carbon (EC), and crustal 

materials. Data recovery for the STN monitor is spotty in 2002 through 2004 but improves by 

2005 and 2006. Sulfate (SO4) and particulate organic matter (POM) are the dominant 

contributors to PM2.5 mass in the Knoxville area. Sulfur dioxide (SO2) emissions, primarily from 

utility and industrial point sources, are the primary contributor to SO4. SO4 mass is highest in 

the summer months, in part due to higher SO2 emissions in the summer months and in part due to 

more active secondary photochemical formation during the higher temperatures, relative 

humidity, and oxidant loading of the summer months. Particulate organic matter concentrations 

are similar across all quarters although carbon analytical studies indicate greater contributions 

from primary carbon (combustion of fossil fuels, biomass burning, vegetative detritus, and 

cooking) in the winter months and greater contributions from secondary organic aerosol (from 

biogenic and anthropogenic emissions) during the summer months. 

Ammonium (NH4) and nitrate (NO3) have comparable contributions in the winter quarters while 

NO3 is very small in the spring and summer (second and third quarters). Higher amounts of NO3

are present in the cooler months, with very low concentrations in the summer months. 

Ammonium nitrate (NH4NO3) formation is a temperature-limited process with particle formation 

favored at lower temperatures. At higher temperatures nitrogen oxides remain in gaseous form as 

nitric acid. Through the year, NO3 makes up only a small fraction of total PM2.5 mass, 

insignificant to the total PM2.5 mass and attainment issues. The EC and crustal components of 

PM2.5 are generally very small and are also insignificant portions of the total PM2.5 mass. 
34 

Note that quarterly and annual average PM2.5 mass values are lower for the STN monitor (Figure 

3- 3) than the collocated FRM monitor (Figure 3- 2). Several factors contribute to these results 

including differences in sampling frequency (1 in 6 days for STN, 1 in 3 days for FRM), sample 

filter collection, and analytical methods. 

3.7. Speciated PM2.5 for Federal Reference Method Monitors 

To make observations of PM2.5 between the different monitoring networks comparable, the 

USEPA derived a method that allows observations from STN monitors to be converted to a 

format that is similar to FRM observations. The “Sulfate, Adjusted Nitrate, Derived Water, 

Inferred Carbonaceous mass Hybrid Material Balance Approach” or SANDWICH is a method 

which resolves differences between STN and FRM total PM2.5 mass. Since STN monitors are 

not co-located with all FRM monitors, EPA allows States to use spatial interpolation of speciated 

data. More information on the interpolation method used by ASIP is provided in Attachment G, 

and in the EPA documentation for the Clean Air Interstate Rule. EPA developed procedures to 

apply the SANDWICH method to calculate speciated 2002 baseline design values for the FRM 

mass measurements and provided an initial spreadsheet with the SANDWICH calculations used 

for the Clean Air Interstate Rule to the North Carolina Division of Air Quality. 

Quarterly and annual average 2002 baseline design values (DVB) for the Knoxville, TN, Spring 

Hill Elementary School FRM monitor (47-093-1020), based on PM2.5 data for 2000-2004 and 

applying the EPA SANDWICH spreadsheet used for the Clean Air Interstate Rule, are illustrated 

in Figure 3- 5. In addition to the STN monitor in Knoxville, TN, a STN monitor in Hamilton 

County TN and an IMPROVE monitor in Blount County (Great Smoky Mountains National 

Park) were available for spatial interpolation of speciated data. 

Table 3- 4 provides the quarterly and annual average speciated PM2.5 2002 baseline design 

values (DVB) for six FRM monitors in the Knoxville, TN nonattainment area. The 2002 DVB 

for the three monitors in Knox County exceed the annual standard for PM2.5; the 2002 DVB for 

the two monitors in neighboring Blount and Roane County attain the standard. 

Consistent with the STN data, Organic Carbon (OC) and SO4 make up the most significant 

portion of the speciated PM2.5 mass at all sites. The derived concentrations for NH4, elemental 

carbon (EC), crustal materials, and particle bound water (PBW) are greater than the derived 

concentration for NO3. The contribution of NO3 to total PM2.5 is only a small fraction during the 

cold months, mostly in the fourth quarter. 
35 

Quarterly and Annual Average PM2.5 Design Value

0

5

10

15

20

25

 Qrt 1 Qrt 2 Qrt 3 Qrt 4 Ann Ave

PM2.5 mass (μg/m3)

PBW

Crustal

EC

OC

NO3

NH4

SO4

Figure 3- 5: Quarterly and Annual Average 2002 Base Design Values (DVB) Calculated 

Using the SANDWICH Method and the 2000-2004 PM2.5 Data for the Spring Hill 

Elementary School FRM monitor (47-093-1020) in Knoxville, TN 

Table 3- 4: Quarterly and Annual Average 2002 Base Design Values (DVB) for the FRM 

Monitors in the Knoxville, TN PM2.5 Nonattainment Area 

AIRS ID County Quarter

FRM 

Mass

Blank 

Mass

Blank

Corrected 

Mass Crustal EC OC SO4 NO3 NH4 PBW

NO3 + 

NH4 + 

PBW

1 12.99 0.50 12.49 0.24 0.48 6.97 2.61 0.16 0.80 0.73 0.26

2 15.73 0.50 15.23 0.66 0.44 6.19 4.71 0.01 1.37 1.34 0.02

3 19.04 0.50 18.54 0.69 0.41 5.65 7.40 0.01 2.02 1.85 0.01

4 12.65 0.50 12.15 0.31 0.52 5.57 3.23 0.24 0.95 0.84 0.37

Ann 14.61 0.50 14.11 0.48 0.46 6.10 4.49 0.11 1.29 1.19 0.16

1 14.00 0.50 13.50 0.22 0.44 8.34 2.42 0.15 0.74 0.68 0.24

2 16.36 0.50 15.86 0.68 0.45 6.66 4.80 0.01 1.40 1.36 0.02

3 19.54 0.50 19.04 0.71 0.42 5.91 7.54 0.01 2.06 1.89 0.01

4 13.62 0.50 13.12 0.29 0.49 6.86 3.06 0.22 0.90 0.79 0.35

Ann 15.35 0.50 14.85 0.47 0.45 6.94 4.45 0.10 1.28 1.18 0.15

1 14.87 0.50 14.37 0.23 0.46 9.09 2.49 0.16 0.76 0.70 0.25

2 17.02 0.50 16.52 0.67 0.45 7.37 4.77 0.01 1.39 1.35 0.02

3 21.57 0.50 21.07 0.70 0.42 8.00 7.50 0.01 2.05 1.88 0.01

4 15.14 0.50 14.74 0.32 0.53 7.94 3.35 0.25 0.99 0.87 0.38

Ann 16.67 0.50 16.17 0.48 0.46 8.10 4.53 0.11 1.30 1.20 0.16

1 14.08 0.50 13.58 0.27 0.61 7.74 2.67 0.23 0.83 0.74 0.36

2 16.60 0.50 16.10 0.63 0.51 6.95 4.73 0.01 1.40 1.37 0.02

3 20.84 0.50 20.34 0.58 0.46 7.94 7.12 0.01 1.95 1.79 0.01

4 14.40 0.50 13.90 0.29 0.71 6.52 3.49 0.42 1.07 0.89 0.66

Ann 15.98 0.50 15.48 0.44 0.57 7.29 4.50 0.17 1.31 1.20 0.26

1 12.31 0.50 11.81 0.27 0.54 5.62 2.83 0.35 0.92 0.78 0.56

2 15.09 0.50 14.59 0.78 0.48 5.40 4.65 0.01 1.39 1.37 0.02

3 19.19 0.50 18.69 0.95 0.50 4.66 7.80 0.01 2.20 2.08 0.02

4 12.69 0.50 12.19 0.38 0.61 4.36 3.72 0.43 1.18 1.01 0.68

Ann 14.32 0.50 13.82 0.60 0.53 5.01 4.75 0.20 1.42 1.31 0.32

47-093-1017 Knox

47-093-1020 Knox

47-093-0028 Knox

47-009-0011 Blount

47-145-0004 Roane
36 

The annual average NO3 mass for the 2002 base design value (DVB) varies from 0.11 to 0.20 

μg/m3

 across the five FRM monitors in the Knoxville, TN PM2.5 nonattainment area. Including 

ammonium (NH4) and particle bound water (PBW) associated with nitrate, the total contribution 

of NH4NO3 to PM2.5 ranges from 0.16 to 0.32 μg/m3

. NO3 plus associated NH4 and particle 

bound water contributes 0.9 to 2.2% of total PM2.5 mass for the 2002 DVB for the five FRM 

monitors in the Knoxville, TN PM2.5 nonattainment area. 

3.8. Speciated Modeled Attainment Test 

Another technical demonstration that is useful in determining NOX significance to PM2.5

attainment is the Speciated Modeled Attainment Test (SMAT). This test allows states to examine 

whether modeled current or proposed controls will bring nonattainment areas into attainment 

while also allowing the examination of the reductions in the individual species of PM2.5. A 

detailed explanation of this test is given in Attachment G. 

2002 and 2009 emissions from the ASIP Base G2 inventory were applied with 2002 

meteorological model outputs in the Community Multi-scale Air Quality (CMAQ) model version 

4.5. Figure 3- 6 illustrates modeling results for 2002 baseline design values (DVB) and 2009 

future design values (DVF) for the FRM monitors in the Knoxville nonattainment area. The bar 

on the left is 2002 DVB, the bar in the middle is 2009 DVF for the 36 km modeling domain and 

the bar on the right is the 2009 DVF for the 12 km modeling domain. Note that the model results 

are essentially the same whether the 12 or 36 km domains are used. The annual average 2002 

DVB and 2009 DVF projected using the 12 km modeling domain are listed by species in Table 

3- 5. 
37 

0

2

4

6

8

10

12

14

16

18

Blount-0011

Knox-0028

Knox-1013Knox-1017Knox-1020

Roane-0004

PM2.5 mass -

μ g/m3

PBW

NH4

Crustal

EC

OC

NO3

SO4

2002 DVB – Left Bar 2009 DVF:12 km – Middle Bar 2009 DVF:36 km – Right Bar

0

2

4

6

8

10

12

14

16

18

Blount-0011

Knox-0028

Knox-1013Knox-1017Knox-1020

Roane-0004

PM2.5 mass -

μ g/m3

PBW

NH4

Crustal

EC

OC

NO3

SO4

0

2

4

6

8

10

12

14

16

18

Blount-0011

Knox-0028

Knox-1013Knox-1017Knox-1020

Roane-0004

PM2.5 mass -

μ g/m3

PBW

NH4

Crustal

EC

OC

NO3

SO4

PBW

NH4

Crustal

EC

OC

NO3

SO4

2002 DVB – Left Bar 2009 DVF:12 km – Middle Bar 2009 DVF:36 km – Right Bar

Figure 3- 6: Annual Average PM2.5 2002 Base Design Values (DVB) and 2009 Future 

Design Values (DVF) for the FRM Monitors in the Knoxville, TN Nonattainment Area

Table 3- 5: Annual Average Speciated 2002 DVB and 2009 DVF for FRM Monitors in the 

Knoxville, TN Nonattainment Area 

Crustal EC OC SO4 NO3 NH4 PBW PM2.5

2002 0.49 0.48 6.32 4.64 0.11 1.33 1.23 14.60

2009 0.51 0.39 6.11 3.56 0.11 1.03 0.95 12.66

2002 0.49 0.47 7.19 4.60 0.10 1.32 1.22 15.38

2009 0.52 0.36 6.96 3.51 0.10 1.02 0.94 13.41

2002 0.46 0.59 7.53 4.66 0.16 1.36 1.24 16.00

2009 0.49 0.44 7.26 3.56 0.16 1.05 0.96 13.93

2002 0.50 0.48 8.36 4.66 0.11 1.34 1.23 16.67

2009 0.52 0.37 8.06 3.56 0.11 1.03 0.95 14.60

2002 0.46 0.59 7.53 4.64 0.17 1.35 1.24 15.98

2009 0.49 0.44 7.25 3.55 0.17 1.05 0.96 13.92

2002 0.62 0.56 5.20 4.91 0.21 1.47 1.35 14.32

2009 0.70 0.46 5.05 3.86 0.22 1.17 1.07 12.53

47-093-1020 Knox

47-145-0004 Roane

47-093-1017 Knox

47-093-1013 Knox

47-009-0011 Blount

47-093-0028 Knox

 

All monitors in the Knoxville nonattainment area are projected to meet the annual PM2.5 standard 

by 2009. The highest monitor, 47-093-1017, at Rule High School is projected to decrease from 

16.67 in 2002 DVB to 14.60 μg/m3

 for 2009 DVF. The major changes in PM2.5 are due to 

reductions in SO4 and associated NH4 and PBW. 

The annual average concentration of NO3 for each monitor does not change between 2002 and 
38 

2009. Spatially NO3 varies between 0.11 and 0.22 μg/m3 in 2009, the same concentrations as in 

2002. The contribution of NO3 plus associated NH4 and PBW also remains unchanged at each 

monitor between 2002 and 2009. Spatially NO3 with associated NH4 and PBW ranges from 0.17 

to 0.34 μg/m3

. These values are an insignificant contribution to total PM2.5 mass. The 

contribution of NO3 with associated NH4 and PBW is 1.2-2.7% of total PM2.5 in 2009; still an 

insignificant contribution to total PM2.5 in the Knoxville nonattainment area. 

3.9. NOX Sensitivity Modeling 

A final technical demonstration for insignificance is to assess the effects of reducing 2009 NOX

emissions on PM2.5 mass. CMAQ was run assuming 100% reduction in NOX emissions from all 

source categories in Tennessee and again assuming 70% reduction in NOX emissions from all 

sources in Tennessee. These runs were performed for Tennessee by the North Carolina Division 

of Air Quality using the ASIP Base G2 2009 CMAQ modeling files and configuration. 

CMAQ was applied using 36-km horizontal grid spacing. A 36-km grid resolution rather than a 

12-km grid resolution was used to allow more efficient use of modeling resources and more 

timely delivery of modeling results. As illustrated in Figure 3- 6, the 2009 model DVFs for the 

Knoxville nonattainment area were not affected by the grid resolution (12 vs 36 km), so we 

conclude that the results of NOX sensitivity runs at 36 km are representative of results if 12-km 

grid resolution had been used. 

While a statewide zeroing out of NOX emissions in Tennessee is impossible to accomplish in 

reality, it is used to represent the maximum conceptual effect of NOX emissions on total PM2.5

mass and to demonstrate that all the NOX emissions in the state do not significantly impact total 

PM2.5. One major caveat is NOX reductions of this magnitude create serious inequities in model 

chemistry. Gaseous species such as ozone (O3) require NOX for oxidation processes. Large 

reductions of NOX seriously deteriorate O3 production, especially during the 2nd and 3rd quarters. 

Such large decreases in O3 reduce associated atmospheric oxidants, which in turn decreases OC 

and SO4 formation (Figure 3- 7). The conversion of VOCs to secondary organic aerosols (e.g., 

OC) and the conversion of SO2 to SO4 are therefore significantly altered. 
39 

Source: Particulate Matter Science for Policy Makers

– A NARSTO Assessment, 2003.

Figure 3- 7: Atmospheric Aerosol Processes 

A 70% reduction in Tennessee statewide NOX emissions was also modeled in addition to the 

100% NOX reduction sensitivity run. The 70% NOX reduction simulates the impacts of 

tremendous NOX removal while still allowing for some summertime O3 and oxidation processes. 

Table 3-6 and Table 3-7 show the results for annual average PM2.5 mass in the Knoxville 

nonattainment area comparing the 2009 Base G2 simulation to the 100% (Table 3- 6) and 70% 

(Table 3-7) NOX reduction sensitivities. 

Table 3- 6: Annual Average PM2.5 for ASIP 2009 Base G2 Future Design Values and for 

Tennessee Statewide 100% NOX Emissions Reduction for FRM Monitors in Knoxville, TN 

PM2.5 Nonattainment Area 

Statewide 100 % NOx 

AIRS ID

47-009-0011 Blount 12.73 12.05 -0.68

47-093-0028 Knox 13.48 12.75 -0.73

47-093-1017 Knox 14.72 13.87 -0.85

47-093-1020 Knox 13.99 13.15 -0.84

47-145-0004 Roane 12.54 11.93 -0.61

2009g2a Annual 

PM2.5 g/m3

PM2.5 2009g2a 

County Difference TN 100% NOx 
40 

Table 3- 7: Annual Average PM2.5 for ASIP Base G2 2009 Future Design Values and for 

Tennessee Statewide 70% NOX Emissions Reduction for FRM monitors in Knoxville, TN 

PM2.5 Nonattainment Area 

Statewide 70% NOx

AIRS ID

47-009-0011 Blount 12.73 12.49 -0.24

47-093-0028 Knox 13.48 13.22 -0.26

47-093-1017 Knox 14.72 14.42 -0.30

47-093-1020 Knox 13.99 13.70 -0.29

47-145-0004 Roane 12.54 12.25 -0.29

2009g2a Annual 

PM2.5 g/m3

PM2.5 2009g2a 

County TN 70% NOx Difference

By zeroing out all the Tennessee statewide NOX emissions, 2009 future design values (DVF) are 

projected by the CMAQ model to be reduced by 0.61 to 0.85 μg/m3

. In comparison, a 70% 

reduction in NOX emissions is projected to reduce 2009 DVF by 0.24 to 0.30 μg/m3. 

Another way that these NOX sensitivities results can be analyzed is to evaluate the quarterly and 

annual responses for individual components of PM2.5. Table 3- 8 and Table 3- 9 provide the 

quarterly and annual differences for individual components of PM2.5 between the 2009 DVF and 

the 100% (Table 3- 8) and 70% (Table 3- 9) NOX reduction sensitivities for the FRM monitors in 

the Knoxville, TN PM2.5 nonattainment area. Figures 3-6-1 and 3.6-2 illustrate the annual 

responses to 100% (Figure 3- 8) and 70% (Figure 3- 9) NOX reductions for individual PM2.5

components at these sites. Annual average changes in Table 3- 8 and Table 3- 9 and in Figure 3- 

8 and Figure 3- 9 can be compared to annual average component concentrations for 2009 Future 

Design Values listed in Table 3- 5. 
41 

Table 3- 8: Changes in Quarterly and Annual Speciated PM2.5 (μg/m3) Between 2009 

Future Design Values and Tennessee Statewide 100% NOX Emissions Reductions for FRM 

Monitors in Knoxville, TN PM2.5 Nonattainment Area 

100% reduction in Tennessee statewide NOx emissions (change in PM2.5 - ≅g/m3

AIRS Code County Qrt SO4 NO3 OC EC Crustal NH4 PBW

1 0.00 -0.06 -0.07 0.00 0.00 -0.02 0.00

2 -0.12 0.00 -0.84 0.00 0.00 -0.03 -0.03

3 -0.19 -0.01 -0.95 0.00 0.00 -0.05 -0.05

4 -0.02 -0.06 -0.21 0.00 0.00 -0.02 0.00

Ann -0.08 -0.03 -0.52 0.00 0.00 -0.03 -0.02

1 0.00 -0.05 -0.08 0.00 0.00 -0.02 0.00

2 -0.12 0.00 -0.91 0.00 0.00 -0.04 -0.03

3 -0.20 -0.01 -0.99 0.00 0.00 -0.06 -0.05

4 -0.02 -0.05 -0.26 0.00 0.00 -0.02 0.00

Ann -0.08 -0.03 -0.56 0.00 0.00 -0.03 -0.04

1 0.00 -0.05 -0.09 0.00 0.00 -0.02 0.00

2 -0.12 0.00 -1.00 0.00 0.00 -0.03 -0.03

3 -0.20 -0.01 -1.35 0.00 0.00 -0.06 -0.05

4 -0.02 -0.06 -0.30 0.00 0.00 -0.02 0.00

Ann -0.08 -0.03 -0.68 0.00 0.00 -0.03 -0.02

1 -0.01 -0.08 -0.15 0.00 0.00 -0.03 0.00

2 -0.12 0.00 -0.96 0.00 0.00 -0.04 -0.03

3 -0.15 -0.01 -1.23 0.00 0.00 -0.04 -0.04

4 -0.02 -0.11 -0.28 0.00 0.00 -0.04 -0.01

Ann -0.07 -0.05 -0.66 0.00 0.00 -0.04 -0.02

1 0.00 -0.09 -0.12 0.00 0.00 -0.02 0.00

2 -0.11 0.00 -0.68 0.00 0.00 -0.03 -0.03

3 -0.18 0.00 -0.74 0.00 0.00 -0.05 -0.05

4 0.00 -0.08 -0.22 0.00 0.00 -0.02 0.00

Ann -0.07 -0.04 -0.44 0.00 0.00 -0.03 -0.02

47-009-0011 Blount

47-145-0004 Roane

Knox

Knox

Knox

47-093-0028

47-093-1017

47-093-1020

NO3 concentrations are very low in all quarters with highest values in the fourth quarter (0.4 

μg/m3

 or less). The 100% NOX reduction run projects very small reductions in NO3

concentrations in the first and fourth quarters (0.1 μg/m3

 or less) and no change in the second 

and third quarters. SO4 is projected to decrease slightly (less than 0.2 μg/m3) in the second and 

third quarter with corresponding minor changes in NH4 and PBW. There are essentially no 

changes in SO4 in the first and fourth quarters, suggesting that the modeled impact of NO3

reductions is reduced photochemical production of SO4 from SO2. Organic carbon is projected 

to decrease in all quarters, with small reductions (0.3 μg/m3

 or less) during the winter quarters 

and larger reductions (up to 1.2 μg/m3) in the third quarter. The seasonal variation in response 

provides additional evidence that these modeled responses are likely due to reduced oxidants 

from zeroed-out NOX emissions and thus reduced photochemical formation of secondary organic 

aerosols (Figure 3- 8). 

The results of the 70% NOX reduction run (Table 3- 9) provide notably smaller decreases in OC 

(0.1 μg/m3 or less in the winter quarters and less than 0.6 μg/m3 in the third quarter) than the 

100% reduction run. SO4 decreases for the 70% NOX reduction run are 0.1 μg/m3

 or less with 

largest responses projected for the third quarter and essentially no change for the winter quarters. 

These results suggest that NOX chemistry is highly nonlinear and that reducing all NOX

emissions produces unrealistically large changes in atmospheric photochemistry that would not 
42 

occur under maximum feasible NOX reductions. 

The annual average responses to 70% NOX reductions are a 0.2 μg/m3

 decrease in OC and a 0.05 

μg/m3

 decrease in SO4. These reductions are still greater than could feasibly be implemented, 

but the responses are clearly insignificant compared to the total PM2.5. We conclude that NOX is 

an insignificant contributor to PM2.5 in the Knoxville nonattainment area. 

 

Table 3- 9: Changes in Quarterly and Annual Speciated PM2.5 (μg/m3) Between 2009 

Future Design Values and Tennessee Statewide 70% NOX Emissions Reductions for FRM 

Monitors in Knoxville, TN PM2.5 Nonattainment Area 

70% reduction in Tennessee statewide NOx emissions (change in PM2.5 - ξg/m3

AIRS Code County Qrt SO4 NO3 OC EC Crustal NH4 PBW

1 0.03 -0.03 0.08 0.00 0.00 0.00 0.01

2 -0.08 0.00 -0.34 0.00 0.00 -0.02 -0.02

3 -0.13 0.00 -0.40 0.00 0.00 -0.04 -0.03

4 0.01 -0.03 0.03 0.00 0.00 -0.01 0.00

Ann -0.04 -0.02 -0.16 0.00 0.00 -0.04 -0.01

1 0.02 -0.03 0.10 0.00 0.00 0.00 0.01

2 -0.08 0.00 -0.37 0.00 0.00 -0.02 -0.02

3 -0.13 0.00 -0.40 0.00 0.00 -0.04 -0.03

4 0.01 -0.03 0.04 0.00 0.00 -0.01 0.00

Ann -0.05 -0.02 -0.16 0.00 0.00 -0.02 -0.01

1 0.02 -0.03 0.11 0.00 0.00 0.00 0.01

2 -0.08 0.00 -0.41 0.00 0.00 -0.02 -0.02

3 -0.14 0.00 -0.57 0.00 0.00 -0.04 -0.03

4 0.01 -0.04 0.05 0.00 0.00 -0.01 0.00

Ann -0.04 -0.02 -0.20 0.00 0.00 -0.02 -0.01

1 0.02 -0.05 0.08 0.00 0.00 -0.01 0.01

2 -0.08 0.00 -0.36 0.00 0.00 -0.02 -0.02

3 -0.10 0.00 -0.51 0.00 0.00 -0.03 -0.03

4 0.01 -0.07 0.02 0.00 0.00 -0.02 0.00

Ann -0.04 -0.03 -0.19 0.00 0.00 -0.02 -0.01

1 0.02 -0.05 0.01 0.00 0.00 -0.01 0.01

2 -0.08 0.00 -0.34 0.00 0.00 -0.02 -0.02

3 -0.13 0.00 -0.38 0.00 0.00 -0.04 -0.03

4 0.01 -0.05 -0.04 0.00 0.00 -0.01 0.00

Ann -0.04 -0.03 -0.19 0.00 0.00 -0.02 -0.02

47-145-0004 Roane

47-093-1017 Knox

47-093-1020 Knox

47-009-0011 Blount

47-093-0028 Knox

These conclusions are further illustrated in Figure 3- 8 and Figure 3- 9. Note that the scale of the 

PM2.5 response changes between the two figures so that although the lengths of the bars look 

comparable, the scale for Figure 3- 8 is from 0.1 to – 0.9 μg/m3 while the scale for Figure 3- 9 is 

0.05 to – 0.35 μg/m3

. 
43 

100% NOx Reduction Responses

-0.9

-0.8

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

47-009-0011 47-093-0028 47-093-1017 47-093-1020 47-145-0004

Delta (μg/m^3)

PBW

NH4

Crustal

EC

OC

NO3

SO4

Figure 3- 8: Annual Average Speciated Response to Tennessee Statewide 100% NOX

Reduction in 2009 for FRM Monitors in Knoxville, TN PM2.5 Nonattainment Area 

70% NOx Reduction Responses

-0.35

-0.3

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

47-009-0011 47-093-0028 47-093-1017 47-093-1020 47-145-0004

Delta (μg/m^3)

PBW

NH4

Crustal

EC

OC

NO3

SO4

Figure 3- 9: Annual Average Speciated Response to Tennessee Statewide 70% NOX

Reduction in 2009 for FRM Monitors in Knoxville, TN PM2.5 Nonattainment Area 
44 

3.10. Summary 

Tennessee has demonstrated that NOX emissions are an insignificant precursor for total annual 

PM2.5 using evidence from inventory, monitoring and modeling data. Emissions inventories 

demonstrate that statewide NOX emissions will be reduced 33% between 2002 and 2009. Within 

the Knoxville nonattainment area, NOX emissions will be reduced by 58% during this period. 

