# Attainment Demonstration

Knoxville, Tennessee Annual PM 2.5 

# Nonattainment Area

(Anderson, Blount, Knox, Loudon, and Roane Counties)

Prepared by:

Tennessee Department of Envi ronment and Conservation Division of Air Pollution Control 9th Floor L&C Annex 401 Church Street Nashville, TN 37243i 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 PM 2.5 CONCEPTUAL DESCRIPTION ............................................................................. 6 3.0 NO X INSIGNIFICANCE .................................................................................................. 25 3.1. Significance of Precursors Contributi ng to Fine Particulate Matter ............................ 25 3.2. Determination of NO X Insignificance .......................................................................... 26 3.3. Elements of NO X Insignificance Demonstration ......................................................... 26 3.4. NO X Emissions Source Categories .............................................................................. 27 3.5. Federal Reference Method Observations ..................................................................... 29 3.6. Speciated Trends Network Observations ..................................................................... 33 3.7. Speciated PM 2.5 for Federal Reference Method Monitors ........................................... 34 3.8. Speciated Modeled Attainment Test ............................................................................ 36 3.9. NO X 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. PM 2.5 Motor Vehicle Emission Budget........................................................................ 70 7.3. Presumed Precursors for PM 2.5 .................................................................................... 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 PM 2.5 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 NO X ................................................................................ 125 REASONABLE FURTHE R PROGRESS ............................................................................ 126ii LIST OF TABLES

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

Table 2- 1: PM 2.5 Monitored Major Components .................................................................... 7

Table 2- 2: Component Concentr ations Relative to total PM 2.5 ............................................... 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 Emi ssions Data, Three-Year Averages ............................... 14

Table 2- 7: Linear Co rrelation Coefficients ........................................................................... 15

Table 2- 8: CAIR Mode ling Results – Projected PM 2.5 Concentrations for Knox County ... 16

Table 3- 1: 2002 Actual NO X Emissions for Counties in Knoxville, TN PM 2.5 Nonattainment Area. ......................................................................................................................... ............... 25

Table 3- 2: 2009 NO X Emissions for Counties in Knoxville, TN PM 2.5 Nonattainment Area.

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

Table 3- 3: Tennessee NO X 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 PM 2.5 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 PM 2.5 for ASIP 2009 Base G2 Future Design Values and for Tennessee Statewide 100% NO X Emissions Reduction for FRM M onitors in Knoxville, TN PM 2.5 Nonattainment Area ...................................................................................................... 36

Table 3- 7: Annual Average PM 2.5 for ASIP Base G2 2009 Future Design Values and for Tennessee Statewide 70% NO X Emissions Reduction for FRM monitors in Knoxville, TN PM 2.5 Nonattainment Area ...................................................................................................... 37

Table 3- 8: Changes in Qu arterly and Annual Speciated PM 2.5 (μg/m 3 ) Between 2009 Future Design Values and Tennessee Statewide 100% NO X Emissions Reductions for FRMiii Monitors in Knoxville, TN PM 2.5 Nonattainment Area .......................................................... 38

Table 3- 9: Changes in Qu arterly and Annual Speciated PM 2.5 (μg/m 3 ) Between 2009 Future Design Values and Tennessee Statewide 70% NO X Emissions Reductions for FRM Monitors in Knoxville, TN PM 2.5 Nonattainment Area ......................................................................... 39

Table 4- 1: Total 2009 Annual Vehicl e Miles Traveled in the Knoxville PM 2.5 Nonattainment Area Used in ASIP Attainment Modeling ..................................................... 46

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

Table 4- 3: 2002 SO 2 Emissions ............................................................................................ 47

Table 4- 4: 2002 PM 2.5 Emissions ......................................................................................... 47

Table 4- 5: Point Sources in the Knoxvill e Nonattainment Area with > 100 tons/year SO 2 Emissions, Sorted by Rank (2002 Actual Emissions) ............................................................ 48

Table 4- 6: Point Source s with > 100 tons/year PM 2.5 Emissions ......................................... 49

Table 4- 7: 2009 SO 2 Emissions ............................................................................................ 50

Table 4- 8: 2009 PM 2.5 Emissions ......................................................................................... 51

Table 4- 9: 2002-2009 SO 2 Emission Reductions ................................................................. 52

Table 4- 10: 2002-2009 SO 2 Emission Reductions ............................................................... 52

Table 4- 11: 2002-2009 PM 2.5 Emission Reductions ............................................................. 53

Table 4- 12: 2002-2009 PM 2.5 Emission Reductions .............................................................. 53

Table 4- 13: Statewide SO 2 Emission Inventory for Tennessee ............................................ 54

Table 4- 14: Statewide PM 2.5 Emission Inventory for Tennessee ......................................... 54

Table 5- 1: SO 2 Emissions 2000-2006 (Acid Rain Program Data) ....................................... 56

Table 5- 2: Year-t o-Year Change in SO 2 Emissions .............................................................. 56

Table 5- 3: PM 2.5 Contributions to Tennessee Nonattainment Counties ............................... 58

Table 5- 4: CAIR Annual SO 2 State Trading Budgets .......................................................... 59

Table 5- 5: CAIR SO 2 Controls at Tennessee Va lley Authority EGUs ................................. 59

Table 7- 1: Total 2009 Annual Vehicl e Miles Traveled in the Knoxville PM 2.5 Nonattainment Area ............................................................................................................ .... 66iv Table 7- 2: PM 2.5 MVEB for 2009 ......................................................................................... 67

Table 8- 1: Vertical Laye r 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 Bi as and Fractional Error Model Performance Metrics ..................... 85

Table 8- 4: ASIP Model Perfor mance Goals and Criteria for PM 2.5 Components ................. 85

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

Table 8- 6: Quarterly and Annual Average Co mponent-Specific Concentrations for the FRM Monitors in the Knoxville, TN PM 2.5 Nonattainment Area .................................................. 104