Following EPA SANDWICH and SMAT methods for calculating 2002 base and 2009 future 

design values, respectively, the annual contributions from NO3 at the FRM monitors within the 

Knoxville nonattainment area range from 0.1 to 0.2 μg/m3

 in both 2002 and 2009. The highest 

concentrations of particulate NO3 are observed in winter months, when formation of NO3 more 

readily occurs. Particulate NO3 is barely measurable during the other portions of the year. 

Including ammonium (NH4) and particle bound water (PBW) attributable to nitrate, total 

contributions from NH4NO3 in both 2002 and 2009 range from 0.15 to 0.32μg/m3. These 

contributions are 0.9 to 2.2% of the total PM2.5 in 2002 and 1.2 to 2.7% of the total PM2.5 in 

2009. 

Model attainment demonstrations based on current and future emission controls clearly 

demonstrate that all the FRM monitors in the Knoxville, TN nonattainment area will be attaining 

by 2009. Reductions in SO2 emissions are responsible for the reduced PM2.5 concentrations. 

Further reductions in PM2.5 are expected when planned flue gas desulfurization controls are 

operational at coal-fired power plants in the Knoxville nonattainment area in the 2009-2010 

timeframe. 

Sensitivity modeling also establishes that NOX is insignificant to total annual PM2.5 mass. Total 

removal of NOX emissions resulted in decreases in secondary sulfate and secondary organic 

carbon during the photochemically active third quarter. We believe these modeled reductions to 

be unrealistic due to unrealistic changes in atmospheric chemistry. Substantial (70%) NOX

reductions resulted in relatively minor (0.3 μg/m3

 or less) changes in total PM2.5 mass, or less 

than 2% of the current NAAQS. Coupled with the aforementioned emissions data, observational 

data, and attainment testing, the modeling sensitivities reinforce the finding that NOX, as a 

precursor to PM2.5 concentrations, is insignificant. 

3.11. Addendum to Section 3.0 

EPA has indicated that the Agency continues to have concerns regarding NOX insignificance 

demonstrations, and that the information presented within this section may not be sufficient to 

overturn the presumption of NOX significance as a PM2.5 precursor pollutant. Tennessee will 

incorporate the measures indicated in Attachment Q (NOX Addendum) as an enforceable part of 

this SIP. If Tennessee obtains sufficient additional information to overturn the presumption of 

NOX significance in the future, that information will be submitted to EPA, and Tennessee will 

submit an amendment to the SIP to request removal of applicable NOX provisions. 
45 

4.0 EMISSION INVENTORIES 

The emission inventory is a comprehensive quantification of all emissions in the nonattainment 

area and the State that cause or contribute to the area’s failure to attain the NAAQS. For 

accurate quantification of emissions, the inventory is developed for a past (baseline) year, and 

future year inventories are developed from the base. EPA recommended 2002 as the baseline 

year in a letter dated November 18, 200212, since a National Emission Inventory and monitored 

PM2.5 values were both available for this year. A regional emissions inventory was developed by 

the ASIP work group, refined over several iterations as stakeholders provided improved 

emissions estimates13,14, and projected forward to develop a 2009 inventory. 

4.1. Development of 2002 Emission Inventories 

4.1a. Area Sources 

The area source sector of the emission inventory consisted of three components: development of 

a “typical” year fire inventory; incorporation of data submitted by States to EPA pursuant to the 

Consolidated Emissions Reporting Rule (CERR); and development of NH3 emission estimates 

for livestock and fertilizers and paved road PM emissions. 

Development of a typical year fire inventory provided the capability of using a comparable data 

set for both the base year and future years. Since fire emissions are not easily grown or 

projected, VISTAS determined that a typical year fire inventory was needed to effectively 

represent fires in base- and future-year inventories. Development of the “typical” year fire 

inventory covered wildfire, prescribed burning, agricultural fires and land clearing fires. Typical 

year fire emissions were developed from actual fire acreage data and emissions were calculated 

for each State in the ASIP region. 

The second component of the area source inventory was the incorporation of CERR data 

submitted by States to EPA. The CERR data work involved: 1) obtaining data from EPA; 2) 

evaluating reported pollutants and emissions to avoid double-counting; and 3) adding missing 

sources/pollutants, as necessary. 

The final component of the area source inventory was related to the development of ammonia 

emission estimates for livestock and fertilizers and estimation paved road PM emissions. 

Version 3.6 of the Carnegie Mellon University (CMU) ammonia model was used to estimate 

 

12 “2002 Base Year Emission Inventory SIP Planning: 8-hr ozone, PM2.5, and Regional Haze Programs,” signed by Lydia N. Wegman 

13 A detailed discussion of inventory development is provided in the “Documentation of the Base G 2002 Base Year, 2009 and 2018 Emission 

Inventories for VISTAS” (July 2, 2007). A copy of this document is provided in Attachment A. 

14 Concurrently with the prehearing draft version of this SIP, the ASIP work group released the air quality modeling results based upon the ASIP 

States’ Best and Final emission inventory, which contains minor updates to the Base G2 version of the 2009 emission inventory. The results of 

the Best and Final modeling runs (Section 8.0) indicate minimal differences between the Best and Final Base G4 results. Section 8.0 of the final 

SIP presents the attainment demonstration results for both Base G2 and Base G4 emission inventories, and the Best and Final changes to the Base 

G2 emission inventory are detailed in Attachment N. 
46 

livestock and fertilizer emissions. For paved road PM estimates, ASIP used the most recent EPA 

estimates developed in the National Emission Inventory (NEI)15. 

4.1b. Mobile Sources 

The MOBILE6 module of the Sparse Matrix Operator Kernel Emissions (SMOKE) model was 

used to develop the on-road mobile source emissions estimates for CO, NOX, NH3, SO2, PM, and 

VOC emissions. The MOBILE6 parameters, vehicle fleet descriptions, and VMT estimates were 

combined with gridded, episode-specific temperature data to calculate the gridded, temporalized 

emission estimates. The emission factors model included the following variables: 

• Hourly and daily minimum/maximum temperatures; 

• Facility speeds; 

• Inspection/maintenance (I/M) control programs, if any; 

• Adjustments for running losses; 

• Splitting of evaporative and exhaust emissions into separate source categories; 

• VMT, fleet turnover, and changes in fuel composition and Reid vapor pressure. 

The primary input to MOBILE6 was the MOBILE shell file, which contained the various options 

to direct the calculation of the MOBILE6 emissions factors (e.g. type of inspection and 

maintenance program, oxygenated fuel program in effect, alternative vehicle mix profiles, Reid 

Vapor Pressure of in-use fuel, operating mode). Onroad mobile source emissions were produced 

using selected weeks (seven days) of each month and using these days as representative of the 

entire month. This selection criterion allowed for the representation of day-of-the-week 

variability in the on-road motor vehicles the meteorological variability in each month. The 

modeled weeks were selected from mid-month, avoiding inclusion of major holidays. 

Emissions from nonroad mobile sources were estimated by developing emissions for sources 

included in the NONROAD model were developed and by estimation of emissions from sources 

not included in the NONROAD model. An initial 2002 base year emissions inventory for 

nonroad engines and equipment covered by the EPA NONROAD model was prepared for 

VISTAS in early 2004. Revisions to the emissions inventory were implemented to ensure that 

the latest State and local data were considered and to accurately reflect gasoline sulfur contents 

for 2002. 

4.1c. Non-EGU Point Sources 

The starting point for the 2002 Base G2 emission inventory was EPA’s 2002 National Emission 

Inventory (NEI). The 1999 data was supplemented with more recent inventories submitted by 

State and local agencies and was ultimately replaced with data submitted by ASIP States 

pursuant to the CERR and included in the 2002 NEI. The 2002 Base G2 emission inventory was 

released in August 2006 and incorporated updates and corrections to the 2002 NEI inventory. 

Changes for Tennessee included the correction of latitude and longitude values; identification of 

 

15 EPA’s improved methodology for estimating paved road emissions were substituted directly into the inventory after receiving consensus from 

the States to perform the replacement. 
47 

closed facilities with non-zero emissions reported in the NEI; and updating emissions for several 

facilities, based on the most recently reported information. 

4.1d. EGU Point Sources 

For point sources, the 2002 baseline inventory includes both actual emissions for coal-fired 

electric utilities and a “typical” year inventory. Actual emissions from 2002 were obtained from 

EPA’s Clean Air Markets (CAMD) emissions data. The “typical year” point source inventory 

was developed to smooth out any anomalies in utility emissions due to meteorology, economic, 

and outage factors in 2002. The 2002 “typical” baseline emission inventory for EGUs was 

developed using CAMD data to develop normalization factors for the 2002 typical emissions 

inventory. 2002 actual emissions were normalized using the ratio of the 2002 actual heat input 

to the average heat input for 2000-2004. ASIP used the actual 2002 heat input and the average 

heat input for the 5-year period from 2000-2004 as the normalization factor, as follows: 

Normalization Factor = (2000-2004 average heat input)

2002 actual heat input 

If the unit did not operate for all five years from 2000-2004, then the average heat input was 

calculated for the years in which the unit did operate. Actual emissions for 2002 were multiplied 

by the normalization factor16 to determine the typical emissions for 2002, as follows: 

Typical Emissions = (2002 actual emissions)(Normalization Factor) 

For the entire ASIP region, actual 2002 SO2 emissions were about 0.5 percent higher than the 

typical year emissions. The differences on a State-by-State basis ranged from actual emissions 

6.6% lower in Florida to 10.9% higher in Mississippi. Tennessee’s 2002 actual SO2 emissions 

from EGUs were 4.2% higher than typical year emissions. 

4.2. Development of 2009 Emission Inventories 

4.2a. Area Sources 

The 2002 base year inventory was used as the starting point for projections. For non-agricultural 

sources, the ASIP contractor worked with States to obtain State-specific growth factors and 

future controls requirements. Uncontrolled emissions were obtained from the 2002 inventory, 

and control requirements were then added to calculate controlled emissions. Growth factors 

were obtained from States or from EPA’s CAIR emission projections and these factors were 

applied to project the controlled emissions to the future year. If no State or CAIR growth factor 

was available, then EGAS Version 5 growth factors were used. The final inventory was then 

submitted to the ASIP States for review and comment. 

 

16 For some EGUs, the ASIP work group made additional adjustments to allow for special circumstances. For example, total emissions were zero 

for units that did not operate in 2002. If the unit had been permanently retired prior to 2002, then the typical year inventory used zero emissions 

for 2002. If the unit had not been permanently retired and would normally operate in a typical year, then the 2000 or 2001 heat input and 

emission rate were used to calculate the typical year emissions. 
48 

To calculate projected emissions for agricultural area sources (predominantly ammonia), ASIP 

used the 2002 base year inventory data and obtained State-specific growth factors from 

individual States. Since base year emissions were uncontrolled, and no future controls were 

identified for agricultural sources, ASIP projected the agricultural emissions using State-specific 

growth or U.S. EPA’s Interstate Air Quality Transport Rule (IAQTR) ammonia inventory. The 

final inventory was submitted to the ASIP States for review and comment. 

The 2009 emissions inventory for fires was updated to account for increased prescribed fire 

burning by Federal agencies in future years. ASIP developed an updated Base G2 fire inventory 

for 2009 to capture the projected increases. 

4.2b. Point Sources 

Different approaches were used to develop the point source inventory for EGUs and non-EGUs. 

For EGUs, Integrated Planning Model (IPM) results were used to project future generation and 

to calculate the impact of future emission control programs17. IPM results were adjusted as 

necessary to account for planned emission controls at specific EGUs. For non-EGUs, the 2009 

inventory was based on updated growth and control data, supplemented with State/Local agency 

input and updated fuel use forecast data from the U.S. Department of Energy. Post-2002 facility 

shutdowns were also noted in the 2009 inventory. 

For both sectors, 2009 and 2018 inventories were generated using a combined on-the-books 

(OTB) and on-the-way (OTW) control scenario. The OTB/OTW control scenario accounted for 

post-2002 emission reductions from promulgated and proposed Federal, State, local, and sitespecific control programs as of July 1, 2004. 

4.2c. Mobile Sources 

To develop the future year projections, ASIP assembled data to develop 2009 base case 

inventories from: 1) an inventory that included all “on-the-books” control programs and 2) an 

“on-the-way” inventory that included controls that were likely to be “on-the way”. For the 2009 

emission forecasts to the mobile source sector, “on-the-books” and “on-the-way” were defined 

with the same strategies and therefore only a single projection scenario was developed for the 

forecast year. To ensure consistency across evaluation years, the 2009 inventory was developed, 

to the maximum extent practical, using methodologies identical to those employed in developing 

the 2002 on-road portion of the revised 2002 base-year inventory. 

The methodology used to generate the 2009 vehicle miles traveled (VMT) for use in estimating 

on-road mobile source emissions was as follows: 

 

17 EPA uses the Integrated Planning Model (IPM) to analyze the projected impact of environmental policies on the electric power sector in the 

48 contiguous states and the District of Columbia. IPM provides forecasts of least-cost capacity expansion, electricity dispatch, and emission 

control strategies for meeting energy demand and environmental, transmission, dispatch, and reliability constraints. IPM was used to evaluate the 

cost and emissions impacts of SO2 and NOX reductions in the CAIR rulemaking. 

IPM runs were used to predict future electric utility emissions for VISTAS regional haze work and ASIP PM2.5 modeling. However, ASIP States 

reviewed IPM-predicted control strategies and made changes as necessary to ensure accuracy. These changes are described in more detail in 

Attachment A 
49 

1. All estimates started from the final VMT estimates used for the 2002 revised base year 

inventory. 

2. Initial 2009 VMT estimates were based on linear growth rates for each State, county, and 

vehicle type as derived from the VMT data assembled by the U.S. EPA for their most 

recent HDD (heavy duty diesel) rulemaking. 

In general, Tennessee estimates were based on the HDD rule growth rate described in step 2. 

Independent VMT estimates for 2009 for the Knoxville PM2.5 Nonattainment Area were used in 

place of the HDD rule-derived estimates. The Knoxville Area VMT projections are shown in 

Table 4- 1 below: 

Table 4- 1: Total 2009 Annual Vehicle Miles Traveled in the Knoxville PM2.5

Nonattainment Area Used in ASIP Attainment Modeling 

County 

Annual VMT 

(miles/year) 

Anderson 1,027,024,857 

Blount 1,295,909,188 

Knox 5,637,316,347 

Loudon 923,326,321 

Nonroad mobile source emissions were developed for 2009 in the same fashion as they were 

developed for 2002. The final version of the NONROAD2005 was used for the 2009 

projections. Other specific updates for the projection years for NONROAD model sources 

consisted of: 

1. Change the emission inventory year in the model to be reflective of the projection year. 

2. Revise the fuel sulfur content for gasoline and diesel powered equipment. 

3. Implement a limited number of local control program changes (most national control 

program changes are handled internally within the NONROAD model, so explicit input 

file changes are not required). 

All equipment population growth and fleet turnover impacts are also handled internally within 

the NONROAD model, so that explicit changes to the input files are not required. To correctly 

account for diesel fuel sulfur content differences between the base and projection years, two sets 

of input and output files were prepared for each forecast year, one set for land-based equipment 

and one set for marine equipment. The specific diesel fuel sulfur contents modeled were as 

follows (Table 4- 2): 

Table 4- 2: Diesel Sulfur Input Used in NONROAD 

Diesel Sulfur (ppm) 2002 2009 

Land-based 2,500 348 

Marine-based 2,500 408 
50 

To correctly account for the national reduction in gasoline sulfur content (a national control not 

explicitly handled by the NONROAD model), all NONROAD input files for 2009 were revised 

to reflect a gasoline fuel sulfur content of 30 ppmW. 

Those sources requiring emissions estimated outside the NONROAD model (locomotives, 

airplanes and commercial marine vessels) were projected through a combination of applied 

technological reductions and growth due to increased demand on these sectors. Further details 

are contained in the Attachment A. 

4.3. 2002 Emission Inventories 

Sulfur dioxide and direct PM2.5 emissions inventories for the 2002 baseline year are summarized 

in Table 4- 3 and Table 4-4. 

Table 4- 3: 2002 SO2 Emissions 

County 

2002 SO2 Emissions in Tons 

Area Nonroad Onroad 

EGU 

Point 

(Actual) 

EGU 

Point 

(Typical) 

NonEGU 

Point 

Total 

(with 

Actual 

Point)

Total 

(with 

Typical 

Point)

Anderson 271 69 111 42,188 36,729 2,504 45,143 39,684 

Blount 59 127 119 0 0 4,264 4,569 4,569 

Knox 39 425 682 0 0 1,303 2,449 2,449 

Loudon 18 111 120 0 0 4,221 4,470 4,470 

Roane* 2 2 11 77,571 76,055 0 77,586 76,070 

Totals 389 734 1,043 119,759 112,784 12,292 134,217 127,242 

* Nonattainment portion only 

Table 4- 4: 2002 PM2.5 Emissions 

County 

PM2.5 Emissions in Tons 

Area Nonroad Onroad 

EGU 

Point 

(Actual) 

EGU 

Point 

(Typical) 

NonEGU 

Point 

Total 

(with 

Actual 

Point)

Total 

(with 

Typical 

Point)

Anderson 501 55 46 1,872 1,630 203 2,677 2,435 

Blount 718 115 41 0 0 1,684 2,558 2,558 

Knox 445 312 284 0 0 471 1,512 1,512 

Loudon 334 62 60 0 0 412 868 868 

Roane* 5 1 3 3,217 3,156 0 3,226 3,165 

Totals 2,002 544 434 5,089 4,786 2,770 10,839 10,536 

* Nonattainment portion only

Review of the nonattainment area’s SO2 emission inventory for 2002 indicates that point sources 

were responsible for the overwhelming majority (98%) of actual SO2 emissions in 2002, and 

point sources with greater than 100 tons/year of SO2 emissions accounted for virtually all 

(99.8%) of point source SO2 emissions in the inventory. About 89% of point source SO2 in the 

nonattainment area (119,759 actual tons, Table 4- 5) was emitted from TVA’s Bull Run and 
51 

Kingston Fossil Plants in Anderson and Roane Counties. 

Table 4- 5: Point Sources in the Knoxville Nonattainment Area with > 100 tons/year SO2

Emissions, Sorted by Rank (2002 Actual Emissions) 

County Facility Description 

SO2 Emissions 

(tons) 

% of Total 

Point Source 

Emissions 

Cumulative 

% of Point 

Source 

Emissions 

Roane 

TVA 

Kingston 

Fossil 

Plant 

External Combustion Boilers 

Electric Generation 

Bituminous/Subbituminous Coal 

Pulverized Coal: Dry Bottom 

(Bituminous Coal) 77,571 58.7% 

Anderson 

TVA Bull 

Run Fossil 

Plant 

External Combustion Boilers 

Electric Generation 

Bituminous/Subbituminous Coal 

Pulverized Coal: Dry Bottom 

(Tangential) (Bituminous Coal) 42,188 31.9% 90.7% 

Blount Alcoa 

Industrial Processes 

Primary Metal Production 

Aluminum Ore (Electro-reduction) 

Materials Handling 3,673 2.8% 93.5% 

Loudon 

Tate & 

Lyle 

External Combustion Boilers 

Industrial 

Bituminous/Subbituminous Coal 

Spreader Stoker 3,262 2.5% 95.9% 

Anderson 

U. S. DOE 

Y-12 Plant 

External Combustion Boilers 

Industrial 

Bituminous/Subbituminous Coal 

Pulverized Coal: Wet Bottom 2,354 1.8% 97.7% 

Knox 

University 

of 

Tennessee 

External Combustion Boilers 

Commercial/Institutional 

Bituminous/Subbituminous Coal 

Spreader Stoker (Bituminous Coal) 656 0.5% 98.2% 

Blount Alcoa 

Industrial Processes 

Primary Metal Production 

Aluminum Ore (Electro-reduction) 

Anode Baking Furnace 424 0.3% 98.5% 

Loudon 

Monterey 

Mushroom 

(see 

Attachment P)

External Combustion Boilers 

Industrial 

Residual Oil 

Grade 6 Oil 390 0.3% 98.8% 

Knox Cemex 

Industrial Processes 

Mineral Products 

Cement Manufacturing (Dry 

Process) 

Kilns 313 0.2% 99.1% 

Loudon 

Tate & 

Lyle 

Industrial Processes 

Food and Agriculture 

Grain Millings 

Gluten Drying: Direct-fired Dryer - 

Produces Corn 276 0.2% 99.3% 
52 

County Facility Description 

SO2 Emissions 

(tons) 

% of Total 

Point Source 

Emissions 

Cumulative 

% of Point 

Source 

Emissions 

Knox 

General 

Shale 

Products 

Industrial Processes 

Mineral Products 

Brick Manufacture 

Curing and Firing: Coal-fired 

Tunnel Kilns 270 0.2% 99.5% 

Blount 

APACTennessee 

Industrial Processes 

Mineral Products 

Asphalt Concrete 

Drum Dryer: Drum Mix Plant 153 0.1% 99.6% 

Loudon 

Kimberly 

Clark 

External Combustion Boilers 

Industrial 

Distillate Oil 

Grades 1 and 2 Oil 129 0.1% 99.7% 

Anderson 

Carlisle 

Tire Corp. 

External Combustion Boilers 

Industrial 

Natural Gas 

10-100 Million Btu/hr 114 0.1% 99.8% 

With respect to direct PM2.5, point sources accounted for about 73% (actual emissions basis) of 

the nonattainment area’s emissions in 2002, and sources with greater than 100 tons/year of direct 

PM2.5 emissions accounted for 88.8% of point source emissions in the inventory (Table 4-6). 

TVA’s Bull Run and Kingston Fossil Plants were the largest emitters of PM2.5, emitting 64.2% 

of total point source emissions. While point sources still make up the largest fraction of directly 

emitted PM2.5 in the nonattainment area, direct PM2.5 emissions from area sources are more 

significant than was observed with SO2. 

Table 4- 6: Point Sources with > 100 tons/year PM2.5 Emissions 

Sorted by Rank (2002 Actual Emissions Basis)

County Facility Description 

PM2.5 Emissions 

(tons/year) 

% of Total 

Point Source 

Emissions 

Cumulative 

% 

Roane 

TVA 

Kingston 

Fossil 

Plant 

External Combustion Boilers 

Electric Generation 

Bituminous/Subbituminous Coal 

Pulverized Coal: Dry Bottom (Bituminous 

Coal) 3,217 40.9% 

Anderson 

TVA 

Bull Run 

Fossil 

Plant 

External Combustion Boilers 

Electric Generation 

Bituminous/Subbituminous Coal 

Pulverized Coal: Dry Bottom (Tangential) 

(Bituminous Coal) 1,872 23.8% 64.7% 

Blount Aloca 

Industrial Processes 

Primary Metal Production 

Aluminum Ore (Electro-reduction) 

Materials Handling 540 6.9% 71.6% 

Knox Cemex 

Industrial Processes 

Mineral Products 

Cement Manufacturing (Dry Process) 283 3.6% 75.2% 
53 

County Facility Description 

PM2.5 Emissions 

(tons/year) 

% of Total 

Point Source 

Emissions 

Cumulative 

% 

Kilns 

Blount USI, Inc. 

Petroleum and Solvent Evaporation 

Surface Coating Operations 

Surface Coating Application - General 

Adhesive: Spray 264 3.4% 78.6% 

Blount Alcoa 

Industrial Processes 

Secondary Metal Production 

Aluminum 

Smelting Furnace/Reverberatory 258 3.3% 81.9% 

Blount Alcoa 

Industrial Processes 

Primary Metal Production 

Other Not Classified 

Other Not Classified 222 2.8% 84.7% 

Loudon 

Tate & 

Lyle 

External Combustion Boilers 

Industrial 

Bituminous/Subbituminous Coal 

Spreader Stoker 111 1.4% 86.1% 

Loudon 

Kimberly 

Clark 

Industrial Processes 

Pulp and Paper and Wood Products 

Miscellaneous Paper Products 

Other Not Classified 108 1.4% 87.5% 

Blount Alcoa 

Industrial Processes 

Secondary Metal Production 

Aluminum 

Rolling/Drawing/Extruding 104 1.3% 88.8% 

4.4. 2009 Emission Inventories 

Projected sulfur dioxide and direct PM2.5 emissions inventories for 2009 are summarized in 

Table 4-7 and Table 4- 8. The 2009 emissions inventories assume that affected sources will 

install controls required to comply with existing Federal measures that become effective between 

2002 and 2009. Additional State-specific measures were not assumed. The SO2 and PM2.5

emissions estimates presented in Table 4-7 and Table 4-8 represent the level of emissions 

modeled in the annual PM2.5 control strategy for the Knoxville nonattainment area to 

demonstrate that the area will attain the annual PM2.5 NAAQS in 2009. 