Table 9- 1: 2009 Change in SO 2 Emissions by Category ..................................................... 110

Table 9- 2: 2009 Change in PM 2.5 Emissions by Category ................................................. 111

Table 9- 3: Additional SO 2 Reductions Not Included in 2009 Emission Inventory ............ 111

Table 9- 4: Qualitative Weighting of Ev idence (Not Including Modeled Attainment Demonstration) ................................................................................................................ ..... 116

LIST OF FIGURES

Figure 1- 1: PM 2.5 Final Nonattainment Designati ons, Effective April 5, 2005 ...................... 2

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

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

Figure 2- 1: Regional Em issions Distribution and PM 2.5 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 PM 2.5 Sites .................................................................... 12

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

Figure 2- 6: PM 2.5 Trends for Knoxville (2000-2006) ........................................................... 15

Figure 2- 7: Scatter Plot of Am bient Monitored Data and Tennessee SO 2 Emissions .......... 15

Figure 2- 8: Scatter Plot of Am bient Monitored Data and Regional SO 2 Emissions ............ 15v Figure 2- 9: Wind Rose Analysis for High PM 2.5 Days ......................................................... 17

Figure 2- 10: General Trends of Ambient PM 2.5 and Ozone, Knoxville, Tennessee............. 18

Figure 2- 11: Comparison of Ambient PM 2.5 and Ozone, Knoxville, Tennessee .................. 19

Figure 2- 12: Comparison of PM 2.5 Speciated Components, FRM Monitor 47-093-1020 .... 20

Figure 2- 13: Comparison of PM 2.5 Speciated Components (Winter Months Only), FRM Monitor 47-093-1020 ........................................................................................................... ... 21

Figure 3- 1: Annual Average PM 2.5 from 2000-2006 at Three Fe deral Reference Method Monitors in Knox County, TN. ............................................................................................... 26

Figure 3- 2: Quarterly and Annual Average PM 2.5 in 2000 Through 2006 from Federal Reference Method Monitors in Knox County, TN PM 2.5 Nonattainment Area. .................... 28

Figure 3- 3: Quarterly and Annual Average PM 2.5 in 2000 through 2006 from Federal Reference Method Monitors for Counties in the Knoxville, TN PM 2.5 Nonattainment Area. 29

Figure 3- 4: Quarterly and Annual Average Speciated PM 2.5 Mass from Speciated Trend Network (STN) Monitor for 2002 through 2006 at Spring Hill Elementary School in Knoxville, TN (47-093-1020). ................................................................................................ 3 0

Figure 3- 5: Quarterly and Annual Average 2002 Base Design Values (DVB) Calculated Using the SANDWICH Method and the 2000-2004 PM 2.5 Data for the Spring Hill Elementary School FRM monitor (47-093-1020) in Knoxville, TN ...................................... 32

Figure 3- 6: Annual Average PM 2.5 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% NO X Reduction in 2009 for FRM Monitors in Knoxville, TN PM 2.5 Nonattainment Area ............ 40

Figure 3- 9: Annual Aver age Speciated Response to Tennessee Statewide 70% NO X Reduction in 2009 for FRM Monitors in Knoxville, TN PM 2.5 Nonattainment Area ............ 40

Figure 5- 1: Tenne ssee and Regional SO 2 Emissions ............................................................ 57

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

Figure 8- 1: MM5 Horizontal Domain (B lue) 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. ......................................................... 84vi Figure 8- 4: Scatter Plots of Predicted and Observed Sulfate (SO 4 ) 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 Pr edicted and Observed Nitrate (NO 3 ) 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 (NH 4 ) 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 a nd October 2002, STN Sites in Tennessee and the CMAQ 2002 36 and 12 km Base G2 Ac tual Base Case Simulation ...................................... 90

Figure 8- 8: Scatter plots of Predicted and Observed Elementa l Carbon (EC) Concentrations for January, April, July and October 2002, ST N Sites in Tennessee and the CMAQ 2002 36 and 12 km Base G2 Actual Base Case Simulation ................................................................. 91

Figure 8- 9: Scatter Plots of Predicte d and Observed Fine Particulate Mass (PM 2.5 ) Concentrations for January, April, July a nd October 2002, STN Sites in Tennessee and the CMAQ 2002 36 and 12 km Base G2 Ac tual Base Case Simulation ...................................... 92

Figure 8- 10: Scatter Plots of Predicte d and Observed Fine Particulate Mass (PM 2.5 ) Concentrations for January, April, July and October 2002, FRM Sites in Tennessee and the CMAQ 2002 36 and 12 km Base G2 Ac tual Base Case Simulation ...................................... 93

Figure 8- 11: Soccer Plot of Monthly Fractio nal Bias versus Fractional Gross Error for PM 2.5 Mass at FRM Monitors in Tennessee for the CMAQ 12-km 2002 Base G2 Actual Base Case Simulation .................................................................................................................... ........... 94vii 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 SO 2 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 PM 2.5 Projections Attachment P Public Participation Attachment Q NO X Addendum