Table 4- 7: 2009 SO2 Emissions 

County 

SO2 Emissions in Tons 

Area Nonroad Onroad EGU Point* 

Non-EGU 

Point Total 

Anderson 282 12 14 8,657 2,427 11,392 

Blount 64 66 15 0 4,757 4,902 

Knox 46 111 72 0 1,336 1,566 

Loudon 19 54 14 0 4,086 4,173 

Roane** 2 1 1 71,120 0 71,124 

Totals 413 243 116 79,777 12,606 93,155 

* 2009 EGU emissions inventory was developed from “2002 typical emissions” inventory for EGUs. See Section 5.0 of this document for 

further discussion of the emissions controls that were applied to EGUs to develop the 2009 inventory. ** Nonattainment portion only.
54 

Table 4- 8: 2009 PM2.5 Emissions 

County 

PM2.5 Emissions in Tons 

Area Nonroad Onroad EGU Point* 

Non-EGU 

Point Total 

Anderson 534 47 33 2,212 165 2,991 

Blount 745 111 32 0 1,457 2,345 

Knox 495 255 171 0 429 1,349 

Loudon 353 52 39 0 378 822 

Roane** 5 1 2 3,391 0 3,399 

Totals 2,133 466 276 5,603 2,429 10,907 

* 2009 EGU emissions inventory was developed from “2002 typical emissions” inventory for EGUs. See Section 5.0 of this document for further 

discussion of the emissions controls that were applied to EGUs to develop the 2009 inventory. 

** Nonattainment portion only

Table 4- 9 and Table 4- 10 show the projected reduction in sulfur dioxide emissions between 

2002 and 2009. Most of the projected sulfur dioxide reductions result from the installation of 

controls at TVA’s Bull Run Fossil Plant, which is required to comply with the provisions of the 

Clean Air Interstate Rule (see Section 5.0 for further discussion of this rule). Significant 

reductions (as a percentage of 2002 emissions) are also achieved from the onroad and nonroad 

mobile source sectors. These reductions offset a slight growth in emissions from area sources. 

Direct emissions of PM2.5 (Table 4- 11 and Table 4- 12) are projected to increase by 1-3% 

between 2002 and 2009, as increased emissions from point and area sources offset reductions 

from onroad and nonroad mobile sectors. 
55 

Table 4- 9: 2002-2009 SO2 Emission Reductions 

Tons per year and % Change from 2002 Baseline 

(Actual Emissions Basis for 2002 Point Source Inventory) 

Area Nonroad Onroad Point 

County Tons 

Change* 

from 2002 Tons 

Change* 

from 2002 Tons 

Change* 

from 2002 Tons 

Change* 

from 2002 

Anderson 10 4% -57 -83% -98 -88% -33,609 -75% -Blount 5 9% -61 -48% -104 -87% 493 12% Knox 7 17% -314 -74% -610 -89% 33 3% Loudon 1 8% -58 -52% -106 -88% -134 -3% Roane** 0.1 3% -1 -45% -10 -89% -6,451 -8% -Totals 24 6% -491 -67% -927 -89% -39,669 -30% -* Negative numbers indicate emissions reduction, positive numbers indicate emissions growth. ** Nonattainment portion only 

Table 4- 10: 2002-2009 SO2 Emission Reductions 

Tons per year and % Change from 2002 Baseline 

(Typical Emissions Basis for 2002 Point Source Inventory) 

Area Nonroad Onroad Point 

County Tons/year 

Change* 

from 2002 Tons/year 

Change* 

from 2002 Tons/year 

Change* 

from 

2002 Tons/year 

Change* 

from 2002 T

Anderson 10 4% -57 -83% -98 -88% -28,150 -72% Blount 5 9% -61 -48% -104 -87% 493 12% Knox 7 17% -314 -74% -610 -89% 33 3% Loudon 1 8% -58 -52% -106 -88% -134 -3% Roane** 0.1 3% -1 -45% -10 -89% -4,936 -6% Totals 24 6% -491 -67% -927 -89% -32,694 -26% * Negative numbers indicate emissions reduction, positive numbers indicate emissions growth. ** Nonattainment portion only 
56 

Table 4- 11: 2002-2009 PM2.5 Emission Reductions 

Tons per year and % Change from 2002 Baseline 

(Actual Emissions Basis for 2002 Point Source Inventory) 

Area Nonroad Onroad Point 

County Tons/year 

Change* 

from 2002 Tons/year 

Change* 

from 2002 Tons/year 

Change* 

from 2002 Tons/year 

Change* 

from 2002 To

Anderson 33 7% -8 -14% -13 -29% 302 15% Blount 27 4% -4 -3% -9 -22% -227 -13% Knox 50 11% -57 -18% -114 -40% -43 -9% Loudon 20 6% -10 -16% -21 -35% -34 -8% Roane** 0.2 4% -0.2 -19% -1 -42% 174 5% Totals 131 7% -78 -14% -158 -36% 172 2% * Negative numbers indicate emissions reduction, positive numbers indicate emissions growth. ** Nonattainment portion only 

Table 4- 12: 2002-2009 PM2.5 Emission Reductions 

Tons per year and % Change from 2002 Baseline 

(Typical Emissions Basis for 2002 Point Source Inventory) 

Area Nonroad Onroad Point 

County Tons/year 

Change* 

from 2002 Tons/year 

Change* 

from 2002 Tons/year 

Change* 

from 2002 Tons/year 

Change* 

from 2002 To

Anderson 33 7% -8 -14% -13 -29% 544 30% Blount 27 4% -4 -3% -9 -22% -227 -13% Knox 50 11% -57 -18% -114 -40% -43 -9% Loudon 20 6% -10 -16% -21 -35% -34 -8% Roane** 0.2 4% -0.2 -19% -1 -42% 235 7% Totals 131 7% -78 -14% -158 -36% 475 6% * Negative numbers indicate emissions reduction, positive numbers indicate emissions growth. ** Nonattainment portion only 
57 

4.5. Statewide Emission Inventories for 2002 and 2009 

Statewide SO2 emission inventories for Tennessee are summarized in Table 4- 13. This table 

projects that Statewide SO2 emissions will decline by 99,948 tons/year (21.6% decrease from 

2002 actual emissions) between 2002 and 2009, with the bulk of emissions reductions (78,743 

tons) occurring at EGU point sources. The largest percentage reductions are projected for 

onroad and nonroad mobile source categories (88.3% and 45.9%, respectively), while area 

source emissions are projected to grow by a small amount. 

Table 4- 13: Statewide SO2 Emission Inventory for Tennessee 

Year 

SO2 Emissions in Tons 

Area Nonroad Onroad EGU Point 

non-EGU 

Point Total 

2002 29,897 10,441 9,226 

333,884 Actual 

319,883 Typical 79,871 463,320* 

2009 30,555 5,651 1,076 255,141 70,947 363,372 

Change 658 -4,790 -8,150 78,743* -8,924 -99,948 

% Change 2.2% -45.9% -88.3% -23.6%* -11.2% -21.6%* 

* Actual emissions basis 

Statewide PM2.5 emission inventories for Tennessee are summarized in Table 4- 14. Overall, the 

emission inventory projects no significant reductions in PM2.5 emissions from EGUs and other 

point sources, and Statewide PM2.5 emissions are projected to increase by 120 tons/year (0.1% 

increase from 2002 actual emissions) between 2002 and 2009. These projected increases are 

offset to some extent by reductions from the onroad (-30.3% reduction) and nonroad (-13.9% 

reduction) source categories. Area source emissions are projected to grow by 3.6% between 

2002 and 2009. 

Table 4- 14: Statewide PM2.5 Emission Inventory for Tennessee 

Year 

PM2.5 Emissions in Tons 

Area Nonroad Onroad EGU Point 

non-EGU 

Point Total 

2002 42,103 6,458 3,949 

12,057 Actual 

11,394 Typical 27,916 92,483* 

2009 43,627 5,557 2,751 13,036 27,632 92,603 

Change 1,524 -900 -1,198 979* -284 120 

% Change 3.6% -13.9% -30.3% 8.1%* -1.0% 0.1%* 

* Actual emissions basis 
58 

5.0 CONTROL MEASURES 

The Fine Particle Implementation Rule states that virtually all nonattainment problems appear to 

result from a combination of local emissions and transported emissions from upwind areas. The 

Clean Air Act requires EPA to develop national rules for sources that significantly contribute to 

local air quality problems, and the Act also provides for States to address emissions sources on 

an area-specific basis through such requirements as Reasonably Available Control Technology 

(RACT), Reasonably Available Control Measures (RACM), and Reasonable Further Progress 

(RFP). This section discusses the control measures that were used in the modeled attainment 

test. 

5. 1. Point Sources - Clean Air Interstate Rule18

In a rulemaking action published in the Federal Register on May 12, 2005, EPA found that 

certain States must reduce emissions of SO2 and/or NOX because those emissions contributed 

significantly to downwind areas in other States that are not meeting the annual PM2.5 NAAQS or 

the 8-hour ozone NAAQS. The resulting Clean Air Interstate Rule (CAIR) required 28 States 

and the District of Columbia to revise their State Implementation Plans (SIPs) to reduce specified 

amounts of SO2 and/or NOX emissions. The following paragraphs summarize trends in SO2

emissions prior to the CAIR rulemaking, EPA’s assessment of the contribution of interstate 

transport to PM2.5 nonattainment, and the development of emissions budgets to reduce SO2

emissions from EGUs. 

Between 2000 and 2006, sulfur dioxide emissions from electricity generating units (EGUs) 

decreased by about 842,000 tons (15.0% reduction based on 2000 emissions) in Tennessee and 

surrounding States19,20 (Table 5- 1), while heat input from the same States grew modestly (2.1%) 

during the same period21. Analysis of the year-to-year variation in SO2 emissions indicates that 

this decline is not uniform, with the greatest reductions occurring between 2000 and 2001 and 

between 2005 and 2006 (Figure 5- 1, Table 5- 2). Emissions from Tennessee EGUs declined in 

all periods except for a slight increase during the period of 2002-2003. A similar trend is 

 

18 Substantial portions of this section were taken from the Federal Register Notice: Rule to Reduce Interstate Transport of Fine Particulate 

Matter and Ozone (Clean Air Interstate Rule); Revisions to Acid Rain Program; Revisions to the NOX SIP Call; Final Rule. Federal 

Register/Vol. 70, No. 91/Thursday, May 12, 2005/pp 25162 – 25405. 

19 For the reasons explained on the following pages, SO2 emissions are presented for Alabama, Georgia, Illinois, Indiana, Kentucky, North 

Carolina, Ohio, Tennessee, and West Virginia. 

20 All Acid Rain Program data presented in this section was obtained from U.S. EPA’s Clean Air Markets Data and Maps website 

(http://camddataandmaps.epa.gov/gdm/). 

21 Regional heat inputs for this time period were as follows: 

Year Heat Input (MMBtu) 

2000 8,399,479,937 

2001 8,628,921,892 

2002 8,007,177,384 

2003 8,554,715,805 

2004 8,466,718,364 

2005 8,474,640,837 

2006 8,804,565,781 

Alabama, Georgia, Illinois, Indiana, Kentucky, North Carolina, Ohio, Tennessee, and 

West Virginia 
59 

observed for TVA’s Bull Run and Kingston fossil plants - the two coal-fired utilities located in 

the nonattainment area (Figure 5- 2). 

Table 5- 1: SO2 Emissions 2000-2006 (Acid Rain Program Data) 

State 

SO2 Emissions in Tons 

1999 2000 2001 2002 2003 2004 2005 2006 

Alabama 542,434 512,075 383,485 448,248 458,622 412,440 460,072 455,193 

Georgia 512,227 518,746 489,627 512,654 540,716 547,413 616,169 636,843 

Illinois 710,354 429,850 368,220 353,699 365,333 362,900 326,632 280,340 

Indiana 941,852 874,617 795,506 778,868 804,829 862,876 870,812 820,993 

Kentucky 658,982 584,917 535,445 482,653 529,559 513,145 500,224 427,576 

North Carolina 457,943 453,442 450,487 462,993 462,041 472,320 500,936 462,143 

Ohio 1,309,892 1,209,458 1,125,479 1,132,069 1,175,905 1,091,520 1,085,485 962,142 

Tennessee 443,478 424,973 360,096 336,995 339,536 303,315 266,081 259,606 

West Virginia 694,517 593,315 498,056 507,110 539,858 473,760 467,082 454,158 

Totals 6,271,680 5,601,392 5,006,400 5,015,289 5,216,398 5,039,688 5,093,492 4,758,995 

Table 5- 2: Year-to-Year Change in SO2 Emissions 

 1999-2000 2000-2001 2001-2002 2002-2003 2003-2004 2004-2005 2005-2006 

Average 

1999-2006 

Alabama -5.6% -25.1% 12.6% 2.0% -9.0% 9.3% -1.0% -2.4% 

Georgia 1.3% -6.9% 0.5% 3.6% -7.0% -0.5% -10.2% -2.7% 

Illinois -39.5% -9.0% -1.9% 3.0% 6.6% 0.9% -5.7% -6.5% 

Indiana -7.1% -8.5% -9.0% 8.0% -2.8% -2.2% -12.4% -4.9% 

Kentucky -11.2% 2.2% -9.9% 2.7% 4.7% -5.8% -6.0% -3.3% 

North Carolina -1.0% 1.1% -1.7% 2.4% 7.7% -1.0% 1.3% 1.3% 

Ohio -7.7% -0.7% 2.8% -0.2% 2.3% 6.3% -8.6% -0.8% 

Tennessee -4.2% -14.3% -3.4% 2.7% -0.6% -8.4% -10.8% -5.6% 

West Virginia -14.6% -5.6% 4.4% 5.4% 1.3% 13.3% 4.0% 1.2% 

Annual Average -10.7% -7.4% -0.6% 3.3% 0.4% 1.3% -5.5% -2.7% 
60 

Figure 5- 1: Tennessee and Regional SO2 Emissions 

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

2000 2001 2002 2003 2004 2005 2006

SO2Emissions (tons)

TVA Bull Run TVA Kingston Total

Figure 5- 2: Change in SO2 Emissions at TVA Bull Run and Kingston, 2000-2006

The overall decrease in SO2 emissions is consistent with a gradual decline in emissions since 

1995, when the first caps under the Acid Rain Program became effective. Total SO2 emissions 

for the region were 4,758,995 tons in 2006, and in the absence of new emission requirements, 

the number would continue to decrease to around the final Title IV allocations as the bank of 

existing Title IV allowances is depleted. Implementation of CAIR in 2010 and subsequent years 

will accelerate this trend, as a tighter SO2 emissions cap is implemented across the CAIR region 

and the Title IV allowance bank is depleted. 

The PM2.5 NAAQS is based upon annual averages, and because PM2.5 precursors are carried by 

wind currents for long distances, the collective contribution from multiple upwind States is a 

pronounced feature of PM2.5 transport. This transport occurs throughout the entire year and 

across a range of wind patterns, small individual contributions from multiple States can 

significantly impact PM2.5 attainment. It is likely that at least some nonattainment areas would 

find it difficult or impossible to attain the standards without upwind reductions. In the CAIR 

rulemaking, EPA used air quality modeling to “remove” an upwind State’s anthropogenic SO2

and NOX emissions and to determine which downwind nonattainment areas received the largest 
61 

ambient impact from upwind emission sources, based on a metric of 0.2 μg/m3 PM2.5 (1% of the 

annual standard, rounded to one significant digit). 

The results of EPA’s 2010 Base Case22 and zero-out modeling runs are indicated in Table 5- 3, 

which shows the maximum contribution from each upwind State to Tennessee’s PM2.5

nonattainment counties. The highest modeled contribution to a nonattainment county in 

Tennessee (from an upwind State) was 1.27 μg/m3

 (contribution from Georgia to the Hamilton 

County nonattainment area). Conversely, Tennessee’s highest contribution to a downwind 

nonattainment area (not shown in Table 5- 3) was 0.65 μg/m3

 to Walker County Georgia (part of 

the Chattanooga nonattainment area). 

Table 5- 3: PM2.5 Contributions to Tennessee Nonattainment Counties 

2010 Base Case 

Upwind State Magnitude of Contribution (μg/m3) 

Hamilton County Knox County 

Alabama 0.98 0.48 

Georgia 1.27 0.86 

Illinois 0.20 0.17 

Indiana 0.34 0.32 

Kentucky 0.32 0.44 

North Carolina 0.15 0.20 

Ohio 0.44 0.54 

Tennessee 0.69 1.20 

West Virginia 0.17 0.24 

Source: Technical Support Document for the Final Clean Air Interstate Rule, Air Quality Modeling Analyses, Appendix H 

Results are shown for States that contribute significantly to at least one nonattainment county in Tennessee. A contribution of <0.2 μg/m3

(rounded to one decimal point) is not considered significant. EPA’s CAIR modeling indicated that Arkansas, Mississippi, Missouri, and 

Virginia contribute less than <0.2 μg/m3 to nonattainment in Tennessee, and those States were not included in this analysis. 

EPA established CAIR emission budgets for SO2 (Table 5- 4) to reduce the contribution of 

upwind States to downwind nonattainment areas to below the significance threshold of 0.2 

μg/m3

. Sulfur dioxide emissions are reduced in two phases, with an initial reduction of Title IV 

(Acid Rain Program) allowance levels by 50 percent in 2010. An additional second-phase 

reduction of Title IV allowances will occur in 2015, bringing the total SO2 reduction to 65 

percent from Title IV Phase II allowance levels. The magnitude of SO2 reduction required to 

meet the 2010 CAIR budget is about three times greater than the observed emissions reductions 

between 2000 and 2006, but actual SO2 emissions are expected to remain above the cap for 

several years, until the existing bank of Title IV allowances is depleted. Air quality modeling 

conducted by EPA in support of CAIR indicates that reduction of interstate transport of PM2.5

precursors will reduce ambient PM2.5 concentrations by 1.28 μg/m3

 in the Knoxville area23, 

compared to EPA’s base case. 

 

22 EPA prepared a 2001 emission inventory from a combination of several different data sources, including continuous emissions monitoring for 

EGUs, MOBILE6.2 and Draft NONROAD 2004 models for onroad and nonroad mobile sources, and various estimates and projections for nonEGU and stationary area source emissions. The 2010 and Base Case reflects the net effects of economic growth and emissions reductions, 

compared to the 2001 emission inventory. 

23 See Table VI-10 in the CAIR final rule. 
62 

Table 5- 4: CAIR Annual SO2 State Trading Budgets 

for Tennessee and Surrounding States 

State 

CAIR Annual SO2 State 

Trading Budget for 2010-

2014 (tons) 

CAIR Annual SO2

State Trading Budget 

for 2015 and 

thereafter (tons) 

2010-2014 CAIR Budget, 

% Reduction from 2006 

Emissions 

Alabama 157,582 110,307 65.4% 

Georgia 213,057 149,140 66.5% 

Illinois 192,671 134,869 31.3% 

Indiana 254,599 178,219 69.0% 

Kentucky 188,773 132,141 55.9% 

North Carolina 137,342 96,139 70.3% 

Ohio 333,520 233,464 65.3% 

Tennessee 137,216 96,051 47.1% 

West Virginia 215,881 151,117 52.5% 

Totals 1,947,860 1,363,499 61.6% 

Tennessee and States found to contribute significantly to at least one nonattainment county in 2010 base case, based on EPA CAIR air quality 

modeling results. CAIR SO2 emission budgets are based on 2010 Title IV (Acid Rain Program) allowance allocations, with a 50% reduction in 

the value of Title IV allocations in 2010 and a 65% reduction in value in 2015. 

The Clean Air Interstate Rule does not mandate the use of any specific control technology, and 

affected sources may comply by installing controls or purchasing emission allowances. The 

Tennessee Valley Authority has begun engineering or construction on several EGUs in the TVA 

system, as indicated in Table 5- 5. Projected changes in TVA’s SO2, NOX, and particulate matter 

emissions are shown in Table 5- 6. 

Table 5- 5: CAIR SO2 Controls at Tennessee Valley Authority EGUs 

Facility 2006 SO2

Emissions (tons) 

2006 SO2

Emission Rate 

(lb/MMBtu) 

Controls 

Allen 17,413 0.62 None planned 

Bull Run 27,987 1.24 Wet scrubber construction began 2005; with 

completion expected by December 2008. 

Cumberland 18,352 0.20 Existing wet scrubbers 

Gallatin 23,459 0.62 None planned 

John Sevier 30,126 1.21 Wet scrubber construction scheduled to begin 

in 2008, with completion expected in 2012. 

Johnsonville 86,793 1.95 None planned 

Kingston 55,473 1.04 Wet scrubber construction is ongoing, with 

completion expected by December 2009 

(Units 6 through 9) and December 2010 

(Units 1 through 5). ASIP modeling for this 

facility assumed that there would be no addon controls in place during the 2009 

attainment year. 
63 

Table 5- 6: Projected Changes in TVA Emissions

Facility Name 

PM2.5 Emissions (tons) SO2 Emissions (tons) NOX Emissions (tons) 

2002 Act. 2002 Typ. 2009 2002 Act. 2002 Typ. 2009 2002 Act. 2002 Typ. 2009 

Allen 458 461 518 19,030 18,413 21,263 14,510 14,226 2,061 

Bull Run 1,872 1,629 2,212 42,188 36,729 8,657 17,909 15,592 2,078 

Cumberland 797 751 736 16,661 16,519 24,009 49,939 49,324 5,762 

Gallatin 563 548 548 34,157 33,520 47,391 11,782 11,520 11,461 

John Sevier 77 78 73 35,488 36,345 32,327 10,234 10,472 10,109 

Johnsonville 5,074 4,769 5,558 108,789 102,302 22,216 23,879 22,454 13,329 

Kingston 3,217 3,156 3,391 77,571 76,055 71,120 26,089 25,678 3,238 

Base G/G2 emission inventory. 

5. 2. Nonroad Mobile Sources 

A variety of Federal nonroad mobile source emissions reduction initiatives will result in reduced 

emissions from nonroad sources, including lawnmowers and garden equipment, farm equipment 

and construction equipment. 

In 1994, EPA adopted the first set of emission standards (Tier 1) for all new nonroad diesel 

engines greater than 37 kilowatts (50 horsepower), except those used in locomotives and marine 

vessels. EPA also phased in more stringent “Tier 2” emission standards from 2001 to 2006 for 

all engine sizes and added more stringent “Tier 3” standards for engines between 37 and 560 kW 

(50 and 750 horsepower) from 2006 to 2008. The EPA estimates these standards will further 

reduce nonroad diesel engine emissions by 60% for NOX and 40% for particulate matter from the 

1994 Tier 1 emission levels24. 

In addition to controls on nonroad diesel engines, EPA is phasing in a set of controls for nonroad 

spark ignition engines. Starting in 2007, manufacturers will need to meet more stringent 

standards which will result in a 90% reduction in NOX, HC, and CO emissions25. Additional 

controls will reduce evaporative hydrocarbon emissions from gasoline fuel tanks.

5. 3. Onroad Mobile Sources 

Onroad mobile sources in the Knoxville Nonattainment Area are estimated to contribute only 

about 2.5% of the total directly emitted PM2.5 in 2009. Several Federal motor vehicle control 

measures in place will substantially decrease the amount of pollution from new cars and trucks. 

These measures will significantly reduce pollution from the onroad mobile source sector in the 

future. 

New federal emissions standards for onroad heavy-duty diesel engines and vehicles, beginning in 

2004, will contribute significantly to reductions in NOX and VOC emissions. Additionally, the 

effects of other national programs, like the new standards for gasoline and diesel fuel sulfur 

 

24 U. S. EPA. Program Update Reducing Air Pollution from Nonroad Engines. April 2003. US EPA EPA420-F-03-011. 

25 Ibid. 
64 

content, will contribute to the decrease in emissions. EPA’s program for onroad heavy duty 

diesel engines is expected to result in NOX and particulate matter reductions of around 90%. As 

the fleet of vehicles nationally, and in the Knoxville area, is replaced with newer and cleaner 

vehicles, the emissions from these vehicles should reduce on a grams per mile basis. 

5.3a. Tier 2 Vehicle Standards 

Federal standards for National Low Emission Vehicles (NLEV) began in 1999, and implemented 

through 2001 for new light duty cars and trucks. EPA has since implemented further reductions 

from onroad mobile sources; the Federal Tier 2 vehicle emission standards. Federal Tier 2 

vehicle emission standards will require all passenger vehicles in a manufacturer’s fleet, including 

light-duty trucks and Sport Utility Vehicles (SUVs), to meet an average standard of 0.07 grams 

of NOX per mile in 200726. The Tier 2 standards will also cover passenger vehicles over 8,500 

pounds gross vehicle weight rating (the larger pickup trucks and SUVs), which are not covered 

by the current Tier 1 regulations. For these vehicles, the standards will be phased in beginning in 

2008, with full compliance in 2009. The new standards require vehicles to be 77% to 95% 

cleaner than those on the road today. The Tier 2 rule also reduced the sulfur content of gasoline 

to 30 ppm starting in January of 2006. Most gasoline sold in Tennessee prior to January 2006 

had a sulfur content of up to 300 ppm. Sulfur occurs naturally in gasoline but interferes with the 

operation of catalytic converters on vehicles, resulting in higher NOX emissions. The 

combination of lower-sulfur gasoline and the Tier 2 engine emissions standards are necessary to 

achieve the Tier 2 vehicle emission standards. 