LIST OF ACRONYMS AND ABBREVIATIONS

AEB Actual Emissions Basis AIRS Aerometric Information Retrieval System AQS Air Quality System ASIP Association for Southeas tern Integrated Planning BACT Best Availabl e 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 Multisc ale 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 modelviii I/M Inspection and Maintenance IMPROVE Interagency Monitoring of Protected Environments IPM Integrated Planning Model KAT Knoxville Area Transit km Kilometer μg/m 3 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 f actor model for onroad mobile sources NADP National Acid Deposition Network NAAQS National Ambient Air Quality Standards NH 3 Ammonia NH 4 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) NO X Nitrogen Oxides NO 3 Nitrate Ion OC Organic Carbon OPP Other primary inorganic particulate matter (crustal) PBW Particle Bound Water PM 2.5 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 Availa ble Control Measures RACT Reasonably Availa ble Control Technology RBLC RACT-BACT-LAER Clearinghouse RFP Reasonable Further Progress RPO Regional Planning Organization RRF Relative Reduction Factor SANDWICH Sulfate, Adjusted Nitrate, De rived 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 Ke rnel Emissions Modeling System SNCR Selective Noncatalytic Reduction SO 2 Sulfur Dioxide SO 4 Sulfate Ion STN Speciated Trends Network TAPCR Tennessee Air Pollution Control Regulationsix TDEC Tennessee Department of Environment and Conservation TDOT Tennessee Departme nt of Transportation TEB Typical Emissions Basis TN Tennessee TOMS Total Ozone Mapping Spectrometer TVA Tennessee Valley Authority VISTAS Visibility Improveme nt State and Tribal Association of the Southeast VOC Volatile Organic Compounds WRAP Western Air Re gional Partnershipx ACKNOWLDEDGEMENTS

Tennessee gratefully acknowledges the efforts of Pat Brewer and the ASIP workgroup for their assistance with this document. We woul d also like to thank the members of the North Carolina Department of Environment and Natura l Resources, Division of Air Quality, for performing NO X zero-out modeling runs for Tennessee.xi EXECUTIVE SUMMARY

The Knoxville, Tennessee PM 2.5 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 site s within this region indicated that the annual average PM 2.5 concentrations exceeded the 15.0 μg/m 3 National Ambient Air Quality Standard (NAAQS), and EPA de signated the area as nonatta inment for the annual PM 2.5 NAAQS, effective April 5, 2005.

Air quality modeling conducted fo r Tennessee by the Association for Southeastern Integrated Planning (ASIP) indicates that the Knoxville-area nonattainmen t counties will attain the NAAQS in 2009. The model results are ba sed 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 PM 2.5 NAAQS in the Knoxville region based upon impl ementation of Federal measures, and no additional local cont rols are planned.1 1.0 INTRODUCTION

Fine particles in the atmosphere are comprise d of a complex mixture of components. Common constituents include: sulfate (SO 4 ); nitrate (NO 3 ); ammonium; elemental carbon; a great variety of organic compounds; and inorgani c “crustal” material, which in cludes 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 PM 2.5 ). ‘‘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 orga nic particles from gasolin e engines). ‘‘Secondary’’ particles (e.g., sulfate a nd nitrate) form in the atmosphere as a result of various chemical reactions.

EPA established air quality standards for PM 2.5 based on evidence from numerous health studies demonstrating that serious health effects are associated with e xposures to elevated levels of PM 2.5 . Epidemiological studies have shown statistically significant correlations between elevated PM 2.5 levels and premature mortality. Other important effects associated with PM 2.5 exposure include aggravation of respirat ory and cardiovascular disease (a s indicated by in creased hospital admissions, emergency room visits, absences from school or work, and restricted activity days), changes in lung function and increased respirator y symptoms, as well as new evidence for more subtle indicators of cardiovascular health . Individuals particularly sensitive to PM 2.5 exposure include older adults, people with h eart and lung disease, and children.

On July 18, 1997, EPA revised the NAAQS for partic ulate matter (PM) to add new standards for fine particles, using PM 2.5 as the indicator. EPA established health-based (primary) annual and 24-hour standards for PM 2.5
. 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 PM 2.5 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 conc entrations. Following a second review of the NAAQS in October 2006, the 24-hour PM 2.5 standard was strengthened to a level of 35 micrograms per cubic meter, based on the 3-year average of the 98 th percentile of 24-hour concentrations, and the level of th e annual standard remained unchanged. In both 1997 and 2006 EPA established welfare-based (secondary) standa rds identical to the levels of the primary standards. EPA’s final PM 2.5 designations for areas violating the 1997 standards were issued on December 17, 2004 and published in the Federal Register on January 5, 2005 1

. 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 attainme nt dates required in the C AA. To assist States with the development of implementation plans, EP A issued the fine particle implementation rule on April 25, 2007. This rule requi res States to submit their SIPs to EPA by April 5, 2008, three years from the effective da te of the designations.

The Knoxville Tennessee PM 2.5 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 Aut hority’s Kingston Fossil Plant.

1 Federal Register / Vol. 70, No. 3 / Wednesday, January 5, 2005, page 944.2 Figure 1- 1 : PM 2.5 Final Nonattainment Designa tions, Effective April 5, 2005

Figure 1- 2 : Map of Roane County Pa rtial Nonattainment Area3 For the calendar years 2001 to 2003, ai r quality monitoring at severa l sites within this region indicated that the highest annual average PM 2.5 concentrations exceeded the 15.0 μg/m 3 NAAQS (Table 1- 1). EPA subsequently designated the area as nonattainment for the annual PM 2.5 NAAQS, effective April 5, 2005. Air quality modeling data for the Knoxville area predicts that PM 2.5 concentrations at these monitors will attain the NAAQS during the 2009 calendar year 2

. These areas are predicted to attain the PM 2.5 NAAQS based on existi ng State and national measures, without additi onal local controls.

Table 1- 1: Knoxville Area Design Values 3

AIRS ID Address County PM 2.5 Design Value in μg/m 3
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 PM 2.5 implementation rule states that, since PM 2.5 designations have an effective date of April 5, 2005, the initial 5-year attainment date for PM 2.5 areas would be no later than April 5, 2010, based on air quality data from the th ree 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 Attainme nt of Air Quality Goals for Ozone, PM 2.5 , and Regional Haze states:
“The logic for requiring emissions reducti ons by the year (or season) immediatel y 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 dead line, EPA is to evaluate whether areas ha ve attained. If the area is clean for the last three years, then the area has met the attainment d eadline. But if the area was a bove the standard for earlier years/seasons but has clean da ta 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 ex tension of the attainment deadline. If the air is clean again the following year, the area is eligible for a second 1-year extens ion 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”.) Ther efore, emissions in the year preceding the attainment year should be at a level that is consistent with attainment. It also follo ws that the year preceding the attainment year should be modeled for attainment planning purposes.” [page 35]
Thus, the PM 2.5 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 Coun ty) and 47-105-0108 (130 Webb Drive in Loudon County) did not hav e 12 quarters of complete data during the 2000-2 004 baseline period and therefore were not a ddressed in the modeled attainment demon stration. Tennessee is including the data from the Loudon monitor in the wei ght of evidence section (Section 9.0) to demonstrate, based o n the weight of evidence, that both monitors will attain th e NAAQS in 2009. Monitor 47-093-1013 was op erated April 2002 to February 2004 and s hut down until March 2007.4 Figure 1- 3: Map of FRM Monitors in Knoxville Nonattainment Area

The Clean Air Fine Particle Implementation Ru le (40 CFR 51 Subpart Z) was promulgated on April 25, 2007. This rule requi res affected States to addr ess nonattainment by adopting a federally enforceable State Implementation Plan (SIP). The SIP documents how an area will attain the NAAQS and generally contains f our elements: emission inventory, modeled attainment demonstration, Reasonably Availa ble Control Technology/Reasonably Available Control Measures (RACT/RACM) analysis, and adoption of controls. 40 CFR 51 Subpart Z specifies the followi ng requirements for PM 2.5 SIPs:

• Affected States must submit the SIP no la ter than three years from the date of designation.

• The SIP must identify and evaluate sources of PM 2.5 direct emissions and PM 2.5 attainment plan precursors in acco rdance with §§51.1009 and 51.1010, as follows:

- The SIP must address sulfur dioxide as a PM 2.5 attainment plan precursor and evaluate sources of SO 2 emissions in the State for control measures.5 - The SIP must address NO X as a PM 2.5 attainment plan precursor and evaluate sources of NO X emissions in the State for control measures, unless the State and EPA provide an appropriate technical de monstration for a specific area showing that NO X emissions from sources in the State do not significantly contribute to PM 2.5 concentrations in the nonattainment area.

- The SIP is not required to address VOC as a PM 2.5 attainment plan precursor and evaluate sources of VOC emissions in th e 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 PM 2.5 concentrations in the nonattainment area, or unless EPA provides such a technical demonstration.

- The SIP is not required to address ammonia as a PM 2.5 attainment plan precursor and evaluate sources of ammonia emissions from sources in the State for control measures, unless the State provides an ap propriate technical demonstration for a specific area showing that ammonia em issions from sources in the State significantly contribute to PM 2.5 concentrations in the nonattainment area, or unless EPA provides such a technical demonstration.

• Consistent with CAA §172(a)(2)(A), PM 2.5 nonattainment areas must demonstrate attainment of the NAAQS no more than five y ears 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 PM 2.5 modeling guidance.

• SIPs must include emission inventories for direct PM 2.5 emissions and emissions of PM 2.5 precursors, as well as any a dditional emission inventory info rmation needed to support an attainment demonstration. For purposes of defining the data elements for these inventories, the PM 2.5 and PM 2.5 precursor-relevant data element requirements under 40 CFR 51 Subpart A shall apply.

• SIPs must include provisions for reasona bly available control measures (RACM), reasonably available control technology (RACT) , and reasonable further progress (RFP), as necessary to demonstrate attainment.

• SIPs must include specific contingency measur es to be undertaken if the area fails to attain the PM 2.5 NAAQS by its attainment date. The c ontingency measures must take effect without significant furthe r action by the State or EPA.6 2.0 PM 2.5 CONCEPTUAL DESCRIPTION

Development of a PM 2.5 conceptual model is necessary for any analysis of PM 2.5 attainment issues. EPA has suggested a series of questions 4 that, when answered, de scribe the nonattainment problem. They are:

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

2. What is the relative impo rtance of measured primary and secondary components of PM 2.5 measured at sites violating the NAAQS?

3. What are the most prevalen t components of measured PM 2.5 ?

4. Does the measured mix of PM 2.5 components appear to roughly agree with mix of emission categories surroundi ng the monitoring sites?

5. Do there appear to be any area s with large gradients of primary PM 2.5 in monitored or unmonitored areas?

6. Is there any indication of what precurs or 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 ma jor changes in emissions of PM 2.5 or its precursors in or near the nonattainment area? What?

9. Are there discernible trends in design valu es or other air quality indicators which have accompanied a change in emissions?

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

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

12. Are there any distinctive meteorological m easurements at the surface or aloft which appear to coincide with occasions with PM 2.5 concentrations in excess of 15.0 μg/m 3 ?

13. Do periods with high measured particulat e 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 PM 2.5 problem. For example, questions 1, 2 and 3 can indicate whet her the area’s nonattainment problem includes

4 U. S. EPA, Guidance on the Use of Models and Other Analysis for De monstrating Attainment of Air Quality Goals for Ozone, PM 2.5

, and Regional Haze , April 2007, pages 128-130.7 significant local or regional components. Ques tions 11, 12 and 13 may be used to assess the relationship of ozone and particul ate matter reductions, and whethe r it is appropriate to examine the effects of existi ng strategies to reduce ozone and national PM 2.5 control measures before simulating additional control measures. Question s 4 and 5 can indicate whether a “local area analysis” is needed, and question 7 can suggest wh ether it is necessary to model with very small grid cells, at least for th e secondary components of PM 2.5
. To bring the area into attainme nt, an understanding of the chemi cal and physical factors that influence PM 2.5 in the area of interest and that potenti ally result in exceedances of the annual PM 2.5 standard are needed. EPA’s questions have b een used to develop a conceptual description for the Knoxville area’s PM 2.5 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 PM 2.5 precursors and by regional transport of emissions from upwind areas. The atta inment demonstration modeling conducted for Tennessee by the Association for Sout heastern Integrated Planning (ASIP) 5 demonstrated that the area would attain the NAAQS w ith a mixture of controls for both local and regional sources. Large regional sources located within the Knoxville area are believed to impact local PM 2.5 concentrations.