5.3b. Heavy-Duty Gasoline and Diesel Highway Vehicle Standards 

New EPA standards designed to reduce NOX and VOC emissions from heavy-duty gasoline and 

diesel highway vehicles began to take effect in 2004. A second phase of standards, beginning in 

2007, will reduce particulate matter from heavy-duty highway engines, and will also reduce 

highway diesel fuel sulfur content to 15 ppm, allowing for additional emission control devices. 

The total program, when fully implemented (by 2030), is expected to achieve a 90% reduction in 

particulate matter (PM) emissions and a 95% reduction in NOX emissions for these new engines 

using ultra low sulfur diesel, compared to existing engines using higher sulfur content diesel27. 

5.3c. Statewide Motor Vehicle Anti-Tampering Rule 

Effective in 2005, the Tennessee Air Pollution Control Board promulgated a statewide motor 

vehicle anti-tampering rule. This rule, defined in Chapter 1200-3-36, Motor Vehicle Tampering, 

was promulgated to reduce the air pollution caused by tampering with a motor vehicle’s 

emissions control system. The area of applicability for this rule is statewide. Chapter 1200-3-36 

defines tampering as modifying, removing or rendering inoperative any air pollution emission 

control device, which results in an increase in emissions beyond established federal motor 

vehicle standards. Additionally, the rule identifies what is specifically prohibited (example: 

removing a catalytic converter). 

 

26Environmental Protection Agency, Federal Register, Vol. 65, No. 28, February 10, 2000. 

27Environmental Protection Agency, Federal Register, Vol. 66, No. 12, January 18, 2001. 
65 

5.3d. Stage I Vapor Recovery 

Tennessee has promulgated rules for Stage I Gasoline Vapor Recovery for several counties 

throughout Tennessee, including Anderson, Blount, Jefferson, Knox, Loudon, and Sevier 

Counties. Gasoline dispensing stations in these counties that were existing sources on December 

29, 2004, were required to comply with this rule by May 1, 2006. 
66 

6.0 RACT/RACM ANALYSIS 

40 CFR 51 Subpart Z states that SIPs must include provisions for reasonably available control 

measures (RACM), reasonably available control technology (RACT), and reasonable further 

progress (RFP), as necessary to demonstrate attainment. States must demonstrate that they have 

adopted all reasonably available control measures (including RACT for stationary sources) 

necessary to demonstrate attainment as expeditiously as practicable and to meet any RFP 

requirements. The SIP revision must contain the list of control measures considered by the State, 

and information and analysis sufficient to support the State's judgment that it has adopted all 

RACM, including RACT. In determining whether specific control measures must be adopted as 

RACM, States must consider the cumulative impact of implementing the available measures. 

Potential measures that are reasonably available considering technical and economic feasibility 

must be adopted as RACM if, considered collectively, they would advance the attainment date 

by one year or more. 

The PM2.5 Implementation Rule provides additional guidance for the identification of appropriate 

RACT and RACM. The guidance states that a State must consider RACT and RACM for all of 

its nonattainment areas, but that if the State projects that an area will attain the standard within 

five years of designation as a result of existing national measures, then the State may conduct a 

limited RACT and RACM analysis that does not involve additional air quality modeling. A 

limited analysis of this type would involve: 

• Review of reasonably available measures; 

• Estimation of potential emissions reductions; and 

• Evaluation of the time needed to implement these measures. 

If the State cannot achieve significant emissions reductions during 2008, due to time needed to 

implement the potential measures or other relevant factors, then the State may conclude that 

there are no further reasonably available control measures that would advance the attainment 

date by one year or more. 

6.1. SO2 and Direct PM2.5 RACT for Point and Area Sources 

Tennessee has established specific limits on particulate matter pursuant to Chapters 1200-3-6 and 

1200-3-7 of the Tennessee Air Pollution Control Regulations (TAPCR). Similarly, sulfur 

dioxide emissions from point and area sources are regulated by TAPCR 1200-3-14. These rules 

are part of Tennessee’s State Implementation Plan and are Federally enforceable. Because the 

specific limits for these pollutants were established by rulemaking, a rule change is required to 

implement more stringent SO2 or PM2.5 emission limits for most existing sources28. This is a 

lengthy process, which includes preparation of draft rule changes, public participation, and 

adoption by the Tennessee Air Pollution Control Board, followed by detailed review of the rule 

changes by Tennessee’s Attorney General and Secretary of State. Tennessee’s rulemaking 

 

28 Tennessee can establish more stringent particulate matter and SO2 emission limits for new sources that are subject to Tennessee’s Prevention 

of Significant Deterioration (PSD) or Nonattainment New Source Review (NNSR) programs. 
67 

experience indicates that this process requires at least twelve months, and that the adoption of 

new rules could not be completed by the end of 2008. Tennessee did conduct a limited review of 

possible RACT options for point and area sources in the Knoxville nonattainment area, which is 

included with Attachment I. 

6.2. PM2.5 RACT/RACM for Mobile Sources 

The statutory RACM requirement can be found in Section 172(c)(1) of the Clean Air Act, which 

directs states to “provide for implementation of all reasonably available control measures as 

expeditiously as practicable.” The regulatory RACT/RACM requirement for a PM2.5 SIP 

revision can be found at 40 C.F.R. Section 51.1010: 

(a) For each PM2.5 nonattainment area, the State shall submit with the attainment 

demonstration a SIP revision demonstrating that it has adopted all reasonably 

available control measures (including RACT for stationary sources) necessary to 

demonstrate attainment as expeditiously as practicable and to meet any RFP 

requirements. The SIP revision shall contain the list of the potential measures 

considered by the State, and information and analysis sufficient to support the 

State's judgment that it has adopted all RACM, including RACT. 

(b) In determining whether a particular emission reduction measure or set of 

measures must be adopted as RACM under section 172(c)(1) of the Act, the State 

must consider the cumulative impact of implementing the available measures. 

Potential measures that are reasonably available considering technical and 

economic feasibility must be adopted as RACM if, considered collectively, they 

would advance the attainment date by one year or more. 

With regards to RACT/RACM evaluation on the nonroad and onroad mobile sectors, Tennessee 

believes that measures to reduce PM2.5 from onroad and nonroad engines would not be practical, 

cost effective, or achievable in a timely fashion to expedite attainment of the PM2.5 NAAQS in 

the Knoxville PM2.5 Nonattainment Area. All onroad and nonroad engines combined are 

expected to contribute less than seven percent of the total PM2.5 emissions in the projected 2009 

emissions inventory. Any control measure for these engines would provide a negligible amount 

of reductions, which would not expedite attainment of the PM2.5 NAAQS. There are significant 

reductions expected from these sectors from existing Federal measures affecting both fuels and 

engines. In addition, an I/M program for onroad heavy-duty diesel engines is not viable since a 

large proportion of heavy-duty diesel trucks (tractor-trailer type) travel through the Knoxville 

region from other States. Tennessee is limited in its ability to affect an enforcement program on 

vehicles which are registered outside of the nonattainment area. For onroad light-duty vehicles, 

an I/M program is not practical since the total impact from onroad vehicles to the PM2.5

inventory in the Knoxville PM2.5 Nonattainment area in 2009 is less than three percent. Only a 

small fraction of this amount could be reduced through an inspection and maintenance (I/M) 

program. 

Tennessee has determined that there are no additional control measures that could be adopted by 

January 1, 2009 that would lead to earlier attainment. Further, existing measures, and those 
68 

planned for implementation by 2009, are expected to bring the region to attainment with the 

PM2.5 NAAQS. As such, no further actions on RACT/RACM are warranted. 

The modeled attainment demonstration presented in Section 8.0 demonstrates that the cumulative 

impact of the control measures described in Section 5.0 will be sufficient to comply with the 

PM2.5 NAAQS by April 2009. Therefore, the Knoxville area has implemented all of the 

necessary measures to demonstrate attainment as expeditiously as practicable and to meet any 

RFP requirements, and no additional measures are necessary. 

As demonstrated by the emission inventory, modeled attainment demonstration, and contingency 

measures, PM2.5 in the Knoxville area results primarily from emissions of sulfur dioxide and 

organic carbon. Substantial reductions of local and regional SO2 emissions will occur by 2009 as 

utilities install controls to comply with CAIR. The available information indicates that there are 

no additional control measures that would advance the attainment date by one year or more. 

Tennessee will continue to implement the control measures described in Section 5.0 to attain the 

PM2.5 NAAQS. 
69 

7.0 MOTOR VEHICLE EMISSIONS BUDGETS 

7.1. Transportation Conformity 

The purpose of transportation conformity is to ensure that Federal transportation actions 

occurring in nonattainment and maintenance areas do not hinder the area from attaining and 

maintaining the National Ambient Air Quality Standards (NAAQS). This means that the level of 

emissions estimated by the metropolitan planning organizations or the Tennessee Department of 

Transportation (TDOT) for the Transportation Improvement Program (TIP) and Long Range 

Transportation Plan (LRTP) must not exceed the motor vehicle emission budgets (MVEB) 

defined in this attainment demonstration. The MVEB was developed through consultation with 

the Interagency Consultation Partners. The annual vehicle miles travelled for 2009 were 

obtained from the Knoxville Transportation Planning Organization’s (TPO) most recent 

conformity determination as presented in Table 7- 1. Further discussion is included in 

Attachment D of the SIP documentation. 

Table 7- 1: Total 2009 Annual Vehicle Miles Traveled in the Knoxville PM2.5

Nonattainment Area 

County 

Annual VMT 

(miles/year) 

Anderson 1,027,637,421 

Blount 1,241,047,135 

Knox 5,631,483,556 

Loudon 924,090,349 

Roane* 91,235 

Total: 8,824,349,696 

*Nonattainment area portion of Roane County only 

EPA’s Guidance for Creating Annual On-Road Mobile Source Emissions Inventories for PM2.5

Nonattainment Areas for Use in SIPs and Conformity29 was followed to develop the onroad 

emissions inventories. Key planning assumptions were developed through interagency 

consultation. For example, it was determined that an annual average modeling run to generate 

emission factors is a reasonable representation of the annual emissions for PM2.5 and its 

precursors. Additionally, annual average minimum and maximum temperatures were developed 

during the initial PM2.5 transportation conformity determination for the Knoxville Region 

(50.1/70.0 °F). 

To model the mobile source emissions in the Knoxville nonattainment area, the newest version 

of the MOBILE model, MOBILE6.2, was used. The MOBILE6.2 input and output files are 

included in Attachment D of the SIP documentation. The emissions factors produced by the 

MOBILE6.2 model are also contained in Attachment D, Air Quality Conformity Determination 

Report (September 24, 2007), Appendix B.5. Onroad emissions totals by county are summarized 

in Appendix B.5 of this same document. The Off-Model Analysis for Roane County is 

 

29 EPA420-B-05-008, August 2005 
70 

contained in the Air Quality Conformity Determination (March 22, 2006), Appendix E; the VMT 

and emission factors are contained in Appendix C2.6. 

7.2. PM2.5 Motor Vehicle Emission Budget 

As part of the consultation process on setting MVEBs, the consultation partners discussed the 

geographic extent of the MVEB. It was decided through Interagency Consultation (IAC) that a 

regional emissions budget would be the most appropriate for the Knoxville nonattainment area. 

The mobile inputs used to develop the attainment demonstration modeling as well as the MVEB 

were developed through interagency consultation with the transportation partners for this area. 

Emissions developed through the attainment demonstration modeling were used in evaluating the 

various precursors since precursor information was available and extensive modeling and 

sensitivity analysis was conducted on this inventory. The MVEB is developed from modeling 

conducted by the Knoxville Transportation Planning Organization (TPO) so that the MVEB 

development is as consistent as possible with the methods used to determine conformity. Note, 

however, the Onroad Mobile emissions estimates from the attainment demonstration do not 

exactly match those numbers used to develop the MVEB which comes from the TPO's most 

recent conformity determination. Slight differences in VMT contribute, in part, to differences in 

emissions between the two modeling efforts. Between the time modeling was conducted by 

ASIP and the most recent work done by the Knoxville TPO, a number of highway projects were 

delayed or changed, resulting in changes to the projected VMT. Also, treatment of the emissions 

by the photochemical model, and the way emissions are developed through the different models, 

inherently leads to different results. These small differences are a product of the different 

modeling approaches, and in no way hinder the timely attainment of the NAAQS. 

Pursuant to the EPA’s transportation conformity rule in 40 CFR Part 93, specific emission 

budgets are hereby defined for the onroad mobile sources portion of the emissions inventory. 

The MVEB, for transportation conformity purposes for the Knoxville PM2.5 nonattainment area 

for 2009 is contained in Table 7- 2 below. This budget is to be used by the transportation 

authorities to assure that transportation plans, programs, and projects are consistent with, and 

conform to, the attainment and maintenance of acceptable air quality in the Knoxville area. This 

MVEB applies to the entire Knoxville PM2.5 nonattainment area, including the donut area 

contained in Roane County. 

Table 7- 2: PM2.5 MVEB for 2009 

Pollutant: 2009 MVEB 

(tons/year) 

PM2.5 283.63 
71 

7.3. Presumed Precursors for PM2.5 

EPA’s Clean Air Fine Particulate Implementation Rule30 (Implementation Rule) in §51.1002 

outlines EPA’s presumptive policy that SO2 and NOX are significant unless demonstrated 

otherwise by the State. Specifically, the Implementation Rule states: 

“(1) The State must address sulfur dioxide as a PM2.5 attainment plan precursor 

and evaluate sources of SO2 emissions in the State for control measures.” 

SO2 has been considered for control programs from point sources. SO2 emissions from onroad 

mobile sources are discussed below. 

The rule continues: 

“(2) The State must address NOX as a PM2.5 attainment plan precursor and 

evaluate sources of NOX emissions in the State for control measures, unless the 

State and EPA provide an appropriate technical demonstration for a specific area 

showing that NOX emissions from sources in the State do not significantly 

contribute to PM2.5 concentrations in the nonattainment area.” 

Tennessee believes NOX to be an insignificant PM2.5 attainment plan precursor as previously 

discussed in Section 3.0. 

Regarding Volatile Organic Compounds (VOCs), the Implementation Rule states: 

“(3) The State is not required to address VOC as a PM2.5 attainment plan 

precursor and evaluate sources of VOC emissions in the State for control 

measures, unless: (i) the State provides an appropriate technical demonstration for 

a specific area showing that VOC emissions from sources in the State 

significantly contribute to PM2.5 concentrations in the nonattainment area, and 

such demonstration is approved by EPA; or (ii) The EPA provides such a 

technical demonstration” 

Tennessee discusses VOC below. 

In addition, the Implementation Rule provides that States do not need to address ammonia as a 

PM2.5 attainment plan precursor: 

“(4) The State is not required to address ammonia as a PM2.5 attainment plan 

precursor and evaluate sources of ammonia unless: (i) the State provides an 

appropriate technical demonstration for a specific area showing that ammonia 

emissions from sources in the State significantly contribute to PM2.5

concentrations in the nonattainment area, and such demonstration is approved by 

EPA; or (ii) The EPA provides such a technical demonstration.” 

Ammonia is discussed below. 

 

30 EPA Clean Air Fine Particle Implementation Rule 40 CFR Part 51 EPA-HQ-2003-0062; FRL-RIN 2060-AK74 
72 

Road and construction dust is also discussed below. The State concurs with EPA’s opinion 

outlined in the Implementation Rule that road and construction dust, or “crustal material” is 

“only a minor part of the PM2.5 annual average concentrations.” as discussed below. 

7.3a. Volatile Organic Compounds (VOC) 

EPA’s final implementation rule explains that States are not required to address VOC in PM2.5

implementation plans and evaluate control measures for such pollutants unless the State or EPA 

makes a technical demonstration that emissions of VOCs from sources in the State significantly 

contribute to PM2.5 concentrations in a given nonattainment area. 

EPA’s Clean Air Fine Particulate Implementation Rule explicitly states that “significant 

contribution” to the nonattainment area’s PM2.5 concentration means that a significant change in 

emissions of the precursor from sources in the state would be projected to provide a significant 

change in PM2.5 concentrations in the nonattainment area”31. 

Tennessee has examined the sources of VOC emissions and their contribution to PM2.5 in 

Knoxville Nonattainment Area. Due to the generally warm and moist climate of Tennessee, 

vegetation abounds in many forms, and forested lands cover much of the state. The biogenic 

sector is the most abundant source of VOC emissions in Tennessee and accounts for the majority 

of VOC emissions. 

Tennessee believes that highway mobile VOCs are insignificant contributors to PM2.5 formation 

in the Knoxville nonattainment area. Emission estimates indicate that highway mobile VOC is a 

small percentage of the total VOC emissions inventory. Highway mobile VOC emissions are 

projected to decrease into the future, despite VMT increases. For these reasons, Tennessee 

presented the VOC insignificance concept to the transportation partners, and agreed through the 

interagency consultation, that VOC emissions are insignificant. Therefore, Tennessee will not 

set a MVEB for VOC for the Knoxville nonattainment area. 

7.3b. Ammonia (NH4)

EPA’s policy on ammonia presumes that ammonia is not a PM2.5 attainment plan precursor. The 

State is not required to address ammonia in its attainment plan or evaluate sources of ammonia 

emissions for reduction measures unless a technical demonstration by the State or EPA shows 

that ammonia emissions from sources in the State significantly contribute to PM2.5

concentrations in a given nonattainment area or to downwind air quality. Tennessee agrees with 

EPA’s policy regarding the uncertainty regarding the emissions inventories and potential 

efficacy of control measures for ammonia. 

7.3c. Nitrogen Oxides (NOX) 

Nitrogen Oxides as a PM2.5 precursor was discussed in Section 3.0, NOX Insignificance. As 

indicated in Section 3.11, EPA has indicated that NOX should be considered a significant 

 

31 EPA Clean Air Fine Particle Implementation Rule 40 CFR Part 51 EPA-HQ-2003-0062; FRL-RIN 2060-AK74 
73 

precursor to PM2.5 formation. A motor vehicle emissions budget for NOX is presented in 

Attachment Q. 

7.3d. Road and Construction Dust 

Tennessee agrees with EPA’s assessment in the July 1, 2004 Federal Register: Transportation 

Conformity Rule Amendments for the New 8-hour Ozone and PM2.5 National Ambient Air 

Quality Standards and Miscellaneous Revisions for Existing Areas; Transportation Conformity 

Rule Amendments: Response to Court Decision and Additional Rule Changes: Final Rule where 

EPA states on page 40034 that evidence suggests that re-entrained road dust is likely to have a 

relatively small impact on PM2.5 compared to PM10 in general. 

Further in the same rule, on page 40036 EPA states that “...construction dust will not be 

significant in all areas...”. Tennessee agrees with this that construction dust is not a significant 

concern in Tennessee. In addition, EPA’s Clean Air Fine Particle Implementation Rule states: 

“...crustal material is only a minor part of PM2.5 annual average concentrations.” From 

SANDWICH data illustrated in the NOX Insignificance Demonstration, all crustal material 

constitutes from three to six percent of the total PM2.5 mass captured at area monitors. Road and 

construction dust constitute a small fraction of this amount. 

Tennessee’s temperate climate and relatively few unpaved roads leave little opportunity for road 

or construction dust to become significant contributors to PM2.5. In addition, generally regular 

rainfall removes dust from paved roads and helps keep unpaved roads from becoming a source of 

significant PM2.5 crustal material. 

7.4. Onroad Mobile Source Precursor Significance and Insignificance 

Section 93.109(k) in the Transportation Conformity Rule Amendments for the new 8-hour ozone 

and fine particulate matter NAAQS addresses areas with insignificant motor vehicle emissions 

and how those determinations should be made. The rule suggests that such a finding would be 

based on a number of factors, including the percentage of motor vehicle emissions in the context 

of the total SIP inventory, the current state of air quality as determined by monitoring data for 

that NAAQS, the likelihood of future motor vehicle control measure implemented for a given 

pollutant or pollutant precursor, and historical trends and future projections of the growth of 

motor vehicle emissions. 

7.4a. Sulfur Oxides (SOX) 

EPA’s Clean Air Fine Particle Implementation Rule states: “Sulfur oxides are mostly emitted 

from the combustion of fossil fuels in boilers operated by electric utilities and other industry. 

Less than 20 percent of SO2 emissions nationwide are from other sources, mainly other industrial 

processes such as oil refining and pulp and paper production” EPA also states that sulfur dioxide 

emissions from motor vehicles would not necessitate a budget since the “de minimis levels of 

sulfur dioxide emissions from on-road vehicles currently, and took into consideration the fact 

that sulfur dioxide emissions from on-road sources will decline in the future due to the 

implementation of requirements for low-sulfur gasoline (which began in 2004) and for low sulfur 

diesel fuel (beginning in 2006).” Tennessee agrees with EPA, and therefore, there will not be a 
74 

motor vehicle budget set for SOX. 

An affirmative insignificance finding from the EPA only relieves the transportation partners 

from a regional emissions analysis for insignificant emissions for this area and does not relieve 

them of the other transportation conformity requirements. The transportation partners will need 

to note the insignificance finding (if found adequate and approved by the EPA) in future 

conformity determinations. 
75 

8.0 MODELED ATTAINMENT DEMONSTRATION 

A modeled attainment demonstration consists of analyses which estimate whether selected 

emissions reductions will result in ambient concentrations that meet the NAAQS and an 

identified set of control measures which will result in the required emissions reductions. 

Emission reduction strategies are typically simulated by reducing emissions from specific source 

categories. The amount of emission reduction needed to demonstrate attainment of the NAAQS 

is estimated using the modeled attainment test. EPA suggests that States consider a broader set 

of model results and perform corroboratory analyses to support whether a proposed control 

strategy will lead to attainment of the NAAQS. 

8.1. ASIP Workgroup 

Southeastern States Air Resource Managers, Inc. (SESARM), is a Georgia corporation organized 

and operated under the provisions of the Official Code of Georgia Annotated, Title 14, Chapter 

3. SESARM directly represents the eight southeastern State air pollution control agencies32 

located within EPA Region 4. SESARM’s Board of Directors consists of the air pollution 

control agency director from each state air pollution control agency. 

EPA promulgated regional haze regulations on July 1, 1999, and established requirements that 

States and tribes submit implementation plans to demonstrate reasonable progress towards the 

ultimate visibility goals of the rule. To allow for more cost-effective analyses, EPA offered an 

optional approach for groups of States to collaborate in regional analyses of the haze problem. 

The SESARM member agencies, plus Virginia and West Virginia, determined that a 

collaborative effort was appropriate for regional haze and formed the Visibility Improvement 

State and Tribal Association of the Southeast (VISTAS). VISTAS member agencies work 

together on a variety of engineering, administrative, and organizational haze-related tasks. 

On December 17, 2004, EPA designated at least one area as nonattainment for the PM2.5

NAAQS in seven southeastern States: Alabama, Georgia, North Carolina, Kentucky, Tennessee, 

Virginia, and West Virginia. EPA guidance indicates that a significant requirement of PM2.5

SIPs will be attainment demonstrations using modeling and other analyses to define effective 

emissions control strategies and to confirm attainment with the NAAQS. 

Because the PM2.5 attainment demonstration requires modeling for 2009, which is also an interim 

analysis year for regional haze, VISTAS States concluded that a collaborative process would be 

an efficient approach for PM2.5 work. The name of this collaborative effort is the Association for 

Southeastern Integrated Planning (ASIP). SESARM was awarded a grant from EPA on February 

8, 2005, to conduct ASIP work. 

PM2.5 modeling was performed by the ASIP workgroup for ten Southeastern States, including 

Tennessee. This modeling was conducted as indicated in the ASIP Modeling Protocol 

(Attachment C), as summarized in the following paragraphs. 

 

32 These States are: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, and Tennessee. 
76 

8.2. Model Selection 

Based on the findings in the VISTAS Phase I and II modeling activities, ASIP selected the 

following models for use in PM2.5modeling: 

• MM5: The Pennsylvania State University/National Center for Atmospheric Research 

(PSU/NCAR) Mesoscale Meteorological Model (MM5) is a nonhydrostatic, 

prognostic meteorological model routinely used for urban- and regional-scale 

photochemical, fine particulate, and regional haze regulatory modeling studies. 

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

is an emissions modeling system that generates hourly gridded speciated emission 

inputs of mobile, nonroad, area, point, fire and biogenic emission sources for 

photochemical grid models. 

• CMAQ: EPA’s Models-3/Community Multiscale Air Quality (CMAQ) modeling 

system is a ‘One-Atmosphere’ photochemical grid model capable of addressing 

ozone, particulate matter (PM), visibility and acid deposition at regional scale for 

periods up to one year. 

8.2a. MM5 Overview 

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

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

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

more than 20 years and has been used for a variety of mesoscale studies. 

 

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

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

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

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

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

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

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

Distinct planetary boundary layer (PBL) parameterizations are available for air-quality 

applications, both of which represent sub-grid-scale turbulent fluxes of heat, moisture and 

momentum. One scheme uses a first-order eddy diffusivity formulation for stable and neutral 

environments and a modified first-order scheme for unstable regimes. The other uses a 

prognostic equation for the second-order turbulent kinetic energy, while diagnosing the other key 

boundary layer terms. 

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

user. Surface fields are analyzed at three-hour intervals. A Cressman-based technique is used to 
77 

analyze standard surface and radiosonde observations, using the National Meteorological 

Center's spectral analysis, as a first guess. The lateral boundary data are introduced using a 

relaxation technique applied in the outermost five rows and columns of the coarsest grid domain. 

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

quality application studies have been widely reported in the literature and many have involved 

comparisons with other prognostic models such as RAMS and SAIMM. The MM5 enjoys a 

richer application history in regulatory modeling studies compared with RAMS or other models. 

Furthermore, in evaluations of these models in over 60 recent regional scale air quality 

application studies since 1995, MM5 tends to produce somewhat better photochemical model 

inputs than alternative models. 

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

the MM5 model, can be found in the ASIP Modeling Protocol (Attachment C) and in the MM5 

Report (Attachment J). 

8.2b. SMOKE Overview 

The SMOKE Emissions Processing System Prototype was originally developed at the Microcomputing Center of North Carolina. SMOKE is principally an emission processing system and 

not a true emissions modeling system in which emissions estimates are simulated from ‘first 

principles’. This means that, with the exception of mobile and biogenic sources, its purpose is to 

provide an efficient, modern tool for converting emissions inventory data into the formatted 

emission files required by an air quality simulation model. For mobile sources, SMOKE 

simulates emissions rates based on input mobile source activity data, emission factors, and 

outputs from transportation travel demand models. 

 

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

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

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

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

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

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

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

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

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

processing. 

 

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

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

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

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

countries and any pollutant can be processed by the system. 

Additional information about the SMOKE model may be found in the ASIP Modeling Protocol 

(Attachment C). 
78 

8.2c. CMAQ Overview 

The photochemical model selected for this study was CMAQ version 4.533. EPA has been 

developing the Models-3 CMAQ modeling system for more than a decade, with the aim of 

producing a “one-atmosphere” air quality modeling system capable of addressing ozone, fine 

particulate matter, visibility and acid deposition within a common platform. The original 

justification for the Models-3 development emerged from the challenges posed by the 1990 

Clean Air Act Amendments, and from EPA’s desire to develop an advanced modeling 

framework for ‘holistic’ environmental modeling utilizing state-of-science representations of 

atmospheric processes in a high performance computing environment. EPA completed the initial 

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

science model under the Models-3 framework. The most recent rendition is CMAQ version 4.4, 

which was released in October 2004. 

 

Another reason for choosing CMAQ as the atmospheric model is the ability to do oneatmospheric modeling. Since the same modeling exercise for the ozone and PM2.5 attainment 

demonstrations SIPs, as well as the regional haze SIP, having a model that can handle both ozone 

and particulate matter is essential. A number of features in CMAQ’s theoretical formulation and 

technical implementation make the model well suited for annual PM modeling. 

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

the CMAQ model, can be found in the ASIP Modeling Protocol (Attachment C). 

8.3. Modeling Year Selection for the PM2.5 Attainment Demonstration 

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

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

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

EPA’s guidance on PM2.5 modeling identifies specific goals to consider when selecting one or 

more episodes for use in demonstrating attainment of the PM2.5 NAAQS. EPA recommends that 

episode selection derive from three principal criteria: 

• The episode should cover a variety of meteorological conditions that lead to 

exceedances of the PM2.5 NAAQS; 

• To the extent possible, the modeling database should include days for which 

extensive data (i.e. beyond routine aerometric and emissions monitoring) are 

available; and 

 

33 During the course of the VISTAS Phase II and ASIP modeling, VISTAS updated the secondary organic aerosol (SOA) module in CMAQ to 

include important SOA processes missing in the standard CMAQ model. The updates significantly improved the OCM performance in the 

summer. The processes missing in the current standard versions of CMAQ, which were included as part of the SOAmods enhancement, are 

described in Section 1.3.3.3.1 of Attachment C (ASIP Modeling Protocol). EPA intends to address SOA issues in the fall 2008 CMAQ release, 

which is too late for PM2.5 SIP work. Thus, both VISTAS and ASIP have adopted CMAQ version 4.5 with SOAmods updates as the core model 

for the modeling analysis. 
79 

• Sufficient days should be available such that the modeled attainment test applied at 

each monitor violating the NAAQS is based on multiple days. 

 

For PM2.5 modeling, the preferred approach is to model a full, representative year. EPA also lists 

several other considerations to bear in mind when choosing PM2.5 modeling episodes including: 

(a) use of periods that have already been modeled; (b) periods that are drawn from the years 

upon which the current design values are based; (c) inclusion of weekend days; and (d) modeling 

periods that meet as many episode selection criteria as possible in the maximum number of 

nonattainment areas. The ASIP workgroup adopted a logical, stepwise approach in 

implementing the EPA guidance, in order to identify the most preferable year for PM2.5

modeling. 

The ASIP work group adopted a logical, stepwise approach in implementing the Attainment 

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

steps include the following: 

• Representativeness of Meteorological Conditions: The ASIP meteorological contractor 

(BAMS) identified important meteorological characteristics and data sets in the ASIP 

region directly relevant to the evaluation of candidate annual modeling episodes. 

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

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

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

modeling years (Attachment K). 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 visibility and PM2.5 concentrations in 2002 were representative of the fiveyear baseline period. 

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

collaborative investigations by VISTAS States intensively studied the availability of 

PM2.5, meteorological, and emissions data and representativeness of alternative baseline 

modeling periods from a regulatory standpoint. Additionally, 2002 was the year that 

EPA required States to provide emissions inventory data for the Comprehensive 

Emissions Reporting Rule (CERR), and the use of 2002 as the modeling year allowed the 

ASIP work group to take advantage of the 2002 inventory. 

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

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

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

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

representative, and pragmatic choice for modeling. All of EPA’s criteria for model year 

selection were considered in this process, as well as other considerations (e.g., timing of new 

emissions or aerometric data deliveries by EPA or States to the modeling teams). 
80 

8.4. Modeling Domain 

8.4a. Horizontal Modeling Domain 

The ASIP horizontal domains for each of the models were identical to those used in the VISTAS 

Phase I and II modeling. A coarse grid continental United States (US) domain with a 36-km 

horizontal grid resolution was used, and the CMAQ domain was nested in the MM5 domain. 

Figure 8- 1 shows the MM5 horizontal domain and the nested CMAQ 36-km domain. To achieve 

finer spatial resolution in the ASIP States, a one-way nested high resolution grid (12-km grid 

resolution) was used (Figure 8- 2). 

Figure 8- 1: MM5 Horizontal Domain (Blue) with Nested CMAQ 36-km Domain 
81 

Figure 8- 2: ASIP Region 12-km Grid 

8.4b. Vertical Modeling Domain 

The CMAQ vertical structure is primarily defined by the vertical grid used in the MM5 

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

using 34 layers that extend from the surface to the 100 mb. Table 8- 1 lists the layer definitions 

for MM5 and CMAQ. A layer averaging scheme is adopted for CMAQ to reduce the 

computational cost of the CMAQ simulations. The effects of layer averaging were evaluated in 

the VISTAS Phase I modeling effort and found to have a relatively minor effect on model 

performance when both 34-layer and 19-layer CMAQ models were compared to ambient 

monitoring data. 
82 

Table 8- 1: Vertical Layer Definition for MM5 Simulations and Approach For Reducing 

CMAQ Layers By Collapsing Multiple MM5 Layers 

MM5 CMAQ 19L

Layer Sigma Pres(mb) Height(m Depth(m) Layer Sigma Pres(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 0 1.000 1000 0 0

8.5. Emissions Data 

The Base G2 2002 emissions inventory was the basis for the ASIP modeling. These data were 

founded on 2002 Consolidated Emission Reporting Rule (CERR) inventories submitted to 

VISTAS and were reviewed by VISTAS stakeholders for completeness and accuracy. NonVISTAS state emissions were based on representative inventories obtained from other RPOs or 

EPA. Stationary source data were supplemented with EPA based VMT and MOBILE6 input 

files necessary to develop onroad mobile source emissions. Additionally, an inventory of point 

source resolved agricultural fire emissions were provided by the Western Regional Air 

Partnership (WRAP) and utilized in the modeling. Mexican and Canadian emissions were based 

on the latest available inventories obtainable in suitable formats. Actual 2002 calendar year 

emissions for EGU and fire activity will be used for air quality model validation. Strategy and 
83 

future year emission runs were based on “typical year” inventories for 2002 and future years. 

Emissions data were converted to Inventory Data Analyzer (IDA) formatted versions and 

processed for air quality modeling using Version 2.1 of the Sparse Matrix Operating Kernel 

Emissions (SMOKE) model. Temporal and speciation profiles and cross-reference data were 

included in these runs, augmented with recommended and approved emission profile data 

provided by the emissions inventory contractor, obtained from EPA, or prepared by the Study 

Team prior to initial emissions modeling. Spatial allocation of emissions was based on profiles 

and spatial allocation factors developed for the National RPO grid. 

8.6. Ozone Column Data 

Additional data used in the air quality modeling include the Total Ozone Mapping Spectrometer 

(TOMS). The day-specific TOMS data was used in the CMAQ radiation model to calculate 

photolysis rates. The TOMS data were missing or bad for several periods in 2002: August 2-12; 

June 10; and November 18-19. Thus, the TOMS data for August 1, 2002 was used for August 2-

7 and TOMS data for August 13 was used for August 8-12. Similarly, TOMS data for June 9 

was used for June 10 and data for August 17 was used for August 18-19. 

8.7. Meteorological Data 

Meteorological data were generated using the MM5 prognostic meteorological model by Baron 

Advanced Meteorological Systems (BAMS). BAMS operated the MM5 at 5-day increments for 

2002 on the 36-km and 12-km grids, with a 14-day spin up period for the end of December 2001. 

8.8. Initial and Boundary Conditions Data 

The CMAQ default Initial Concentrations (ICs) were used, with a 15-day spin-up period to 

eliminate any significant influence of the ICs. The CMAQ Boundary Conditions (BCs) for the 

Inter-RPO 36-km grid and the ASIP simulations were based on day-specific 3-hour averages 

from a 2002 GEOS-CHEM global simulation model output. Boundary conditions for the 12 km 

grid were based on CMAQ results from the 36 km grid processed with the CMAQ BCON 

boundary condition processor. Additional information on the GEOS-CHEM global simulation 

may be found in Attachment L. 

8.9. Quality Assurance 

In December 2002, EPA published extensive guidance on developing a Quality Assurance 

Project Plan (QAPP) for modeling studies to ensure that the studies are scientifically defensible. 

The guidance suggested the following elements for QAPPs: 

• a systematic planning process, including identification of assessments and related 

performance criteria; 

• peer reviewed theory and equations; 
84 

• a carefully designed life-cycle development process that minimizes errors; 

• clear documentation of assumptions, theory, and parameterization that is detailed enough 

so others can fully understand the model output; 

• input data and parameters that are accurate and appropriate for the problem; 

• output data that can be used to help inform decision making; 

• documentation of any changes from the original quality assurance plan; 

EPA’s guidance specified that the required quality assurance would depend on the intended 

application of the model, and that a modeling study designed for regulatory purposes would 

require the highest level of quality assurance. The modeling team subsequently developed QA 

documents and procedures in the ASIP modeling efforts. 

8.9a. Emissions Model Inputs and Outputs 

Quality Assurance (QA) and Quality Control (QC) are a critical part of all air quality modeling 

studies. Emissions processing is tedious and time consuming and involves complex manipulation 

of many different types of large data sets. Errors in emissions processing may remain undetected 

if rigorous QA measures are not in place. An “Emissions Gatekeeper” function was 

implemented in the ASIP modeling work to perform quality assurance activities on emission 

inventory data obtained from the ASIP emissions inventory contractors and inventory data used 

for modeling outside of the Southeastern States. 

The Emissions Gatekeeper reviewed the content and format of emission inventories to ensure an 

appropriate appraisal of the data. Other tasks included additional translation from mass emissions 

files into the emissions modeling input file structure. The Study Team supplemented these 

activities with QA checks on the intermediate and model output files, using internal and public 

domain visualization and diagnostic packages. 

8.9b. Meteorological Model Outputs 

As part of the ASIP effort, a “Meteorological Gatekeeper” function was implemented. The task 

of the Gatekeeper was to provide an independent review and quality assurance of the 

meteorological modeling and related data sets developed by the meteorological modeling 

contractor and used by the emissions and air quality modeling teams. The Gatekeeper QA 

review served two purposes: (a) to identify and correct potential problems with the data sets in a 

timely manner; and (b) to provide information to support ongoing CMAQ model performance 

testing and sensitivity analyses. The Gatekeeper’s analysis of the MM5 meteorological data sets 

served to provide direct assistance to the emissions and air quality modeling team as it worked to 

ratify the SMOKE model outputs and to diagnose CMAQ model performance. The 

Meteorological Gatekeeper was also responsible for the quality and chain of custody of the 

meteorological data sets. 
85 

8.9c. Air Quality Meteorological Model Inputs and Outputs 

Key aspects of quality assurance for the CMAQ input and output data included the following: 

• Verification that correct configuration and science options were used in compiling and 

running each CMAQ model. 

• Verification that correct input data sets were used to run each model. 

• Evaluation of results to verify that model output is reasonable and consistent with general 

expectations. 

• Processing of ambient monitoring data for use in the model performance evaluation. 

• Evaluation of the CCTM results against concurrent observations. 

• Backup and archiving of critical model input data. 

8.10. Model Performance Evaluation34 

A critical component of every air quality modeling study is the model performance evaluation 

where the modeled estimates for the current year base case are compared against observed values 

to assess the model’s accuracy and provide an indication of its reliability. The first step in the 

modeling process is to verify the model’s ability to correctly predict ambient PM2.5 

concentrations, including the correct mixture of individual components (e.g., sulfate, nitrate, 

ammonium, organic carbon, elemental carbon, and other PM2.5). Model predictions for the base 

year simulation are compared to the ambient data observed in the historical episode, using a 

combination of statistical and graphical evaluations. If the model appears to correctly predict 

ambient PM2.5 concentrations at various locations, then the model can be used as a predictive tool 

to evaluate the effect of control strategies on ambient PM2.5 levels. 

This section summarizes the model performance evaluation for the CMAQ 2002 36-km and 12-

km Base G2 Actual base case simulations. This model performance evaluation focuses on PM2.5

and its component species in PM2.5 nonattainment areas (NAAs), building upon prior work by 

the ASIP workgroup (formerly VISTAS35) for regional haze and ozone evaluations36. The 

VISTAS regional haze components and the ASIP urban ozone model performance evaluations 

are directly relevant to the ASIP PM2.5 evaluation, since they share many of the same 

precursor/product species and atmospheric processes that produce elevated PM2.5 levels in the 

 

34 This section is a summary of the Environ Model Performance Evaluation (January 2008), Chapter 3. For the full document, including relevant 

citations, see Attachment F. 

35 Visibility Improvement State and Tribal Association of the Southeast. 

36 The CMAQ 2002 Base G2 base case simulation was evaluated for PM species and visibility (primarily at Class I areas) as part of the VISTAS 

regional haze assessment. The VISTAS model evaluation focused on the performance of PM component species and visibility at more rural (e.g., 

IMPROVE) monitors. The ASIP work group also performed an urban ozone evaluation performance as part of the development of the 

southeastern States’ 8-hour ozone SIPs. Appendix B of Attachment F provides details on the ASIP urban and NAAs PM2.5 mass and PM2.5

component species model performance evaluation. Appendix C of Attachment F provides a qualitative evaluation of the CMAQ base case for 

PM2.5 components and total mass 
86 

nonattainment areas. 

8.10a. CMAQ 2002 Base G2 Model Evaluation Methodology 

VISTAS and ASIP share the same 2002 Base G2 Actual base case modeling results from the 

Community Multiscale Air Quality (CMAQ) modeling system37, and the VISTAS and ASIP 

base case evaluations are the product of numerous evaluations of predecessor CMAQ base case 

simulations. With the exception of Organic Carbon Mass (OCM)38, the basic features of the 

model performance evaluation have essentially remained unchanged from the initial VISTAS 

evaluations to the current 2002 Base G2 actual base case model performance. 

The CMAQ results in the VISTAS model performance evaluation were compared with 

observational data from various monitoring networks. VISTAS focused primarily on the air 

quality model’s performance with respect to individual components of fine particulate matter 

(PM2.5), since model performance with respect to PM component species dictates model 

performance for visibility effects. VISTAS also evaluated the ability of the model to reproduce 

gaseous PM precursor and product species. The ASIP model performance evaluation focuses on 

ozone and PM2.5 performance in urban and nonattainment areas (NAAs). The ASIP PM2.5 

evaluation is summarized in Attachment D, Sections 3.5 and 3.6, with more details provided in 

Appendices B and C of that Attachment. 

8.10b. Evaluation Approach 

EPA’s integrated ozone, PM2.5 and regional haze modeling guidance calls for a comprehensive, 

multi-layered approach to model performance testing, consisting of the four major components: 

operational, diagnostic, mechanistic (or scientific) and probabilistic. The CMAQ model 

performance evaluation effort for PM2.5 focuses on the first two components of the EPA’s 

recommended evaluation approach, namely: 

• Operational Evaluation: Tests the ability of the model to estimate PM2.5 mass 

concentrations and the components of PM2.5 (sulfate, nitrate, ammonium, organic carbon 

matter, elemental carbon, and other inorganic PM2.5). This evaluation examines whether 

the measurements are properly represented by the model predictions, but it does not 

necessarily ensure that the model is getting “the right answer for the right reason”; and 

• Diagnostic Evaluation: Tests the ability of the model to predict visibility and extinction, 

PM chemical composition including PM precursors (e.g., SO2, NOX, and NH3) and 

associated oxidants (e.g., ozone and nitric acid); PM size distribution; temporal variation; 

spatial variation; mass fluxes; and components of light extinction (i.e., scattering and 

 

37 Version 4.51 with SOAmods enhancement. The VISTAS regional model performance evaluation focused on monitoring sites within the 

VISTAS states and VISTAS 12-km grid. 

38 During the course of the VISTAS Phase II and ASIP modeling, VISTAS updated the secondary organic aerosol (SOA) module in CMAQ to 

include important SOA processes missing in the standard CMAQ model that significantly improved the OCM performance in the summer. The 

processes missing in the current standard versions of CMAQ, which were included as part of the SOAmods enhancement, are described in 

Section 1.3.3.3.1 of Attachment C. EPA intends to address SOA issues in the fall 2008 CMAQ release, which is too late for PM2.5 SIP work. 

Thus, both VISTAS and ASIP have adopted CMAQ version 4.51 with SOAmods updates as the core model for the modeling analysis. 
87 

absorption). The diagnostic evaluation also includes the performance of diagnostic tests 

to better understand model performance and to identify potential flaws in the modeling 

system that can be corrected. 

This model performance evaluation emphasizes the operational evaluation, since this aspect is 

emphasized in EPA’s modeling guidance. The ASIP work group has also examined other 

diagnostic features dealing with the model’s ability to simulate sub-regional and monthly/diurnal 

gas phase and aerosol concentration distributions, and has performed numerous diagnostic 

sensitivity tests to investigate and improve model performance and test the model assumptions. 

8.10c. Particulate Matter and Component Species 

PM2.5 attainment is based on PM2.5 mass measurements using Federal Reference Method (FRM) 

monitoring devices, which measure the following PM2.5 components: 

• Sulfate (SO4) 

• Nitrate (NO3) 

• Ammonium (NH4) 

• Organic Carbon Matter Carbon (OCM) 

• Elemental Carbon (EC) [also called Black Carbon ] 

• Other Inorganic PM2.5 (also referred to as soil, crustal material, fine soil, major metal 

oxides, or other PM2.5) 

• Particle Bound Water (PBW) 

• Sea Salt (mostly sodium chloride) 

• Passive Mass (Blank Correction) 

8.10d. Ambient Air Quality Data for Model Performance Evaluation 

A ground-level model evaluation database for 2002 was compiled by the modeling team using 

several routine and research-grade databases. The primary monitoring networks available to 

evaluate the PM2.5 component of the CMAQ are: (a) Interagency Monitoring of Protected Visual 

Environments (IMPROVE); (b) Clean Air Status and Trends Network (CASTNET); (c) 

Southeastern Aerosol Research and Characterization (SEARCH); (d) EPA Federal Reference 

Method (FRM) PM2.5 and PM10 Mass Networks (EPA-FRM); (e) EPA Speciation Trends 

Network (STN) of PM2.5 species; and (f) National Acid Deposition Network (NADP). Table 8-2 

and Figure 8- 3 summarize the species collected and locations of the monitoring sites for the 

monitoring networks use in the ASIP model evaluation. 
88 

Table 8- 2: Available VISTAS/ASIP Region 2002 Ambient Monitoring Data 

Monitoring 

Network Chemical Species Measured 

Sampling Frequency; 

Duration 

IMPROVE Speciated PM2.5 and PM10 1 in 3 days; 24 hr 

CASTNET Speciated PM2.5, Ozone Hourly, Weekly; 1 hr, Week 

SEARCH 

24-hr PM25 (FRM Mass, OC, BC, SO4, NO3, 

NH4, Elem.); 24-hr PM coarse (SO4, NO3, NH4, 

elements); Hourly PM2.5 (Mass, SO4, NO3, NH4, 

EC, TC); and Hourly gases (O3, NO, NO2, NOy, 

HNO3, SO2, CO) Daily, Hourly; 

NADP WSO4, WNO3, WNH4 Weekly 

EPA-FRM Only total fine mass (PM2.5) 1 in 3 days; 24 hr 

EPA-STN Speciated PM2.5 Varies; Varies 

AIRS/AQS CO, NO, NO2, NOX, O3 Hourly; Hourly 

250 500 750 1000 1250 1500 1750 2000

-1500

-1250

-1000

-750

-500

-250

0

250

500

IMPROVE

CASTNet

SEARCH

STN

NADP

AQS

Figure 8- 3: IMPROVE, STN, CASTNet, NADP and SEARCH Monitoring Sites in the 

VISTAS/ASIP Region and VISTAS/ASIP 12-km grid. 
89 

8.10e. Model Performance Statistics and Goals 

To quantify model performance, several statistical measures were calculated and evaluated for 

all monitors within the ASIP region or ASIP 12-km domain, individually for each monitor and 

individually for each ASIP State. The statistical measures selected were based on the 

recommendations outlined in section 18.4 of the USEPA’s Guidance on the Use of Models and 

Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and 

Regional Haze. The ASIP model performance evaluation considered several statistical 

performance measures and displays and reviewed numerous metrics to evaluate their descriptive 

capabilities for summarizing the relevant features of the model performance evaluation. 

Although numerous model performance statistics measures are routinely used, ASIP has found 

that the fractional bias and fractional gross error provide the best descriptive power over a wide 

range of concentrations. The fractional bias and error are expressed as a percentage and are 

normalized by the average of the predicted and observed values. Consequently, they are 

bounded statistics, with the fractional bias bounded by -200% to +200% and the fraction error 

bounded by 0 to 200%. Table 8- 3 summarizes the formulas for the fractional bias and error 

statistics, and the ASIP model performance goals and criteria are given in Table 8- 4. 

Table 8- 3: Fractional Bias and Fractional Error Model Performance Metrics 

Statistical Measure Shorthand 

Notation 

Mathematical Expression Notes 

Mean Fractional Gross Error 

(Fractional Error) 

MFE 

∑= +

− N

i i i

i i

P O

P O

N 1

2 Reported as % 

Mean Fractionalized Bias 

 (Fractional Bias) 

MFB 

∑= ⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

+

− N

i i i

i i

P O

P O

N 1

2 Reported as % 

Table 8- 4: ASIP Model Performance Goals and Criteria for PM2.5 Components 

Fractional Bias Fractional Error Comment 

<±15% <35% Goal for PM model performance based on ozone model 

performance, considered excellent performance 

<±30% <50% Goal for PM model performance, considered good performance 

<±60% <75% Criteria for PM model performance, considered average 

performance. Exceeding this level of performance indicates 

fundamental concerns with the modeling system and triggers 

diagnostic evaluation. 

8.10f. Regional Model Performance Evaluation 

Table 8- 5 summarizes the monthly CMAQ concentration fractional bias and error across the 

ASIP 12-km grid region for the IMPROVE, STN, CASTNet, SEARCH Daily and SEARCH 

Hourly monitoring networks for sulfate, nitrate, organic carbon, other PM2.5/soil, and total PM2.5. 
90 

Table 8- 5: Regional Model Performance Evaluation Summary of Results 

Component Model Performance Results Sulfate (SO4) Underprediction bias is clearly evident across most of the year and monitoring networks with the lowest SO4 bias occurring in Oct

severe (almost always within ±20% and always within ±25%), and almost always achieves the PM model performance goals for fractional bias and 50% for fractional error), except for the comparison with the SEARCH Hourly network (exhibits a positiv

months). SO4 monthly fractional error values are usually under 40% and, with one exception, always under 50%. The exception is comp

network (error values ranging from 50% to 70%). SEARCH hourly SO4 measurements are made with research grade monitor

subject to greater uncertainties than the other monitoring networks. Summer SO4 underprediction bias is due in part to overstate

MM5 simulations. This is somewhat confirmed by the SO4 wet deposition model performance evaluation that exhibits near ze

precipitation is dominated by synoptic weather events) but has a positive overprediction bias during the summer (when convective 

Nitrate (NO3) Monthly fractional bias time series plot for NO3 clearly shows a seasonal dependence of this performance measure. Summer unde

100% to -150%). Winter bias values are generally within ±50%. Fractional error values also exhibit a seasonal dependence. Er

and is 160% error with a bell-like distribution in the summer. Large summer underprediction bias occurs when NO3 concent

μg/m3). When the average observed NO3 concentration exceeds 1 μg/m3, the model mostly achieves the model performance goa

model performance criteria for bias. The model performance goal and criteria are achieved less often for NO3 fractional error

across the CASTNet and usually achieved across the IMPROVE monitoring networks. 