2. What is the relative importance of me asured primary and secondary components of PM 2.5 measured at sites violating the NAAQS?

PM 2.5 is a mixture of primary components (directly emitted PM 2.5 ) and secondary precursors that react in the atmosphere to form fine particulate matter. PM 2.5 in the Knoxville area includes the following components:

• Nitrates are formed from atmospheric reactions of NO X with ammonia. NO X is emitted from all combustion processes, including onr oad 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 SO 2 with ammonia. Coal-fired electric utilities account for most SO 2 emissions, with smaller quantiti es emitted by stationary and mobile sources that burn fuel oils.

• Ammonia that reacts with NO X and SO 2 is emitted from automobile catalysts, sewage treatment, and agriculture.

• Organic carbon is a complex category that in cludes motor vehicle em issions, industrial

5 In 2001, southeastern States began collaborative work on Stat e Implementation Plans to address regional haze through the Visi bility Improvement State and Tribal Asso ciation of the Southeast (VISTAS) . VISTAS member States include Alabama, Georgia, Kentucky, Mississippi, North Carolina, South Carolina Tennessee, Virginia, a nd West Virginia, and the local programs within these States.

The PM 2.5 attainment demonstration builds upon the VI STAS work through the Association for Sout heastern Integrated Planning (ASIP). The ASIP work group includes the original VISTAS members. The collabor ative approach of VISTAS and AS IP allows member States to ad dress regional issues, such as interstate transport, and to sa ve labor by avoiding duplicati on of modeling efforts.8 VOC emissions, and biogenic compounds. Tolu ene, xylene, and trimethyl benzene are considered to be the most significant indus trial precursors for secondary organic aerosol (SOA).

The major PM 2.5 components measured at speciation monitor 47-093-1020 (Mil dred Drive) are shown in Table 2- 1:

Table 2- 1: PM 2.5 Monitored Major Components Speciation Site 47-093-1020

Year PM 2.5 (μg/ m 3 ) * PM 2.5 (μg/ m 3 ) ** Nitrate (μg/ m 3 ) Sulfate (μg/ m 3 ) Organic Carbon (μg/ m 3 ) Elemental Carbon (μg/ m 3 ) Ammonium (μg/ m 3 )

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 specia tion sampler results may result from the sample collection frequency of the respective monitors. Th e 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 prevale nt components of measured PM 2.5 ?

For the Knoxville region, the PM 2.5 components are listed by percentage of total PM 2.5 in Table 2- 2. On an annual average basis, the most prevalent PM 2.5 components for all years were, in order, organic carbon, sulfate, and ammonium . Nitrate tends to replace ammonium when individual daily sampled values are compared (T able 2- 3), but not when results are averaged (Table 2- 4).

Table 2- 2: Component Concentrations Relative to total PM 2.5

Year Total PM 2.5 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 PM 2.5 in this table is based on speciation sampler mass. "Other" includes PM 2.5 that is not nitrate, sulf ate, organic carbon, elemental carbon, or ammonia.9 Table 2- 3: Knoxville Sp eciation Monitor 47-093-1020 Highest Daily Sampled Values (μg/m 3 )

Year First Max 2 nd Max 3 rd Max 4 th Max 5 th 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 Sp eciation Monitor 47-093-1020 Highest Average of the Daily Sampled Values (μg/m 3 )

Year First Max 2 nd Max 3 rd Max 4 th Max 5 th 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 PM 2.5 components appear to r oughly agree with mix of emission categories surroundi ng the monitoring sites?

The overall mix of PM 2.5 components does not match the mix of precursor emissions in the surrounding area, primarily due to the large NO X 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 Tabl e 2- 5, which indicates that there are significant NO X emissions within the region. However, NO X does not contribute significantly to PM 2.5 formation (see Section 3.0 for additional informati on), and as indicated above in Table 2- 2, nitrate does not const itute a significant fraction of monitored PM 2.5
. When speciation data is compared with emission inventory data for othe r pollutants, there is rough agreement between sulfate co ncentrations at the Speciated Trends Network (STN) monitor (29-33% of total PM 2.5 at the Mildred Drive monitor) and em issions of sulfur dioxide (about10 34% of regional precursor emissions). Similar results are observed for ammonia, although there is greater variation in the fraction of speciated PM 2.5 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 PM 2.5 (36-44% of total PM 2.5 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 Su mmary for Knoxville No nattainment Area

Regional Emissions in Tons/Year

PM 2.5 NO X SO 2 VOC NH 3 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 PM 2.5 in monitored or unmonitored areas?