Organic Carbon Mass (OCM) Fairly good performance across the IMPROVE monitors, with bias usually within ±15% and errors between 40% and 50%

underprediction bias of -35% to -60% at urban STN sites. Underprediction bias at the STN sites may be due to multiple factors, suor over-dilution of urban OCM emissions by the model through the coarse 12-km grid. Underprediction of urban OCM is a comm

may point to uncertainties in the OCM and SOA precursor emission inventories. 

OCM performance was a concern in the preliminary CMAQ evaluations using early VISTAS Phase I and II databases, 

underprediction bias and the importance of OCM to the visibility extinction and PM budgets. VISTAS conducted a focused summer OCM underprediction, the identification of missing processes in the CMAQ model, and the development of the SOAmod

greatly improved the CMAQ OCM model performance. The CMAQ Version 4.51 with the SOAmods enhancements was used in t

Elemental Carbon (EC) Bias and error are lower in the first and last quarters of the year. During the summer and adjacent months EC performance across 

a large underprediction bias (-40% to -80%) that peaks in June. EC performance across the SEARCH network is somewhat simi

underprediction bias in the summer. Model performance compared to the STN network has fairly low EC fractional bias during q

larger underprediction bias during quarter 2 (-20% to -40%). The comparison to the STN network very low EC bias during manthropogenic EC emissions inventory may be adequately characterized in urban areas. 

Other PM2.5 or Soil Seasonal dependence of the Soil model performance across the IMPROVE and STN monitors is clearly evident, with a large ov

winter and near zero (IMPROVE) or much lower (SEARCH) bias in the summer. Modeled Soil values tend to be between 0 and 

values are much lower in the winter (0 to 0.5 μg/m3) and are comparable to modeled values in summer. Poorer winter Soil mo

incorrect emission temporal adjustment factors. 

Fine Particulate (PM2.5) The model generally exhibits good performance for total PM2.5 mass concentrations. During the first and last quarters of the y

PM2.5, with low fractional bias (<±20%) and error (<40%) except for the SEARCH Hourly network. Underprediction bias (-20

from April to July, due in part to the SO4 underprediction bias discussed above (SO4 is a major component of PM2.5 in the southeas
91 

8.10g. PM2.5 Attainment Test for Tennessee

CMAQ predicts the observed SO4 concentrations in Tennessee with bias and error values that 

achieve, or nearly achieve, the most stringent ozone39 performance goal (Figure 8- 4). CMAQ 

12-km results are slightly better than 36-km predictions. Unlike other States, where the largest 

underprediction bias was observed in July, Tennessee’s SO4 performance in July is quite good, 

with 12-km results producing a 4% bias and 32% error. 

Figure 8- 4: Scatter Plots of Predicted and Observed Sulfate (SO4) Concentrations for 

January, April, July and October 2002, STN Sites in Tennessee and the CMAQ 2002 36 

and 12 km Base G2 Actual Base Case Simulation 

 

39 See Table 8- 4 for explanation. 
92 

The model exhibits less skill with nitrate predictions (Figure 8- 5) and a large underprediction 

bias40 is observed in the summer (e.g., -170% in July). The bias is lower in January and October 

(<±10%), but the error is large (60% to 80%). Ammonia performance (Figure 8- 6) is generally 

good, with low bias and error in January and April, but an underprediction bias in July (-20% to -

30%) and an overprediction bias in October (33% to 36%). As observed in other States, OCM 

exhibits a large underprediction bias that ranges from -40% in the fall, winter, and spring to -

60% in summer (Figure 8- 7). EC performance is good in January and October, but tends to 

under-predict in April and July (Figure 8- 8). 

Figure 8- 5: Scatter Plots of Predicted and Observed Nitrate (NO3) Concentrations for 

January, April, July and October 2002, STN Sites in Tennessee and the CMAQ 2002 36 

and 12 km Base G2 Actual Base Case Simulation 

 

40 This underprediction bias is typical for nitrate, as indicated in Table 8- 5. 
93 

Figure 8- 6: Scatter Plots of Predicted and Observed Ammonium (NH4) Concentrations 

for January, April, July and October 2002, STN Sites in Tennessee and the CMAQ 2002 36 

and 12 km Base G2 Actual Base Case Simulation. 
94 

Figure 8- 7: Scatter Plots of Predicted and Observed Organic Matter Carbon (OCM) 

Concentrations for January, April, July and October 2002, STN Sites in Tennessee and the 

CMAQ 2002 36 and 12 km Base G2 Actual Base Case Simulation 
95 

Figure 8- 8: Scatter plots of Predicted and Observed Elemental Carbon (EC) 

Concentrations for January, April, July and October 2002, STN Sites in Tennessee and the 

CMAQ 2002 36 and 12 km Base G2 Actual Base Case Simulation 

Tennessee’s PM2.5 mass performance across the STN and FRM networks is illustrated in Figure 

8- 9 and Figure 8- 10. Across the STN networks, performance for PM2.5 achieves the ozone goal 

in January and October, but the model exhibits an underprediction bias in April and July, and the 

model exceeds the performance goal. The model performs better across the FRM network for 

PM2.5 achieving or nearly achieving the ozone performance goal in January, April and October, 

but with an underprediction bias in July (-26% to -35%) that meets PM performance goal. 
96 

Figure 8- 9: Scatter Plots of Predicted and Observed Fine Particulate Mass (PM2.5) 

Concentrations for January, April, July and October 2002, STN Sites in Tennessee and the 

CMAQ 2002 36 and 12 km Base G2 Actual Base Case Simulation 
97 

S f f( ) Figure 8- 10: Scatter Plots of Predicted and Observed Fine Particulate Mass (PM2.5) 

Concentrations for January, April, July and October 2002, FRM Sites in Tennessee and the 

CMAQ 2002 36 and 12 km Base G2 Actual Base Case Simulation 

The monthly fractional bias and error Soccer Plot for FRM PM2.5 performance in Tennessee 

(Figure 8- 11) indicates that all months of the year achieve the PM model performance goal, and 

that five months achieve (or nearly achieve) the ozone model performance goal. The ozone 

performance goal was not met for some months because of a summer underprediction bias for 

May-July; a fall/winter overprediction bias for October and November; and excessive error in 

December. 
98 

Figure 8- 11: Soccer Plot of Monthly Fractional Bias versus Fractional Gross Error for 

PM2.5 Mass at FRM Monitors in Tennessee for the CMAQ 12-km 2002 Base G2 Actual 

Base Case Simulation 

8.11. PM2.5 Projections for 200941

Attainment for the Knoxville area was demonstrated using EPA’s Speciated Modeled Attainment 

Test (SMAT), following the requirements of EPA’s April 2007 guidance. In order to perform 

the recommended modeled attainment test, observed mass concentrations of PM2.5 were divided 

into seven components, plus passively collected mass: 

 Sulfate (SO4); 

 Nitrates (NO3); 

 Ammonium (NH4); 

 Organic carbon (OC); 

 Elemental carbon (EC); 

 Particle bound water (PBW); 

 “Other” primary inorganic particulate matter (OPP); and 

 Passively collected mass 

 

41 A full description of the modeled attainment test may be found in Attachment G. 
99 

EPA has published final modeling guidance42 that includes recommendations on the use of 

modeling results to project future-year PM2.5 levels. EPA recommends use of the modeling 

results in a relative fashion to scale the observed current-year PM2.5 Design Value (DVC) to 

project a future-year PM2.5 Design Value (DVF). The model-derived scaling factors are called 

Relative Response Factors (RRFs) and are defined as the ratio of the future-year to current-year 

modeling results. The future-year PM2.5 Design Values (DVF) are obtained from the currentyear PM2.5 Design Values (DVC) by applying the RRF: 

DVF = DVC x RRF 

RRFs are site-specific and are derived from modeling results “near” each monitor. Separate 

RRFs are applied to five components of the PM2.5 DVC to obtain future-year PM2.5 estimates 

from which the DVF is derived that is compared with the PM2.5 NAAQS. 

PM2.5 attainment is based on PM2.5 mass measurements collected at FRM monitoring sites. In 

order to apply the species-specific RRFs, PM2.5 mass measurements must be speciated into 

individual components. Two speciation networks are operated in the U.S.: (1) the Speciated 

Trends Network (STN); and (2) the Interagency Monitoring of Protected Visual Environments 

(IMPROVE) networks. PM2.5 speciation data from these networks must be mapped to the FRM 

measurements in order to project future-year PM2.5 Design Values with RRFs. Two major 

components are required to project future-year design values from modeling results: 

SANDWICH Method: Both the FRM PM2.5 mass and STN/IMPROVE PM2.5 speciation 

measurements have positive and negative artifacts that must be accounted for when 

mapping observed speciation data to the FRM mass measurements. PM2.5 attainment is 

based solely on the FRM PM2.5 mass measurements, and the STN/IMPROVE PM2.5

speciation measurements must be adjusted to mimic the FRM measurements. EPA has 

developed the Sulfate Adjusted Nitrate, Derived Water Inferred Carbon Hybrid material 

balance approach (SANDWICH) to estimate the PM2.5 composition of the FRM mass 

measurements and to account for measurement artifacts. 

Speciated Modeled Attainment Test (SMAT): The SMAT test is the group of 

procedures used to project observed PM2.5 design values to a future year, using the 

relative changes in modeled concentrations. 

 

8.11a. SANDWICH Speciation of STN PM2.5 Components 

The SANDWICH procedure is designed to map STN/IMPROVE PM2.5 speciation measurements 

to FRM mass measurements and to account for the artifacts and sampling protocol variations of 

both sampling networks. The SANDWICH procedure assumes that the FRM PM2.5 mass 

consists of the following components: 

 

42 Guidance on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5 and Regional 

Haze, EPA, 2007. 
100 

FRM PM2.5 Mass = [SO4] + [EC] + [NO3FRM] + [NH4FRM] + [OCMmb] + [water] + 

[crustal] + [blank correction] 

Where: 

[SO4] = measured sulfate ion, SO4 fraction of the STN PM2.5 from the STN site 

associated with the FRM monitor; 

[EC] = measured elemental carbon from the associated STN monitor; 

[NO3FRM] = nitrate retained on the FRM filter after a portion has been volatilized in the 

FRM measurement process; 

[NH4FRM] = NH4 retained on the FRM filter after partial volatilization; 

[OCMmb] = organic carbon material, obtained as the difference between the FRM 

PM2.5 mass measurements and the remainder of the PM2.5 components; 

[water] = particle bound water; 

[crustal] = soil and other inorganic fine particulate matter; and 

[blank correction] = passively collected PM material in the STN measurement process, 

assumed to be 0.5 μg/m3. 

8.11a(i). Retained Particulate Nitrate [NO3FRM] 

The first step in the SANDWICH procedure was to estimate the retained nitrate mass on the 

FRM filters. The FRM does not capture all of the semivolatile components of the ambient air, 

such as ammonium nitrate. The retained amount of nitrate, however, can be estimated by a 

simple thermodynamic model that uses 24-hour ambient nitrate speciation concentrations, 

combined with hourly ambient temperature and humidity measurements. Nitrate is typically 

retained at low temperatures and high humidity, which varies by sampling location and time of 

year. Because nitrate retention varies by site and season, the Aerosol Inorganic Model (AIM) 

ammonium nitrate equilibrium model was used to predict the amount of nitrates retained on the 

FRM Teflon filter under the FRM sampling conditions (35% relative humidity and 21° C). 

8.11a(ii). Estimated Ammonium Associated with Sulfate and Retained Nitrates and 

Sulfates 

To determine the mass associated with nitrates, the SANDWICH approach assumed that all 

retained nitrate was ammonium nitrate, as is likely over most of the ASIP region. Assuming that 

all particulate nitrate is in the form of ammonium nitrate, the ammonium associated with nitrates 

was derived from the FRM retained NO3FRM as: 

 NH4NO3 = 0.29 * NO3FRM 
101 

Similarly, the dry PM2.5 mass associated with ammonium nitrate was calculated as: 

 [Retained dry FRM Ammonium Nitrates] = 1.29 * NO3FRM 

8.11a(iii). Ammoniated Sulfate Mass 

Sulfates may not be fully neutralized throughout the year. In winter, when nitrates are prevalent 

in the ambient aerosol, sulfates tend to be fully neutralized and exist as ammonium sulfate 

[(NH4)2SO4]. Less ammonia is available for reaction during the summer, when sulfates are 

higher. The resulting aerosol can be acidic and the form of sulfates can include ammonium 

bisulfate [NH4SO4] or even H2SO4. The amount of ammonium associated with the sulfate ion 

was estimated as: 

 NH4(SO4) = NH4adj - 0.29 * NO3FRM, 

 Where: 

 0.29 = molar ratio of NH4 to NO3 and NH4FRM and NO3FRM reflect 

the amounts retained on the FRM filter. 

The amount of NH4(SO4) may not exceed the fully neutralized amount of 0.375 multiplied by the 

estimated sulfate ion concentration. Because of uncertainties in NH4 speciation measurements, 

and because the IMPROVE monitoring network does not measure NH4, NH4 was calculated by 

deriving the degree of sulfate neutralization (DON) from the estimated NH4(SO4) as: 

 DON = NH4(SO4) / SO4 

The DON was assumed to remain constant from the current-year to future-year. Values of DON, 

sulfate and estimated FRM nitrate (adjusted nitrate) were used to estimate the adjusted 

ammonium at each FRM site as follows: 

 NH4FRM = DON * SO4 + 0.29*NO3FRM

where, DON, SO4 and NO3FRM were the quarterly average values at each FRM site. 

In the default EPA PM2.5 Design Value projection approach, interpolated DON values were used 

to estimate ammonium, due to uncertainties in the ammonium measurements and the lack of NH4

measurements at IMPROVE sites. However, for the ASIP SANDWICH/SMAT application, the 

DON, SO4 and NO3adj data from a specific STN monitoring site were assigned to FRM monitors 

and spatial interpolation was not used. 
102 

8.11a(iv). Particle Bound Water 

Because ammoniated sulfate and ammonium nitrate are hygroscopic, the retained sulfate and 

nitrate mass will include water43. Particle bound water (PBW) was estimated using the Aerosol 

Inorganic Model (AIM), using the quarterly average FRM concentrations of sulfate, ammonium, 

and nitrate and typical filter equilibration conditions of 35% RH and 22° C. Application of AIM 

at the specified FRM filter equilibration conditions indicated that PBW was more dependent on 

sulfate concentrations (compared to nitrate) and that the relationship varied somewhat by season. 

There was proportionally less estimated PBW water for winter aerosol, which has higher NH4

and NO3 and lower SO4. 

8.11a(v). Passively Collected PM2.5 Components (Blank Correction) 

Passively collected mass was represented by the typical field blank concentration of 0.3-0.5 

μg/m3. This value was assumed to remain constant from the current year to the future year. 

8.11a(vi). Calculation of Carbonaceous Mass 

The SANDWICH/SMAT approach estimated carbon by mass balance (OCMmb), comparing 

precisely measured FRM PM2.5 mass with the sum of its non-carbon components (sulfates, 

ammonium, nitrates, particle bound water, crustal material plus 0.5 μg/m3

 passively collected 

mass). Because of uncertainties in speciation measurements, a lower limit (floor) for OCMmb

was set so that OCMmb could not be more than 30% lower than measured OCM. The STNmeasured OCM was used to calculate the floor, assuming a 1.4 ratio of OCM/OC. The lower 

limit was defined as STN-measured OC * 1.4 * 0.7. If the OCMmb concentration was less than 

the lower limit, it was set equal to the lower limit. 

8.11b. Summary of PM2.5 Composition Calculations 

In summary, the SANDWICH species data was generated in the following order: 

1. Adjusted nitrate was calculated using hourly meteorology and 24-hour average nitrate 

measurements. 

 

2. Quarterly averages were calculated for adjusted nitrate, sulfate, elemental carbon, degree 

of sulfate neutralization (DON), crustal mass , and measured OCM. 

3. Quarterly average ammonium was calculated from the adjusted nitrate, sulfate, and DON 

values (or in the case of ASIP the NH4adj is used directly). 

4. Calculated ammonium, sulfate, and nitrate values were input into the water equation to 

derive particle bound water concentrations. 

 

43 Note that some organic carbon (OC) species are also likely hygroscopic but, due to various uncertainties, the PBW associated with 

hygroscopic OC species is not accounted for. 
103 

5. Carbon mass by difference (OMCmb) was calculated from the PM2.5 mass, adjusted 

nitrate, ammonium, sulfate, water, elemental carbon, crustal, and blank mass values. 

6. The sum of these species plus blank mass was equal to the FRM mass. 

8.11c. Defining Current-Year PM2.5 Design Values (DVC) 

The PM2.5 component species fractions are applied to current-year PM2.5 Design Values (DVC), 

which are projected to the future using model-derived RRFs. EPA’s PM2.5 modeling guidance 

recommends using the average of the three years of PM2.5 design value periods that straddle the 

emissions year. 

Quarterly average values are needed for each FRM site to derive the average PM2.5 design values 

for future projections. Quarterly average FRM values were derived as follows. 

1. The analysis began with quarterly average FRM data for all quarters from 2000-2004. 

2. A quarterly average three-year design value was calculated for each design value period 

in which a site had 12 quarters of complete data (2000-2002, 2001-2003, and 2002-2004). 

This resulted in four quarterly averages for up to three design value periods for each 

FRM site. 

3. Up to three quarterly design value periods were averaged to produce a single quarterly 

average design value for each site. 

8.12. Modeled Attainment Test 

The modeled attainment test consisted of the following steps: 

8.12a. Step #1: Determine Baseline Design Values 

The first step of the attainment test process is to determine the baseline design value (DVB). In 

the Attainment Guidance, EPA recommends using a DVB that is the average of the three design 

value periods that straddle the baseline inventory year (e.g., the average of the 2000-2002, 2001-

2003, and 2002-2004 design value periods for a 2002 baseline inventory year). This works out 

to a 5-year weighted average, with the baseline year having the heaviest weight (e.g. {[2000] + 

2*[2001] + 3*[2002] + 2*[2003] + [2004]}/9). For the SMAT process, a mean PM2.5 DVB is 

determined, as well as component-specific DVB for each quarter. 

8.12a(i). Mean PM2.5 Baseline Design Values 

To begin the SMAT process, a mean PM2.5 DVB is calculated on a quarterly basis for each 

Federal Reference Method (FRM) monitor in the PM2.5 nonattainment area. Concentrations are 

calculated based on calendar quarters (e. g., Q1: January - March; Q2: April - June; etc.) to 

facilitate comparison with the annual NAAQS and to allow States to examine the differences in 

PM2.5 composition during individual seasons. 
104 

Table 8- 6 contains the quarterly average PM2.5 concentration for the FRM monitors in the 

nonattainment areas. This quarterly data was averaged, using the weighted scheme suggested by 

EPA, to produce a 5-year weighted DVB. The Loudon County FRM site (47-105-0108) was not 

operational for most of the baseline period, and the attainment test was not performed for this 

monitor (see Section 9.0 for a discussion of this monitor). Only two years of data were available 

for FRM monitor 47-093-1013 (1403 Davanna Street). Per the Attainment Guidance, if a site has 

less than three years of data, then the site should not ordinarily be used in the attainment test. 

Table 8- 7 presents the final quarterly mean PM2.5 DVBs for the nonattainment areas. 

Table 8- 6: Knoxville-Area Quarterly Average PM2.5 Mass for FRM Monitors 

AIRS ID County Site Name Year Q1 Q2 Q3 Q4 

47-009-0011 Blount 

2007 Sequoyah 

Ave. 

2000 18.96 17.21 18.58 

2001 15.35 14.87 18.45 11.01 

2002 11.53 15.17 19.21 11.79 

2003 11.69 14.39 18.85 10.63 

2004 10.33 14.09 17.43 12.15 

47-093-0028 Knox 

1000 Francis 

Road 

2000 16.55 17.93 18.33 19.82 

2001 13.92 16.55 20.47 11.90 

2002 13.40 15.51 19.35 13.42 

2003 12.96 15.26 18.31 10.88 

2004 10.98 14.68 17.41 12.42 

47-093-1017 Knox 

1613 Vermont 

Avenue 

2000 18.65 19.88 20.72 20.41 

2001 15.00 17.72 21.53 15.57 

2002 13.89 16.26 21.53 13.82 

2003 12.81 14.81 21.46 12.98 

2004 13.40 14.92 18.36 13.69 

47-093-1020 Knox 

4625 Mildred 

Drive 

2000 15.39 18.32 19.09 19.55 

2001 15.30 18.53 20.53 13.52 

2002 13.24 16.04 21.27 13.84 

2003 12.01 13.36 19.83 11.96 

2004 12.49 14.64 19.48 13.05 

47-105-0108 Loudon 130 Webb Drive 

2000 N/A N/A N/A N/A 

2001 N/A N/A N/A N/A 

2002 N/A N/A N/A N/A 

2003 N/A N/A N/A N/A 

2004 11.29 15.96 19.27 12.17 

47-145-0004 Roane 

1002 North 

Roane Street 

2000 14.55 15.88 16.91 20.33 

2001 12.38 16.36 20.76 11.40 

2002 11.74 14.37 17.79 10.60 

2003 10.90 12.17 19.19 10.97 

2004 9.97 15.30 18.05 12.84 
105 

Table 8- 7: Observed Quarterly Mean PM2.5 DVB for Monitors in the Knoxville, Tennessee 

Nonattainment Area 

AIRS ID County Site Name 

2000-2004 Averages 

Q1 Q2 Q3 Q4 

47-009-0011 Blount 2007 Sequoyah Ave. 11.99 14.73 18.04 11.65 

47-093-0028 Knox 1000 Francis Road 13.00 15.36 18.54 12.62 

47-093-1017 Knox 1613 Vermont Avenue 13.87 16.02 20.57 14.24 

47-093-1020 Knox 4625 Mildred Drive 13.08 15.60 19.84 13.40 

47-105-0108 Loudon 130 Webb Drive 10.79 15.46 18.77 11.67 

47-145-0004 Roane 1002 North Roane Street 11.31 14.09 18.19 11.69 

8.12a(ii). Speciated Baseline Conditions 

The monitored attainment test for PM2.5 utilizes total PM2.5 and individual PM2.5 component 

species. Because a separate RRF is calculated for each PM2.5 species, States must divide 

observed PM2.5 mass concentrations into seven components, plus passive mass: 

1. Mass associated with sulfates (SO4); 

2. Mass associated with nitrates (NO3); 

3. Mass associated with ammonium (NH4); 

4. Mass associated with organic carbon (OC); 

5. Mass associated with elemental carbon (EC); 

6. Mass associated with particle bound water (PBW); 

7. Mass associated with “other” primary inorganic particulate matter (Crustal); and 

8. Passively collected mass (mass of the blank filter: 0.5 μg/m3

) 

The second part of the process is to speciate the quarterly mean PM2.5 DVBs into individual 

components to calculate the quarterly mean concentrations of these components at the FRM 

sites. This need to speciate the FRM data presents two issues: 

8.12a. FRM measurements and speciated PM2.5 measurements do not always measure 

the same mass; and 

 

8.12b. Not all FRM monitoring sites have co-located STN speciation monitors. 

The following sections will explain how these issues were overcome to produce the speciated 

values needed for this attainment demonstration. 

8.12a(iii). SANDWICH Speciation Method 

As the Attainment Guidance notes, recent data analyses have noted that the FRM monitors do 

not measure the same components and do not retain all of the PM2.5 that is measured by routine 

speciation samplers. Therefore, the FRM monitors cannot be directly compared to speciation 

measurements from the Speciation Trends Network (STN)44. This results in concentrations (and 

 

44 By design, the FRM mass measurement does not retain all ammonium nitrate and other semivolatile materials (negative sampling artifacts) 
106 

percent contributions to PM2.5 mass), which may be different than the ambient levels of some 

PM2.5 chemical constituents. 

To resolve the differences between FRM and STN total mass, EPA recommends the “sulfate, 

adjusted nitrate, derived water, inferred carbonaceous material balance approach” or 

SANDWICH approach. This approach adjusts nitrate mass to account for volatilization, based 

on hourly meteorology parameters. Subsequently, quarterly average nitrate, sulfate, elemental 

carbon, and crustal mass, and the Degree of Neutralization (DON) of sulfates can be calculated. 

Quarterly average NH4 can be calculated from the adjusted nitrate mass, sulfate mass, and sulfate 

DON. The mass of particle bound water can be calculated from DON, sulfate, nitrate, and 

ammonium values. Finally, organic carbon may be calculated as the difference between the 

PM2.5 mass measured at the FRM monitor and the calculated component mass (i.e. OC from 

mass balance ([OCMmb]) = PM2.5FRM - {[EC] + [SO4] + [NO3] + [NH4] + [water] + [crustal 

material] + [passive mass]}). 

8.12a(iv). Speciated Profiles 

While the SANDWICH method reconciles the differences between FRM and STN, not all FRM 

monitoring sites have co-located STN monitors to provide speciated data. EPA’s Attainment 

Guidance suggests four measures that can be taken to resolve the lack of speciated data: 

8.12a. Use of concurrent data from a nearby speciated monitor 

8.12b. Use of representative data (from a different time period) 

8.12c. Use of interpolation techniques to create a spatial field using ambient speciation 

data 

8.12d. Use of interpolation techniques to create spatial fields, and gridded modeling 

outputs to adjust the species concentrations 

Of the four methodologies, EPA recommends the use of spatial interpolation techniques to 

estimate species concentrations at FRM sites that do not have speciation data (items 3 and 4 

above). EPA is developing a software tool called “Modeled Attainment Test Software” (MATS) 

that will perform the spatial analysis, but the PM2.5 portion of the MATS tool has not been 

released at this time. As an alternative to MATS, the ASIP work group used the speciated 

profiles from the Clean Air Interstate Rule (CAIR) SMAT tool45. 

The CAIR SMAT tool uses data from both the Interagency Monitoring of Protected Visual 

Environments (IMPROVE) and EPA’s Speciation Network (ESPN) to derive mean 

concentrations for six PM2.5 components. Quarterly average concentrations between January 

2002 to December 2002 were retained for sites that had at least 11 monitored values per quarter 

for each of the major PM2.5 species. Major species for ESPN include EC, OC, NH4, SO4, NO3, 

and crustal material (which includes the five trace elements aluminum, calcium, iron, silicon, and 

titanium). The major species for IMPROVE are the same except for NH4, which is not routinely 

measured in the IMPROVE protocol. 

 and includes particle bound water associated with sulfates, nitrates and other hygroscopic species (positive sampling artifacts). 

45 A report on the CAIR SMAT procedure is included in Attachment M. 
107 

The quarterly averaged species concentrations at the IMPROVE and ESPN monitors were used 

to interpolate concentrations at the PM2.5 FRM monitoring sites using a technique called Voronoi 

Neighbor Averaging (VNA). 

As a result of the CAIR SMAT process, quarterly species fractions were generated for the FRM 

sites, which are presented in Table 8- 8 below. These fractions were applied to observed 

quarterly mean PM2.5 values to determine quarterly component-specific concentrations (Table 8- 

9) shows the quarterly DVBs for crustal, EC, OC, SO4, NO3, NH4 and PBW, assuming a constant 

passive mass of 0.5 μg/m3

. 

Table 8- 8: Quarterly Species Fractions from the CAIR SMAT Tool 

AIRS 

ID County Site Name Qtr. blank DON 

Frac. 

Crustal 

Frac. 

EC 

Frac. 

OC 

Frac. 

SO4

Frac. 

NO3

Frac. 

NH4

Frac. 

H2O 

47-009-

0011 Blount 

2007 

Sequoyah 

Ave. 

1 0.5 0.2894 0.0199 0.0399 0.5813 0.2175 0.0136 0.0669 0.0609 

2 0.5 0.2910 0.0450 0.0300 0.4203 0.3198 0.0007 0.0933 0.0909 

3 0.5 0.2732 0.0385 0.0230 0.3132 0.4099 0.0005 0.1121 0.1027 

4 0.5 0.2738 0.0266 0.0443 0.4778 0.2773 0.0204 0.0818 0.0718 

47-093-

0028 Knox 

1000 

Francis 

Road 

1 0.5 0.2894 0.0171 0.0341 0.6418 0.1861 0.0116 0.0572 0.0521 

2 0.5 0.2910 0.0440 0.0293 0.4337 0.3125 0.0007 0.0911 0.0888 

3 0.5 0.2732 0.0382 0.0228 0.3185 0.4068 0.0005 0.1113 0.1019 

4 0.5 0.2738 0.0232 0.0387 0.5439 0.2422 0.0178 0.0715 0.0627 

47-093-

1017 Knox 

1613 

Vermont 

Avenue 

1 0.5 0.2894 0.0164 0.0328 0.6551 0.1792 0.0112 0.0551 0.0501 

2 0.5 0.2910 0.0419 0.0279 0.4605 0.2976 0.0006 0.0868 0.0846 

3 0.5 0.2732 0.0342 0.0205 0.3889 0.3648 0.0005 0.0998 0.0914 

4 0.5 0.2738 0.0225 0.0375 0.5575 0.2350 0.0173 0.0693 0.0609 

47-093-

1020 Knox 

4625 

Mildred 

Drive 

1 0.5 0.2878 0.0204 0.0463 0.5916 0.2041 0.0173 0.0637 0.0566 

2 0.5 0.2948 0.0405 0.0328 0.4455 0.3031 0.0006 0.0895 0.0879 

3 0.5 0.2735 0.0294 0.0231 0.3999 0.3587 0.0005 0.0982 0.0902 

4 0.5 0.2726 0.0217 0.0532 0.4866 0.2602 0.0315 0.0801 0.0666 

47-105-

0108 Loudon 

130 Webb 

Drive 

1 N/A 

2 N/A 

3 N/A 

4 N/A 

47-145-

0004 Roane 

1002 North 

Roane 

Street 

1 0.5 0.2885 0.0240 0.0480 0.4966 0.2499 0.0311 0.0811 0.0692 

2 0.5 0.2983 0.0555 0.0339 0.3834 0.3302 0.0007 0.0987 0.0975 

3 0.5 0.2815 0.0520 0.0278 0.2560 0.4285 0.0006 0.1208 0.1143 

4 0.5 0.2841 0.0327 0.0525 0.3732 0.3179 0.0366 0.1009 0.0861 
108 

Table 8- 9: Quarterly and Annual Average Component-Specific Concentrations for the 

FRM Monitors in the Knoxville, TN PM2.5 Nonattainment Area 

AIRS ID County Quarter

FRM 

Mass

Blank 

Mass

Blank

Corrected 

Mass Crustal EC OC SO4 NO3 NH4 PBW

NO3 + 

NH4 + 

PBW

1 12.99 0.50 12.49 0.24 0.48 6.97 2.61 0.16 0.80 0.73 0.26

2 15.73 0.50 15.23 0.66 0.44 6.19 4.71 0.01 1.37 1.34 0.02

3 19.04 0.50 18.54 0.69 0.41 5.65 7.40 0.01 2.02 1.85 0.01

4 12.65 0.50 12.15 0.31 0.52 5.57 3.23 0.24 0.95 0.84 0.37

Ann 14.61 0.50 14.11 0.48 0.46 6.10 4.49 0.11 1.29 1.19 0.16

1 14.00 0.50 13.50 0.22 0.44 8.34 2.42 0.15 0.74 0.68 0.24

2 16.36 0.50 15.86 0.68 0.45 6.66 4.80 0.01 1.40 1.36 0.02

3 19.54 0.50 19.04 0.71 0.42 5.91 7.54 0.01 2.06 1.89 0.01

4 13.62 0.50 13.12 0.29 0.49 6.86 3.06 0.22 0.90 0.79 0.35

Ann 15.35 0.50 14.85 0.47 0.45 6.94 4.45 0.10 1.28 1.18 0.15

1 14.87 0.50 14.37 0.23 0.46 9.09 2.49 0.16 0.76 0.70 0.25

2 17.02 0.50 16.52 0.67 0.45 7.37 4.77 0.01 1.39 1.35 0.02

3 21.57 0.50 21.07 0.70 0.42 8.00 7.50 0.01 2.05 1.88 0.01

4 15.14 0.50 14.74 0.32 0.53 7.94 3.35 0.25 0.99 0.87 0.38

Ann 16.67 0.50 16.17 0.48 0.46 8.10 4.53 0.11 1.30 1.20 0.16

1 14.08 0.50 13.58 0.27 0.61 7.74 2.67 0.23 0.83 0.74 0.36

2 16.60 0.50 16.10 0.63 0.51 6.95 4.73 0.01 1.40 1.37 0.02

3 20.84 0.50 20.34 0.58 0.46 7.94 7.12 0.01 1.95 1.79 0.01

4 14.40 0.50 13.90 0.29 0.71 6.52 3.49 0.42 1.07 0.89 0.66

Ann 15.98 0.50 15.48 0.44 0.57 7.29 4.50 0.17 1.31 1.20 0.26

1 12.31 0.50 11.81 0.27 0.54 5.62 2.83 0.35 0.92 0.78 0.56

2 15.09 0.50 14.59 0.78 0.48 5.40 4.65 0.01 1.39 1.37 0.02

3 19.19 0.50 18.69 0.95 0.50 4.66 7.80 0.01 2.20 2.08 0.02

4 12.69 0.50 12.19 0.38 0.61 4.36 3.72 0.43 1.18 1.01 0.68

Ann 14.32 0.50 13.82 0.60 0.53 5.01 4.75 0.20 1.42 1.31 0.32

47-093-1017 Knox

47-093-1020 Knox

47-093-0028 Knox

47-009-0011 Blount

47-145-0004 Roane

8.12b. Step #2: Relative Response Factor Calculation 

The next step in the SMAT process is to use base year and future year modeling results to 

estimate a relative response factor (RRF) for each component of PM2.5 for each quarter. Simply 

put, the RRF is the quarterly average future year concentration near a monitor divided by the 

quarterly average base year concentration near the same monitor, or: 

Quarterly Mean Modeled Base Year Concentration "Near" Monitor "X"

Quarterly Mean Modeled Future Year Concentration "Near" Monitor "X" RRF =

Instead of focusing on the individual cell containing the monitor, an array of cells that are “near” 

a monitor are considered in the attainment test. By sampling an array of cells from the modeling, 

the attainment test allows for variations in the model performance, as the peak concentrations 

may not occur in the grid cell that contains the monitor, but rather nearby the monitor. Table 8- 

10 provides EPA's recommendations for defining “nearby” cells for grid systems having cells of 

various sizes. Since the modeling for the attainment demonstration was performed at a 12-km 

grid resolution, a 3x3 grid array was used. 
109 

Table 8- 10: EPA’s Recommendation for Defining “Near” Cells 

Size of Cell 

(km) 

Size of the Array of 

“Nearby” Cells 

<5 7 x 7 

>5-8 5 x 5 

>8-15 3 x 3 

>15 1 x 1 

For the PM2.5 SMAT, quarterly RRFs are calculated for each component. The concentration for 

each PM2.5 component is extracted from the base year and future year modeling output near the 

FRM monitoring sites for each day. The daily component concentrations from the 3x3 array are 

averaged to develop a mean daily component mass for each day in both the base and future 

years. These mean daily component concentrations are averaged for each quarter to develop 

base and future year quarterly mean component concentration. The future year quarterly mean 

component concentrations are then divided by their respective base year quarterly mean 

component concentrations to develop quarterly RRFs for each PM2.5 component. The quarterly 

RRFs for the FRM monitors in the Knoxville PM2.5 nonattainment area are presented in Table 8- 

11. The CAIR SMAT tool estimates the future mass of NH4 and PBW from the estimated future 

mass of SO4 and NO3, in lieu of using RRFs, per the following equations: 

NH4 = DON * SO4 + 0.29*NO3

PBW = (-0.002618) + (0.980314*NH4) + (-0.260011* NO3) + (-0.000784* SO4) + (-0.159452* 

(NH4^2)) + (-0.356957* NO3* NH4) + (0.153894* (NO3^2)) + (0.212891* SO4* NH4) + 

0.0444366* SO4* NO3) + (-0.048352* (SO4^2)) 

Table 8- 11: Quarterly Component RRFs for Monitors in the Knoxville, Tennessee 

Nonattainment Area (Base G4a) 

AIRS ID County Site Name Qtr.

RRF 

Crustal EC OC SO4 NO3

47-009-0011 Blount 2007 Sequoyah Ave. 

1 1.0135 0.8377 0.9759 0.8784 1.0202 

2 1.0155 0.8069 0.9600 0.7805 0.7672 

3 1.0235 0.8041 0.9574 0.6573 1.0666 

4 1.0312 0.7923 0.9737 0.8555 1.0003 

47-093-0028 Knox 1000 Francis Road 

1 1.0348 0.8008 0.9752 0.8782 1.0166 

2 1.0297 0.7703 0.9634 0.7770 0.7721 

3 1.0398 0.7666 0.9601 0.6571 1.0696 

4 1.0521 0.7600 0.9740 0.8574 0.9830 

47-093-1017 Knox 

1613 Vermont 

Avenue 

1 1.0200 0.8011 0.9705 0.8746 1.0125 

2 1.0160 0.7730 0.9602 0.7773 0.7652 

3 1.0271 0.7707 0.9582 0.6554 1.0594 

4 1.0384 0.7622 0.9707 0.8528 0.9872 

47-093-1020 Knox 4625 Mildred Drive 

1 1.0381 0.7750 0.9694 0.8746 1.0150 

2 1.0346 0.7443 0.9611 0.7755 0.7669 
110 

3 1.0505 0.7425 0.9579 0.6521 1.0468 

4 1.0584 0.7340 0.9707 0.8512 0.9862 

47-105-0108 Loudon 130 Webb Drive 

1 1.0663 0.8410 0.9877 0.8936 0.9974 

2 1.0720 0.7879 0.9642 0.7879 0.7259 

3 1.0781 0.7821 0.9589 0.6704 0.9086 

4 1.0798 0.7751 0.9783 0.8740 0.9483 

47-145-0004 Roane 

1002 North Roane 

Street 

1 1.0797 0.8546 0.9809 0.9035 1.0289 

2 1.0986 0.7983 0.9622 0.7944 0.8016 

3 1.1162 0.7875 0.9519 0.6750 0.8780 

4 1.1001 0.7858 0.9759 0.8774 0.9827 

8.12c. Step #3: Future Year Quarterly Concentration Calculation 

The next step in the SMAT process is to calculate future quarterly mean concentration estimates 

for each PM2.5 component. Current quarterly mean component concentrations were multiplied 

by the component-specific RRFs obtained in Step 2. The quarterly component DVFs for the 

monitors in the Knoxville PM2.5 nonattainment areas are provided in Table 8- 12. 

Table 8- 12: Future Quarterly Component Concentrations for Monitors in the Knoxville, 

Tennessee Nonattainment Area (Base G4a) 

AIRS ID County Site Name Qtr. 

DVF (Base G4a) 

Crustal EC OC SO4 NO3 NH4 PBW 

47-009-

0011 Blount 

2007 Sequoyah 

Ave. 

1 0.2424 0.4006 6.8052 2.2917 0.1663 0.7114 0.6412 

2 0.6732 0.3566 5.9440 3.6770 0.0077 1.0724 1.0444 

3 0.7106 0.3334 5.4103 4.8618 0.0103 1.3311 1.2455 

4 0.3194 0.4090 5.4208 2.7646 0.2375 0.8258 0.7185 

Avg. 0.4864 0.3749 5.8951 3.3988 0.1055 0.9852 0.9124 

47-093-

0028 Knox 

1000 Francis 

Road 

1 0.2295 0.3551 8.1346 2.1242 0.1537 0.6593 0.5947 

2 0.6956 0.3469 6.4189 3.7298 0.0079 1.0878 1.0594 

3 0.7362 0.3242 5.6694 4.9562 0.0105 1.3570 1.2687 

4 0.3082 0.3711 6.6855 2.6205 0.2208 0.7815 0.6821 

Avg. 0.4924 0.3493 6.7271 3.3577 0.0982 0.9714 0.9013 

47-093-

1017 Knox 

1613 Vermont 

Avenue 

1 0.2324 0.3651 8.8194 2.1739 0.1573 0.6747 0.6085 

2 0.6816 0.3457 7.0817 3.7054 0.0078 1.0807 1.0525 

3 0.7235 0.3242 7.6650 4.9185 0.0104 1.3466 1.2595 

4 0.3330 0.4074 7.7058 2.8539 0.2427 0.8517 0.7410 

Avg. 0.4926 0.3606 7.8180 3.4129 0.1045 0.9884 0.9154 

47-093-

1020 Knox 

4625 Mildred 

Drive 

1 0.2771 0.4695 7.5008 2.3350 0.2293 0.7384 0.6477 

2 0.6541 0.3810 6.6780 3.6654 0.0077 1.0827 1.0604 

3 0.6122 0.3405 7.6013 4.6411 0.0100 1.2723 1.1934 

4 0.3083 0.5236 6.3285 2.9673 0.4161 0.9294 0.7650 

Avg. 0.4630 0.4286 7.0272 3.4022 0.1658 1.0057 0.9166 

47-105-

0108 Loudon 

130 Webb 

Drive 

1 DVF not calculated 

2 DVF not calculated 

3 DVF not calculated 

4 DVF not calculated 

Avg. DVF not calculated 
111 

47-145-

0004 Roane 

1002 North 

Roane Street 

1 0.2933 0.4643 5.5107 2.5542 0.3623 0.8421 0.7084 

2 0.8597 0.3813 5.2000 3.6976 0.0081 1.1053 1.0882 

3 1.0568 0.3977 4.4334 5.2619 0.0092 1.4837 1.4149 

4 0.4203 0.4822 4.2575 3.2610 0.4210 1.0484 0.8821 

Avg. 0.6575 0.4314 4.8504 3.6937 0.2002 1.1198 1.0234 

8.12d. Step #4: Future Year Annual Average Estimate 

The final step in the SMAT process is to sum the quarterly mean components to get annual mean 

PM2.5 values. Table 8- 13 displays the quarterly mean PM2.5 values for the FRM sites in the 

Knoxville nonattainment area. 

Table 8- 13: Quarterly Mean PM2.5 Mass Estimates for 2009 (Base G4a) 

AIRS ID County Site Name 

DVF (Total Non-Blank Mass) 

Q1 Q2 Q3 Q4 Avg. 

47-009-0011 Blount 2007 Sequoyah Ave. 11.26 12.78 13.90 10.70 12.16 

47-093-0028 Knox 1000 Francis Road 12.25 13.35 14.32 11.67 12.90 

47-093-1017 Knox 1613 Vermont Avenue 13.03 13.96 16.25 13.14 14.09 

47-093-1020 Knox 4625 Mildred Drive 12.20 13.53 15.67 12.24 13.41 

47-105-0108 Loudon 130 Webb Drive 0.00 0.00 0.00 0.00 0.00 

47-145-0004 Roane 1002 North Roane Street 10.74 12.34 14.06 10.77 11.98 

The quarterly mean PM2.5 values were averaged to produce a future year annual average PM2.5

estimate for each FRM site in the nonattainment area (Table 8- 14). These values estimated 

annual PM2.5 values were compared to the NAAQS (15.0 μg/m3), and since predicted future 

concentrations values at each FRM site in the nonattainment area are less than 15.0 μg/m3

, the 

attainment test is passed. 

Table 8- 14: Estimated Annual Mean 2009 PM2.5 Mass Compared to the DVB 

AIRS ID County Site Name 

Modeled PM2.5 Concentrations in μg/m3

2002 Annual 

DVC

2009g4a 

Annual

Difference 

(2009g4a2002gt2a)

47-009-0011 Blount 2007 Sequoyah Ave. 14.6 12.7 -1.9 

47-093-0028 Knox 1000 Francis Road 15.4 13.4 -2.0 

47-093-1017 Knox 1613 Vermont Avenue 16.7 14.6 -2.1 

47-093-1020 Knox 4625 Mildred Drive 16.0 13.9 -2.1 

47-105-0108 Loudon 130 Webb Drive 14.7 N/A N/A 

47-145-0004 Roane 1002 North Roane Street 14.3 12.5 -1.8 

8.13. Comparison of Attainment Test Results: Base G2a vs. Base G4a 

A comparison of the 2009 Base G2a and 2009 Base G4a attainment test results is presented in 

Table 8- 15. As this table indicates, a minimal change in projected design values was observed 

between the two modeling iterations. 
112 

Table 8- 15: Comparison of ASIP Attainment Test Results 

2009 Base G2a vs. 2009 Base G4a 

AIRS ID County Site Name 

Modeled PM2.5 Concentrations in μg/m3

2009 g2a 

Annual 

2009g4a 

Annual 

Change 

(2009g2a - 

2009 g4a) 

47-009-0011 Blount 2007 Sequoyah Ave. 12.7 12.7 0.0 

47-093-0028 Knox 1000 Francis Road 13.5 13.4 0.1 

47-093-1017 Knox 1613 Vermont Avenue 14.7 14.6 0.1 

47-093-1020 Knox 4625 Mildred Drive 14 13.9 0.1 

47-145-0004 Roane 1002 North Roane Street 12.6 12.5 0.1 

8.14. Data Management 

Large data files are required for each component of the modeling process, including 

meteorological data, emissions processing, and CMAQ modeling files. Data backup and 

archiving will be performed at each of the modeling centers (ENVIRON and AG), and copies of 

critical project data will be maintained to provide redundant backup of key project data. In 

addition, each modeling center will perform backups of key project data to tape or redundant 

disk storage systems. 

The ASIP work group will archive all modeling files, MM5, SMOKE, and CMAQ on external 

drives, and an external drive containing all supporting modeling data will be sent to each ASIP 

State. These files will be made available to EPA and the public upon request. To request access 

to these files, please contact Travis Blake at (615) 532-0554. 

8.15. Weight of Evidence Requirement 

EPA guidance includes a weight of evidence zone, in which additional analysis is needed to 

support a modeled attainment demonstration. EPA recommends a weight-of-evidence analysis if 

the modeled future-year PM2.5 Design Value is between 14.5 and 15.5 μg/m3

. As indicated in 

Table 8- 14 and Table 8- 15, the projected future design value is above 14.5 μg/m3

 for one 

monitor in the Knoxville nonattainment area, and a weight of evidence analysis is required. The 

weight of evidence analysis is presented in the following section. 
113 

9.0 WEIGHT OF EVIDENCE ANALYSIS 

Section 2.3 of EPA’s Guidance on the Use of Models and Other Analyses for Demonstrating 

Attainment of Air Quality Goals For Ozone, PM2.5, and Regional Haze discusses basic 

requirements for weight of evidence analyses. This guidance states that States should review the 

results of the modeled attainment test and of several different types of air quality analyses. Each 

analysis should be weighed according to its credibility and its ability to assess the adequacy of 

the proposed attainment strategy, and the conclusions should be combined into an overall 

assessment of whether the area is likely to meet the air quality goals. For areas in which the 

predicted future design values are greater than 14.5 μg/m3

 at one or more monitoring sites, the 

guidance states that a weight of evidence demonstration should be conducted to determine 

whether the aggregate supplemental analyses support the modeled attainment test. As indicated 

in Table 8- 15, the predicted future design value at one monitor in the Knoxville nonattainment 

area is greater than 14.5 μg/m3

, and Tennessee is conducting a weight of evidence analysis in 

support of the modeled attainment test. 

EPA’s modeling guidance states that each analysis in a weight of evidence argument must be 

weighted qualitatively, depending upon: 1) the capacity of the analysis to address the adequacy 

of a control strategy; and 2) the technical credibility of the analysis. If the overall weight of 

evidence produced by the combination of the primary modeling analysis and the various 

supplemental analyses supports the attainment hypothesis, then attainment of the NAAQS is 

demonstrated with the proposed strategy. 

The end product of a weight of evidence determination is a document that describes the analyses 

performed, databases used, key assumptions and outcomes of each analysis, and why a 

State/Tribe believes that the evidence, viewed as a whole, supports a conclusion that the area will 

attain the NAAQS. The weight of evidence analysis for the Knoxville area is summarized in 

Table 9- 9, with additional supporting comments in the following paragraphs. 

9.1. Air Quality Trends 

The Knoxville nonattainment area has seen a significant downward trend in annual average 

PM2.5 concentrations since 1999, with a corresponding decrease in three-year design values (see 

Figure 2- 6). The decline in ambient PM2.5 concentrations was contemporaneous with significant 

decreases in SO2 emissions from electric utilities in Tennessee and other States (Table 5- 1 

indicates that SO2 emissions from Tennessee and surrounding States decreased by about 836,000 

tons/year between 2000 and 2006); declining SO2 emissions from the two electric utilities 

located in the nonattainment area (see Figure 5- 2); and decreasing emissions from mobile 

sources due to tighter standards and fleet turnover46. Quarterly air quality monitoring results for 

all monitors in the Knoxville nonattainment area are presented in Attachment E. 

 

46 See Sections 5.0 and 7.0 and Attachment D for further discussion of emission controls for mobile sources. 
114 

9.2. Correlation of Ambient Monitoring Data with Regional SO2 Reductions from 

Electric Utilities 

As indicated in Sections 2.0 and 5.0, regional emissions of sulfur dioxide from electric utilities 

have declined significantly between 2000 and 2006, and these changes appear to be wellcorrelated with reductions in ambient PM2.5 concentrations at the Knoxville-area monitors. 

Comparison of ambient monitoring data for the Knoxville area with utility SO2 emissions data 

from the Acid Rain Program strongly suggest a linear relationship between ambient PM2.5 levels 

and local, State, and regional SO2 emissions. These data suggest that continued SO2 reductions 

from electric utilities will result in further declines in ambient PM2.5 levels. 

9.3. Emissions Inventory: Changes in Direct PM2.5 and Precursor Emissions 

The Knoxville-area emission inventory was reviewed to determine whether the predicted 

emission reductions are: 1) significant (i. e., are the reductions a sizeable fraction of the total 

emissions inventory); and 2) likely to occur by 2009. 

Sulfur Dioxide – Point Sources: The ASIP emission inventory predicts that sulfur dioxide 

emissions in the Knoxville area will decrease by 31% between 2002 and 2009 (Table 9- 1), with 

the largest reductions resulting from the installation of wet scrubber controls at TVA’s Bull Run 

Fossil plant for CAIR compliance. Although the CAIR rule does not require emission controls at 

specific facilities, there is a high probability that these emission reductions will occur as 

predicted, since physical construction of the wet scrubber is almost complete. 