The spatial distribution of PM 2.5 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 distributio n of measured PM 2.5 is reasonably uniform, with the numbers falling in the range of 14.1 to 15.6 μg/m 3 for the controlling monitors in each county where PM 2.5 monitoring is currently being c onducted. The annual design values are further augmented by the daily average PM 2.5 design values, which range from 30 to 33 μg/m 3 for the same area. The emissions data for the major contributing PM 2.5 pollutants and/or precursors are also depicted in the slides, with the color variations deno ting the relative emission density. Despite the variation in emissions density, the PM 2.5 levels appear to be reasonably uniform, with little evidence of significant gradie nts. Although one county in the area does not have a PM 2.5 monitor, it would be reasonable to conc lude that the county is similar in PM 2.5 ambient levels to the other adjacent counties.11 Figure 2- 1: Regional Em issions Distribution and PM 2.5 Gradients12 Figure 2- 1 (Continued)13 Figure 2- 1 (Continued)

6. Is there any indication of what precurso r might be limiting formation of secondary particulate matter?

The preceding comparison of monitoring and emi ssion inventory data (Question #4) suggests that sulfate is the limiting precursor for seconda ry particulate formation. Nitrogen oxides do not appear to be a significant PM 2.5 precursor and the organic carbon and ammonia fractions appear to have a significant biogenic component. Th e data suggest that reduction of anthropogenic SO 2 emissions would have the greatest impact on PM 2.5 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 PM 2.5 nonattainment area is loca ted in a geographic region of the State known as the Valley and Ridge region. Th e Valley and Ridge covers 7,703 sq uare miles and is situated between the Cumberland Plateau to the west and th e 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 n ear the Georgia State Line. Tw enty-seven counties of Tennessee are partially or completely lo cated within this region. The topography of the Valley and Ridge consists of long linear ridges and parallel lowland valley s that trend in a nor theast to southwest direction. The ridges usually have high eleva tions 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 PM 2.5 monitors identified with yellow stars. The shaded relief imagery shows that the ma jor 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-attainme nt region is shown in Figure 2- 4, with the local elevation for the Knox county ar ea ranging from about 800 to 1,900 feet.15 Figure 2- 4: Elevation of Knoxville PM 2.5 Sites

The topography has a pronounced effect upon the pr evailing wind direc tion. The mountains serve to modify the hot summer winds that are co mmon 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 freq uency of afternoon thunde rstorms. Relief from extremely high temperatures that such thunders torms 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 north east (Figure 2- 5). These winds are relatively light, averaging 6.9 mph for the year.

Figure 2- 5: Three-Year Wind Rose for Knoxville Region16 8. Have there been any recent ma jor changes in emissions of PM 2.5 or its precursors in or near the nonattainment area? What?

As discussed in Section 5.0, SO 2 emissions in Tennessee and su rrounding States decreased by about 12.7% in Tennessee and surrounding States between 2000 and 2006. This change is consistent with a gradual dec line in emissions since the em ission caps under the Acid Rain Program became effective.

NO X emissions from electric utilities declined by 38.1% during the same period, but this decline is believed to have made no significant impact on PM 2.5 concentrations. The decline in NO X emissions may be attributed to NO X reductions that occurred pr imarily during the summer ozone season in 2003 and subsequent years. As discussed in Section 3.0, ambient PM 2.5 concentrations in the Knoxville region are re latively insensitive to NO X emissions, and seasonal variations in PM 2.5 concentrations vary inversely w ith seasonal nitrate levels.

9. Are there discernible trends in design valu es or other air quality indicators which have accompanied a change in emissions?

Monitoring data for the Knoxville area indicates that ambient PM 2.5 concentrations declined significantly between 1999 and 2006 (Figure 2- 6). The more recently monitored concentrations (from about 2004 to 2006) do indicate so me variation in th e annual average PM 2.5 concentration, including some year-to-year increases. These changes (increases and decreases) tend to be well correlated with State and regional SO 2 emissions from electric ut ilities, suggesting a strong regional component to PM 2.5 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 SO 2 emissions data from the Acid Rain Program (Table 2- 6) strongly suggests a linear relationship between ambient PM 2.5 levels and local, St ate, and regional SO 2 emissions (Table 2- 7, Figure 2- 7, Figure 2- 8). Due to the complex mixture of precursor pollutants in ambient PM 2.5 , 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 SO 2 emissions between 1999 and 2006 resulted in a noticeable change in PM 2.5 concentrations at the ambient monitors.

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

3-Year Period 3-Year Avg. SO 2 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 2006ug/m3PM2.5 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: PM 2.5 Trends for Knoxville (2000-2006)18 Figure 2- 7: Scatter Plot of Ambient Monitored Data and Tennessee SO 2 Emissions

Figure 2- 8: Scatter Plot of Ambi ent Monitored Data and Regional SO 2 Emissions19 Table 2- 7: Linear Correlation Coefficients 6

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 calculate d for three-year averages of SO 2 emissions and three-year average ambient PM 2.5 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 sp atial pattern to the trends in design values?

See item 9. From about 2004 to 2006, annual PM 2.5 concentrations were relatively stable, compared to the more significant decreas es that were observed from 1999 to 2004.

11. What past modeling has been perf ormed 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 Rule 7 . EPA’s CMAQ model resu lts indicated that PM 2.5 concentrations would decrease as CAIR controls were implemented, but that PM 2.5 concentrations would still exceed the NAAQS in the absence of add itional 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 used 8 , the assumed mixture of EGU controls 9 , or other factors. Monitoring data for the Knoxville area suggests th at CAIR modeling underestimated the positive impact of Acid Rain program or other reduction s, since the Knoxville ar ea design values for 2004-2006 (see Table 1- 1) are already below thos e predicted for the 2010 CAIR scenario.

Table 2- 8: CAIR Modeling Results – Projected PM 2.5 Concentrations for Knox County

Projected Annual PM 2.5 Concentration (μg/m 3 ) 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 em issions inventory to estimate fu ture-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 Pla nning Model (IPM) results.20 12. Are there any distinctive meteorological measurements at the surface or aloft which appear to coincide with occasions with PM 2.5 concentrations in excess of 15.0 μg/ m 3 ?

Recent elevated PM 2.5 data was analyzed to compare mon itoring 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 PM 2.5 concentrations were 35 μg/m 3 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 larg est number of event da ys in the dataset. Several days in 2005 with elevated PM 2.5 were selected to evaluate the winds patterns present (Figure 2- 9). The wind roses developed for thes e selected dates with elevated levels of PM 2.5 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 PM 2.5 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 PM 2.5 Days21 13. Do periods with high measured particulate matter or components of particulate matter appear to track each other or any other measured pollutant?

Measured PM 2.5 concentrations follow the same general trends as ozone concentrations. Ambient levels of ozone and PM 2.5 tend to be highest in the su mmer months (Figure 2- 10), when the hot, stagnant conditions are conduciv e 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 PM 2.5 concentrations also tend to be high (20-40 μg/m 3 – Figure 2- 11).

Comparison of individual spec iated components at FRM Mon itor 47-093-1020 shows the same trend (Figure 2- 12). Ambient PM 2.5 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 PM 2.5 and Ozone In the Knoxville NAA

0 10 20 30 40 50 60

2 / 2 8 / 2 0

0 2

5 / 2 9 / 2 0

0 2

8 / 2 7 / 2 0

0 2

1 1 / 2 5 / 2

0 0 2

2 / 2 3 / 2 0

0 3

5 / 2 4 / 2 0

0 3

8 / 2 2 / 2 0

0 3

1 1 / 2 0 / 2

0 0 3

2 / 1 8 / 2 0

0 4

5 / 1 8 / 2 0

0 4

8 / 1 6 / 2 0

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8 / 1 1 / 2 0

0 5

1 1 / 9 / 2 0

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2 / 7 / 2 0 0

6

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6

8 / 6 / 2 0 0

6Max Daily PM2.5ug/m3

0 0.02 0.04 0.06 0.08 0.1 0.12Max Daily Ozone 8 Hour PPM PM 2.5 VALUE
8 Hour Ozone PPM

Figure 2- 10: General Trends of Ambient PM 2.5 and Ozone, Knoxville, Tennessee22 Comparisons of PM 2.5 and Ozone In the Knoxville NAA (Ozone Days >=0.080 PPM)

0 10 20 30 40 50 60

5 / 2 4 / 2 0

0 2

6 / 3 / 2 0 0 2

6 / 1 2 / 2 0

0 2

6 / 2 0 / 2 0

0 2

7 / 8 / 2 0 0 2

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8 / 1 0 / 2 0

0 2

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0 2

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0 2

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6 / 2 4 / 2 0

0 3

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1 / 2 0

0 4

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0 5

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1 / 2 0

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6

7 / 2 0 / 2 0

0 6

8 / 1 / 2 0 0

6Max Daily PM2.5ug/m3

0 0.02 0.04 0.06 0.08 0.1 0.12Max Daily Ozone 8 Hour PPM PM 2.5 VALUE
8 Hour Ozone PPM

Figure 2- 11: Comparison of Ambient PM 2.5 and Ozone, Knoxville, Tennessee High Ozone Days (>= 0.080 ppm)23Knoxville Region Speciated Components Comparison051015202530354045 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 3PM2.5 Mass Collocated FRM 470931020SULFATEKnoxville Region Speciated Components Comparison051015202530354045 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 3PM2.5 Mass Collocated FRM 470931020NITRATEKnoxville Region Speciated Components Comparison051015202530354045 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/m3PM2.5 Mass Collocated FRM 470931020AMMONIUMKnoxville Region Speciated Components Comparison051015202530354045 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/m3PM2.5 Mass Collocated FRM 470931020Organic Carbon Mass (k=1.4)Elemental CarbonFigure 2- 12: Comparison of PM2.5Speciated Components, FRM Monitor 47-093-102024Knoxville Region Speciated Components Comparison0510152025October 2002 2006

ug/m3PM2.5 Mass Collocated FRM 470931020AMMONIUMNITRATESULFATEKnoxville Region Speciated Components Comparison02468101214161820November 2002 2006

ug/m 3PM2.5 Mass Collocated FRM 470931020AMMONIUMNITRATESULFATEKnoxville Region Speciated Components Comparison0510152025December 2002 2006

ug/m 3PM2.5 Mass Collocated FRM 470931020AMMONIUMNITRATESULFATEKnoxville Region Speciated Components Comparison02468101214161820January 2002 2006

ug/m3PM2.5 Mass Collocated FRM 470931020AMMONIUMNITRATESULFATEKnoxville Region Speciated Components Comparison051015202530February 2002 2006

ug/m 3PM2.5 Mass Collocated FRM 470931020AMMONIUMNITRATESULFATEKnoxville Region Speciated Components Comparison02468101214161820March 2002 2006

ug/m 3PM2.5 Mass Collocated FRM 470931020AMMONIUMNITRATESULFATEFigure 2- 13: Comparison of PM2.5Speciated Components (Winter Months Only), FRM Monitor 47-093-102025 3.0 NO X INSIGNIFICANCE 10

As indicated in Section 1.0, the PM 2.5 Implementation Rule requires States to address NO X as a PM 2.5 attainment plan precursor and evaluate sources of NO X emissions in the State for control measures, unless the State and EPA provide an appr opriate technical demonstration for a specific area showing that NO X emissions from sources in the State do not significantly contribute to PM 2.5 concentrations in the nonattainment area 11 . As indicated in th e following paragraphs, Tennessee believes that NO X emissions do not signifi cantly contribute to PM 2.5 concentrations in the Knoxville nonattainment area.