Sulfur Dioxide – Mobile Sources: Emissions from nonroad and onroad mobile sources are also 

predicted to decline. Mobile source emissions make up a smaller percentage of the total 

inventory than point source emissions, but mobile source emissions are a significant fraction of 

the total inventory in Knox County. Mobile source SO2 reductions are primarily based upon 

Federal rules restricting the sulfur content of gasoline and diesel fuel, and there is a high 

probability that these reductions will occur as predicted. 

Table 9- 1: 2009 Change in SO2 Emissions by Category 

Category 2002 SO2 Emissions, 

% of Total Inventory 

% Change in SO2

Emissions, 2002-2009 

2009 SO2 Emissions, 

% of Total Inventory 

Area 0.3% 6% 0.4% 

Nonroad 0.5% -67% 0.3% 

Onroad 0.8% -89% 0.1% 

Point (Actual Emissions Basis) 98.4% -30% 99.2% 

Total 100.0% -31% 100.0% 

Direct PM2.5 Emissions: The emission inventory predicts some growth in direct PM2.5 emissions 

between 2002 and 2009, primarily as a result of point source emissions growth. Across the entire 

nonattainment area, the increase in PM2.5 emissions is offset by declining SO2 emissions. 

However, the inventory predicts significant decreases in PM2.5 emissions from mobile sources, 

and these ground-level reductions should have a positive impact on PM2.5 concentrations within 

the city of Knoxville and in other high-traffic areas. 
115 

Table 9- 2: 2009 Change in PM2.5 Emissions by Category 

Category 2002 PM2.5 Emissions, 

% of Total Inventory 

% Change in PM2.5

Emissions, 2002-2009 

2009 PM2.5 Emissions, 

% of Total Inventory 

Area 18.5% 7% 19.6% 

Nonroad 5.0% -14% 4.3% 

Onroad 4.0% -36% 2.5% 

Point (Actual Emissions Basis) 72.5% 2% 73.6% 

Total 100% 1% 100.0% 

Other Emission Reductions: As indicated in Sections 6.0 and 10.0, Tennessee expects some 

additional reductions in point source SO2 emissions that were not included in the 2009 emission 

inventory (Table 9- 3). These reductions are expected to have a positive impact on PM2.5

attainment. 

Table 9- 3: Additional SO2 Reductions Not Included in 2009 Emission Inventory 

Facility SO2 Control Technology Projected SO2 Reduction 

(tons) 

Comments 

TVA Kingston Fossil 

Plant 

Wet scrubber to be 

installed for CAIR 

compliance. Physical 

construction of the 

scrubber is underway. 

30,224 Scrubber is currently 

scheduled to come online 

December 2009 for Units 

6-9. Most benefits will 

occur in 2010 (some 

benefits could occur in 

2009 if early startup is 

achieved). Contingency 

measure for PM2.5 SIP. 

U. S. Department of 

Energy Y-12 Plant 

Existing coal-fired boilers 

to be replaced with natural 

gas-fired units. 

2,315 Construction is projected 

for 2009. 

9.4. Air Quality Trends at Loudon County Monitor (47-105-0108) 

FRM monitor 47-105-0108 in Loudon County began collecting data in 2003 and did not collect 

sufficient data during the 2002-2004 baseline period to be included in the attainment 

demonstration. Comparison of the PM2.5 design values at this monitor with other FRM sites in 

the Knoxville area (Table 9- 4), shows that PM2.5 concentrations at the Loudon monitor from 

2003-2005 are higher than concentrations at all other Knoxville-area monitors during the threeyear period 2003-2005. During the 2004-2006 period, the design value at this monitor is 

somewhat lower than at the controlling monitor (47-093-1017) and is slightly higher than the 

three-year averages measured at the Francis Road and Mildred Drive sites in Knox County. 

The design value for the Loudon site is significantly influenced by the lack of PM2.5 data in 

2003. Historically, the highest PM2.5 concentrations for Tennessee are observed in the third 

quarter. The average actual data collected for the Loudon site in 2004 through 2006 for the first 

and second quarters, if substituted for the missing quarters in 2003, confirms that the site’s 

design value is not significantly higher than other Knox county monitors that have traditionally 
116 

experienced elevated levels of PM2.5 (Table 9- 5)47. 

Table 9- 4: Sorted PM2.5 Design Values at Knoxville-Area FRM Monitors 

AIRS ID Address County 

PM2.5 Design Value in μg/m3

2002-2004 2003-2005 2004-2006 

47-009-0011 2007 Sequoyah Avenue Blount 13.9 14.1 14.1 

47-145-0004 1002 North Roane Street Roane 13.6 14.2 14.5 

47-093-0028 1000 Francis Road Knox 14.5 14.5 15.2 

47-093-1020 4625 Mildred Drive Knox 15.1 15.1 15.2 

47-105-0108 130 Webb Drive Loudon 15.5* 15.7 15.3 

47-093-1017 1613 Vermont Avenue Knox 15.7 15.6 15.6 

* Incomplete, partial design value above the NAAQS 

Table 9- 5: Data Substitution Analysis for Loudon County Monitor 

Calculated using the missing 1st and 2nd quarters in 2003.

Year AIRS Site ID Quarter 1 Quarter 2 Quarter 3 Quarter 4

Annual 

Average 470930028 470931013 470931017 470931020

2002 471050108 15.5 2002 2004 14.5 14.9 15.7 15.1

2003 471050108 20.1 12.67037 16.39 15.7 2003 2005 14.5 13.9 15.6 15.1

2004 471050108 11.28519 15.96 19.27 12.16667 14.67 15.3 2004 2006 15.2 11.8 15.6 15.2

2005 471050108 12.26 17.80333 21.16207 13.38276 16.15

2006 471050108 11.47083 16.18462 18.54286 13.66786 14.97 Controlling monitor DV

Calculated using the averaged quarterly data values for 2004, 2005 and 2006 for quarters 1 and 2 to replace the missing quarters in 2003.

Year AIRS Site ID

 Quarter 1 Quarter 2 Quarter 3 Quarter 4

Annual 

Average

470930028 470931013 470931017 470931020

2002 471050108 15.0 2002 2004 14.5 14.9 15.7 15.1

2003 471050108 11.67201 16.64932 20.1 12.67037 15.27 15.4 2003 2005 14.5 13.9 15.6 15.1

2004 471050108 11.28519 15.96 19.27 12.16667 14.67 15.3 2004 2006 15.2 11.8 15.6 15.2

2005 471050108 12.26 17.80333 21.16207 13.38276 16.15

2006 471050108 11.47083 16.18462 18.54286 13.66786 14.97 Controlling monitor DV

AIRS Site ID 2002 2003 2004 2005 2006

470930028 15.4 14.4 13.9 15.3 16.4

470931013 16.9 16.0 11.8

470931017 16.4 15.5 15.1 16.2 15.6

470931020 16.1 14.3 14.9 16.2 14.4

2004 2006 Averages 2003 Data

3 Yr DV

3 Yr Derived DV 

Loudon Site

Review of the annual average PM2.5 concentrations for these monitors from 2003 through 2006 

(Table 9- 6, Figure 9- 1) suggests that annual average PM2.5 concentrations at the Loudon 

monitor are not significantly different from the three Knox County monitors. The annual 

average from 2003 was elevated at this monitor, but a full year of data was not obtained in 2003. 

In other years with more complete data, the annual PM2.5 concentration at the Loudon monitor is 

comparable to other results observed across the region. 

 

47 The process of substitution has been utilized by EPA in generation of design values where some of a monitoring data is not present. In this 

case substitution is used for illustrative purpose only and helps in properly identifying the impact the lack of data has in developing a design value 

for this site. 
117 

Table 9- 6: Comparison of Annual Average PM2.5 Concentrations 

AIRS ID Address County

Number of Observations and Annual Average PM2.5 Concentration (μg/m3) 

2003 2004 2005 2006 

# Obs. PM2.5 # Obs. PM2.5 # Obs. PM2.5 # Obs. PM2.5

47-093-

0028 

1000 Francis 

Road Knox 100 14.4 107 13.9 86 15.4 96 16.4 

47-093-

1020 

4625 Mildred 

Drive Knox 337 14.3 317 14.9 294 16.2 319 14.4 

47-105-

0108 

130 Webb 

Drive Loudon 47 16.4 114 14.7 118 16.2 106 15.0 

47-093-

1017* 

1613 Vermont 

Avenue Knox 334 15.4 347 15.1 284 16.3 284 15.6 

* Controlling monitor. 

Figure 9- 1: Annual PM2.5 Concentrations 

As discussed in Section 8.0, the attainment test for the Knoxville-area monitors requires the 

calculation of RRFs at each monitor, based on the modeled concentrations for the baseline year 

and the future year (see Table 8- 11). When the modeled RRFs at Loudon were compared with 

the Knox County monitors, the modeled RRFs at the Loudon site were higher for most pollutants 

(Table 9- 7). 
118 

Table 9- 7: Comparison of RRFs 

AIRS ID County 

Site 

Name Qtr. 

RRF % Difference with 47-105-0108 (Loudon Co. Monitor) 

Crustal EC OC SO4 NO3

47-093-

0028 Knox 

1000 

Francis 

Road 

1 3.0% 4.8% 1.3% 1.7% -1.9% 

2 3.9% 2.2% 0.1% 1.4% -6.4% 

3 3.6% 2.0% -0.1% 2.0% -17.7% 

4 2.6% 1.9% 0.4% 1.9% -3.7% 

Avg. 3.3% 2.8% 0.4% 1.7% -7.3% 

47-093-

1017 Knox 

1613 

Vermont 

Avenue 

1 2.6% 7.8% 1.9% 2.1% -1.8% 

2 3.5% 5.5% 0.3% 1.6% -5.6% 

3 2.6% 5.1% 0.1% 2.7% -15.2% 

4 2.0% 5.3% 0.8% 2.6% -4.0% 

Avg. 2.7% 6.0% 0.8% 2.2% -6.6% 

47-093-

1020 Knox 

4625 

Mildred 

Drive 

1 2.6% 7.8% 1.9% 2.1% -1.8% 

2 3.5% 5.5% 0.3% 1.6% -5.6% 

3 2.6% 5.1% 0.1% 2.7% -15.2% 

4 2.0% 5.3% 0.8% 2.6% -4.0% 

Avg. 2.7% 6.0% 0.8% 2.2% -6.6% 

Where % Difference = [(Loudon RRF) – (Knox County Monitor RRF)] / (Loudon RRF) 

 Difference > 0% indicates that the relative reduction factor is higher at the Loudon County monitor. 

Comparison of the Knox County monitors with the Loudon monitor indicates that, modeled 

RRFs at the Loudon site are greater than other Knoxville-area RRFs for most pollutants. Nitrate 

RRFs tend to be lower at the Loudon monitors, but as previously indicated in Sections 2.0 and 

8.0, ambient PM2.5 in the Knoxville area consists primarily of sulfate and organic carbon, and the 

nitrate fraction tends to be less significant. The combined weight of ambient monitoring data 

and modeled RRF values indicates that the Loudon monitors will attain the annual PM2.5

NAAQS in 2009. 
119 

9.5. Summary of Projected Change in Emissions for 2008 and Early 2009 

Projected changes in emissions are summarized in Table 9- 8. 

Table 9- 8: Summary of Projected Emission Changes 

Facility Change 2002 Emissions* 2009 Emissions Projected 

Reduction (2002-

2009) 

TVA Bull 

Run Fossil 

Plant 

Installation and startup 

of wet scrubber 

projected for December 

2008. Year-round 

operation of existing 

SCRs for CAIR 

compliance, beginning 

in 2009. 

SO2: 42,188 tons 

(actual), 36,729 tons 

(typical) 

NOX: 17,909 tons 

(actual), 15,592 tons 

(typical) 

SO2: 8,657 tons** 

NOX: 2,078 tons** 

SO2: 28,072 tons 

NOX: 13,514 tons 

TVA 

Kingston 

Fossil Plant 

Year-round operation of 

existing SCRs for CAIR 

compliance, beginning 

in 2009. 

NOX: 26,089 tons 

(actual), 25,678 tons 

(typical) 

NOX: 3,238 tons** 22,440 tons 

* Data source: EGUs - ASIP 2002 actual and typical emissions inventories, ASIP 2009 emissions inventory. Change in emissions from 2002 to 

2009 is calculated as (2009 emissions) – (2002 typical emissions) 
120 

Table 9- 9: Qualitative Weighting of Evidence (Not Including Modeled Attainment Demonst

Analysis Data Source 

Key Assumptions and Outcomes Qualitative Weighting 

Air Quality Monitoring Data 

FRM monitoring data for Knoxville, Tennessee area. 

Downward trend in ambient PM2.5

levels from 1999 to 2006. Design value at the controlling monitor decreased by about 25% between 1999-2001 and 2004-2006. Monitoring data is collected per EPA specifications and is considered highly reliable. 

High weighting – monitoring data shows downward trend in PM2.5 emissions, consistent with 

known reductions. 

1999-2006 SO2 Emissions 

from TVA Bull Run and Kingston Fossil Plants, Statewide Utility SO2

Emissions in Tennessee, Regional Utility SO2

Emissions 

Acid Rain Program monitoring data from 1999 to 2006. 

Data is based on continuous emissions monitoring for ARP compliance and is considered to be valid and highly reliable. 

High weighting – comparison of emission trends with ambient PM2.5 monitoring suggests a 

strong relationship between declining SO2 emissions and 

improvements in ambient PM2.5

between 1999 and 2006. 

Projected Emission Controls at TVA Bull Run Fossil Plant 

TVA-stated construction schedule, visual confirmation of start of construction. 

Significant reduction in SO2

emissions by 2009. Physical construction of the scrubber is underway, analysis assumes completion. Startup of the wet scrubber at this facility is expected to occur December 2008. The emission inventory projects that SO2 emissions from 

this source will be reduced from 36,729 tons/year (2002 typical emissions basis) to 8,657 tons/year in 2009. 

High weighting – Physical construction demonstrates a large capital investment in emission controls and makes projected emission reductions highly likely. 
121 

Table 9- 9 (Continued) 

Analysis Data Source Key Assumptions and Outcomes Qualitative Weighting CAIR Modeling Results 

CAIR Final Rule and associated technical support documents 

CAIR modeling results show improvement in ambient PM2.5, 

while predicting that Knoxville area will remain nonattainment in 2009. 

Low to medium weighting – CAIR modeling shows a change in ambient PM2.5 due to SO2 controls on electric 

utilities, but CAIR modeling is based on a different year (2010). CAIR modeling also indicates that PM2.5

design value in 2010 will be higher than is currently indicated by ambient monitoring in the Knoxville area. 

Other SO2 Emission 

Inventory Changes 

VISTAS/ASIP Base G2 Emission Inventory 

Small growth in area source SO2

emissions is offset by elimination of most SO2 emissions from 

mobile sources between 2002 and 2009. Point sources are still responsible for most SO2 emissions 

in 2009. 

Low to medium weighting – mobile and area source emissions are a small fraction of total SO2 emissions 

inventory. SO2 reductions from 

mobile sources may have a positive impact on attainment in high-traffic areas. 

PM2.5 Emission Inventory 

Changes 

VISTAS/ASIP Base G2 Emission Inventory 

Some reductions from nonroad and onroad mobile sources are offset by gains from area and point sources. Small overall increase in direct PM2.5 emissions. 

Low weighting – direct PM2.5

emissions from all source categories are much lower than SO2 emissions. 

Emissions reductions from mobile sources may have a positive impact in high-traffic areas. 

SO2 Reductions at U. S. 

DOE Oak Ridge. 

VISTAS/ASIP Base G2 Emission Inventory and facility construction permit application. 

About 2,000 tons/year of SO2

(2002 actual emissions) will be eliminated. 

Low weighting – emissions reductions were considered for RACT analysis, but the impact on attainment was not quantified. The reductions should have some degree of positive impact on ambient PM2.5

levels. These reductions were not modeled as part of the 2009 attainment demonstration. 
122 

Table 9- 9 (Continued)

Analysis Data Source 

Key Assumptions and Outcomes Qualitative Weighting 

SO2 Reductions at TVA 

Kingston (see Section 10.0). 

TVA construction schedule, onsite verification that scrubber construction is underway. 

Startup of scrubber for Kingston units 1-4 may reduce emissions in 2009 if construction is finished ahead of schedule. 

Low weighting – startup of scrubber is not expected before the end of 2009. Based on existing construction schedule, scrubber installation is not expected to support attainment for the year 2009, if construction proceeds as scheduled. Kingston scrubbers will provide significant support to Knoxville attainment in 2010 and subsequent years. Physical construction demonstrates a large capital investment in emission controls and makes projected emission reductions highly likely. 

N

R
123 

10.0 CONTINGENCY MEASURES 

Consistent with section 172(c)(9) of the Act and 40 CFR §51.1012, the State must submit in each 

attainment plan specific contingency measures to be undertaken if the area fails to make 

reasonable further progress, or fails to attain the PM2.5 NAAQS by its attainment date. As 

discussed in the preamble to the PM2.5 implementation rule, the key requirements associated with 

contingency measures are: 

• Contingency measures must be fully adopted rules or control measures that are ready to 

be implemented quickly upon failure to meet RFP or failure of the area to meet the 

standard by its attainment date. 

• The SIP should contain trigger mechanisms for the contingency measures, specify a 

schedule for implementation, and indicate that the measures will be implemented without 

further action by the State or by EPA. 

• The contingency measures should consist of other control measures for the area that are 

not included in the control strategy for the SIP. 

• The measures should provide for emission reductions equivalent to about one year of 

reductions needed for RFP, based on the overall level of reductions needed to 

demonstrate attainment divided by the number of years from the 2002 base year to the 

attainment year. 

Contingency measures are those measures that would not be included in the attainment strategy 

for various reasons; for example, they may not be as economically feasible as other measures 

that are considered to be RACM, or it may not be possible to implement the measures soon 

enough to advance the attainment date (e.g. federal mobile source measures based on the 

incremental turnover of the motor vehicle fleet each year). 

10.1. Contingency Measures for SO2 

Tennessee has elected to use a portion of the SO2 emission reductions obtained pursuant to the 

Clean Air Interstate Rule (40 CFR 96 Subparts AAA through III and TAPCR 1200-3-14-.04) to 

comply with the contingency plan requirements of the PM2.5 Implementation Rule. Specifically, 

Tennessee will use the reductions at Units 6 through 9 of Tennessee Valley Authority’s Kingston 

Fossil Plant to comply with the contingency plan requirements48. 

• The CAIR rules were adopted by Tennessee and filed with the Secretary of State on 

August 10, 2006. Tennessee’s request to incorporate this rule into the State 

 

48 TVA’s Bull Run Fossil Plant is also located within the nonattainment area. However, Tennessee is not claiming the reductions at Bull Run as 

a contingency measure. Construction of the wet scrubber at Bull Run is projected to be complete by the end of 2008, and the scrubber is 

projected to be operational throughout 2009. The ASIP attainment modeling for the Knoxville nonattainment area assumed that the scrubber at 

Bull Run would be operational. Since Tennessee used Bull Run’s projected reductions to demonstrate attainment in 2009, the State may not use 

the same reductions as a contingency measure. The situation for TVA’s Kingston Fossil Plant is different, as explained below. 
124 

Implementation Plan49 is pending, and the CAIR Federal Implementation Plan (40 CFR 

97 Subparts AAA through III) and abbreviated SIP provisions until the full SIP is 

approved. Tennessee has fully adopted the CAIR rules50 and implementation of the rules 

is currently underway. The emission reductions required by CAIR will occur without 

further action by the State. 

• The Implementation Rule states that the SIP should contain trigger mechanisms for the 

contingency measures, specify a schedule for implementation, and indicate that the 

measures will be implemented without further action by the State or by EPA. For the SO2

reductions at TVA Kingston, the requirement to include a trigger mechanism does not 

apply, since the emission reductions will occur regardless of the attainment status in 

2009. 

• The attainment modeling for Knoxville indicated that the PM2.5 design value for 2009 

would attain the NAAQS, but this modeling assumed that wet scrubber controls for the 

Kingston facility would not be in place during the attainment year. The SO2 reductions at 

Kingston comply with the requirement that contingency measures should consist of other 

control measures for the area that are not included in the control strategy for the SIP. 

• The emission reductions in the contingency plan provide for greater than one year of 

reductions needed for RFP, based on the overall level of reductions needed to 

demonstrate attainment divided by the number of years from the 2002 base year to the 

attainment year. The proposed contingency measures will exceed this requirement by an 

ample margin, as indicated in Table 10- 1. 

Table 10- 1: SO2 Reductions from Contingency Measures 

Actual SO2 emissions from all source categories (area, nonroad, onroad, and point 

sources) in 2002 baseline year 

134,218 tons 

Projected SO2 emissions from all source categories (area, nonroad, onroad, and 

point sources) in 2009 attainment year 

93,155 tons 

SO2 reductions required from proposed contingency measures 5,866 tons51

Projected SO2 reductions from TVA Kingston Units 6-9 after scrubber installation 30,224 tons52

 

49 Tennessee requested adoption of the CAIR rules into the SIP on September 8, 2006. 

50 With some revisions pending. 

51 (134,893 tons – 93,852 tons)/(7 years) = 5,863 tons 

52 Projected SO2 reductions from Units 6-9 of TVA’s Kingston Fossil Plant were calculated from the ASIP emission inventories by (1) 

comparing 2002 actual emissions and 2009 emissions from TVA’s Bull Run Fossil Plant; (2) estimating a control efficiency for TVA Bull Run 

based on 2002 and 2009 emissions; (3) assuming the same control efficiency for TVA Kingston Units 6-9 upon installation and startup of the 

scrubber (TVA’s Kingston and Bull Run Fossil Plants will have the same control equipment); and (4) using the TVA Kingston’s 2002 actual 

emissions and the assumed control efficiency to project the 2009 emissions for Units 6-9. The results are summarized in the following table: 

Actual SO2 Emissions for TVA Bull Run in 2002 (tons) 36,729 

Projected SO2 Emissions for TVA Bull Run in 2009 (tons) 8,657 

Projected SO2 Control Efficiency for TVA Bull Run in 2009 76.4% 

Actual SO2 Emissions for TVA Kingston in 2002 (tons) 76,055 

Heat Input for TVA Kingston (Units 1-9) 106,727,181 

Heat Input for TVA Kingston (Units 6-9) 54,427,415 

2002 Heat Inputs for Units 6-9, % of Total 51.0% 

Estimated Actual 2002 SO2 Emissions for TVA Kingston Units 6-9 (tons) 39,559 
125 

• Direct PM2.5 emissions will increase by 66 tons/year between 2002 and 2009, based on 

the 2002 actual emission inventory. Because the air quality modeling demonstrates 

attainment with no reduction in direct PM2.5 emissions, no contingency measures are 

proposed for this pollutant. 

Tennessee notes that the SO2 emission reductions relied upon for contingency planning will be of 

greater magnitude than SO2 or direct PM2.5 emission reductions that could be obtained from any 

other source category. Tennessee also notes that these reductions will be achieved more quickly 

than reductions from other source categories, since contingency rulemaking would need to allow 

a schedule of three years or more for implementation of equivalent measures (assuming that such 

equivalent reductions could be obtained from other sources). 

10.2. Contingency Measures for NOX 

Contingency measures for NOX are discussed in Attachment Q of the SIP. 

 

Projected SO2 Control Efficiency for TVA Kingston (based on TVA Bull Run) 76.4% 

Projected SO2 Emissions for TVA Kingston After Scrubber Installation (tons) 9,335 

Projected SO2 Reduction for TVA Kingston Units 6-9 After Scrubber 

Installation (tons) 30,224 
126 

 REASONABLE FURTHER PROGRESS 

Clean Air Act §172(c)(2) requires plans for nonattainment areas to require “reasonable further 

progress,’’ (RFP) as defined in CAA §171(1). The Act requires nonattainment areas to make 

“such annual incremental reductions in emissions of the relevant air pollutant as are required by 

this part or may reasonably be required by the Administrator for the purpose of ensuring 

attainment of the applicable national ambient air quality standard by the applicable date.” In 

general terms, the goal of RFP is to allow areas to achieve generally linear progress toward 

attainment. The RFP requirements were included in the Clean Air Act to assure steady progress 

toward attaining air quality standards, as opposed to deferring implementation of all measures 

until the end date by which the standard is to be attained. 

40 CFR §51.1009 states that, consistent with CAA §172(c)(2), State Implementation Plans for 

PM2.5 nonattainment areas must demonstrate reasonable further progress as provided in 

§51.1009(b) through (h). Paragraph (b) of that section states that “if the State submits to EPA an 

attainment demonstration and State implementation plan for an area which demonstrates that it 

will attain the PM NAAQS within five years of the date of designation, the State is not required 

to submit a separate RFP plan. Compliance with the emission reduction measures in the 

attainment demonstration and State implementation plan will meet the requirements for 

achieving reasonable further progress for the area.” 

Consistent with the provisions of §51.1009(b), Tennessee has submitted a State Implementation 

Plan that demonstrates that the Knoxville nonattainment area will attain the annual PM2.5

NAAQS within five years of designation. Therefore, no additional provisions for Reasonable 

Further Progress are required. Compliance with the emission reduction measures in this 

attainment demonstration and State Implementation Plan will meet the requirements for 

achieving reasonable further progress for the Knoxville area. 
Attachments 

Please refer to the compact disc included with this 

submittal for electronic copies of all attachments.