3.1. Significance of Precursors Contributing to Fine Particulate Matter

The United States Environmental Protection Ag ency (EPA) revised the National Ambient Air Quality Standards (NAAQS) for particulate ma tter in 1997 establishing fine particulates (particulate matter w ith aerodynamic diameter ≤ 2.5 micrometers or PM 2.5 ) as a benchmark. The revised NAAQS for particulate matter set a daily standard of 65 μg/m 3 and an annual standard of 15.0 μg/m 3 . The daily PM 2.5 standard was more recently revised in 2006 by lowering it to 35 μg/m 3 based on a review of th e air quality criteria and the NAAQS, but the annual PM 2.5 standard was retained at 15.0 μg/m 3 . 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 attainme nt will be met as outlined in the Clean Air Act (CAA). These implementation plans must outlin e the measures that will be taken to curtail the concentrations of various pollutants that ar e assumed to have significant contributions to nonattainment for fine particulate ma tter, including su lfur dioxide (SO 2 ), nitrogen oxides (NO X ), and primary PM 2.5
. EPA, in 72 FR 20586, requires states to “evaluate a nd consider control strategies for sources of SO 2 , direct PM 2.5 , and NO X emissions in all nonattainment areas .” However, the rule does allow States to make technical demonstrat ions to reverse th e inclusion of NO X as precursor of PM 2.5 , or deem the precursor insignificant, based on geographical regions, emi ssions, etc. This eliminates the need to examine NO X control measures for purposes of reducing PM 2.5 concentrations.

The two remaining precursor species that contribute PM 2.5 , ammonia (NH 3 ) and volatile organic carbons (VOCs) have been deemed as insign ificant contributors to the total mass of PM 2.5 by the USEPA. With regards to NH 3 , 72 FR 20586 states NH 3 “is presumed not to be a PM 2.5 attainment plan precursor, meaning that the State is not required to address [NH 3 ] in its attainment plan or evaluate sources of [NH 3 ] emissions for reduction m easures.” Likewise, the

10 This section was adapted from NO X Insignificance Demonstration, Knoxville, TN PM 2.5 Nonattainment Area. Pat Brewer, January 2008.
11 The preamble to the implementation rule states: “Demonstra tions to reverse the presumptions for ammonia, VOC, or NO X are to be based on the weight of evidence of available informa tion, and any demonstration by the State must be approved by EPA. The State must dem onstrate that based on the sum of available technical and scientific information, it would be appropriate for a nona ttainment area to reverse the presumptive approach for a particular precu rsor. The demonstration should include informati on from multiple sources, including results of s peciation data analyses, air quality modeling studies, chemical tracer studies, em ission 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 “State s are not required to address VOC in PM 2.5 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 PM 2.5 concentrations in a gi ven nonattainment area.”

The State of Tennessee agrees with EPA’s presumptive exclusion of NH 3 and VOC with regards to the PM 2.5 implementation plan. Theref ore, emission controls for NH 3 and VOC are not considered as a part of Tennessee’s PM 2.5 attainment demonstration plan.

3.2. Determination of NO X Insignificance

NO X is assumed to be precursor for PM 2.5 unless the state can demonstrate that NO X is not a significant contributor to PM 2.5 attainment. The USEPA has provided suggested guidelines for producing the technical demonstrations necessary to determine the significance of a pollutant towards attaining the PM 2.5 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 NO X is insignificant to PM 2.5 attainment in the Knoxville, TN nonattainment area. Data are included that address each of the four categories of evidence that the EPA suggest s be included in the demonstration.

3.3. Elements of NO X Insignificance Demonstration

The NO X insignificance demonstration incl udes the following elements:

• Annual emissions inventories for 2002 and 20 09 are presented by so urce category for each county in the Knoxville nonattainment area and for the State total. NO X emissions in the Knoxville nonattainment area are proj ected to decrease by 58% between 2002 and 2009.

• An analysis of total PM 2.5 mass is provided for the Federal Reference Method (FRM) monitors in the Knoxville, TN PM 2.5 nonattainment areas. These data are presented as both quarterly and annual averages and in dicate that the Knoxville area is already demonstrating PM 2.5 values that attain the annual standard of 15 μg/m 3

.

• An analysis is provided of speciated data available from the Speciated Trends Network (STN) monitor in Knoxv ille, TN. These data demonstrate that NO 3 is an extremely small component of total PM 2.5
.

• Results of the SANDWICH method (measured Su lfate, Adjusted Nitrate, Derived Water, Inferred Carbonaceous mass Hybrid Material Balance Approach) to speciate the PM 2.5 mass for the FRM monitors in the Knoxville nonattainment area demonstrate that NO 327 and associated ammonium and particle bound wa ter account for less th an 2% of the total PM 2.5
.

• The Speciated Modeled Attainment Test (SMAT) method is applied to 2009 modeling results to project the change in speciated PM 2.5 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 PM 2.5 standard in 2009 and demonstrate that NO3 will be an insignificant co ntribution to PM 2.5 in the Knoxville area in 2009.

• The results from 2009 sensitivity modeling runs are presented to further demonstrate the insignificance of NO X emissions to PM 2.5 attainment in the Knoxville, TN nonattainment

area.

3.4. NO X Emissions Source Categories

Table 3- 1, Table 3- 2, a nd Table 3- 3 outline NO X emissions by source category for each of the counties in the Knoxville PM 2.5 nonattainment area and for Tenne ssee 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 NO X emissions in the Knoxville nonattainment area. Coal-fired power plants in these tw o counties installed NO X controls under the NO X SIP call and as demonstrated in Table 3- 2, by 2009 NO X 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, NO X emissions from onroad mobile in the Knoxville nonattainme nt area are projected to decrease by 39% (11,500 tons) due to EPA rules for cl eaner fuels and cleaner engines. NO X emissions from nonroad engines are projected to decrease by 11% (900 tons) between 2002 and 2009 while NO X emissions from area sources are projected to in crease slightly (50 tons). The cumulative NO X emissions reductions for the Knoxville nona ttainment area between 2002 and 2009 is 58% (50,000 tons). These reductions su pport the demons tration that NO X emissions will continue to be an insignificant contribution to the PM 2.5 nonattainment issues in the Knoxville nonattainment

area.28 Table 3- 1: 2002 Actual NO X Emissions for Counties in Knoxville, TN PM 2.5 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 includ ing point source emissions for Kingston Steam plant and onroad, nonroad, and area emissions for Kingston census track only.

Table 3- 2: 2009 NO X Emissions for Counties in Knoxville, TN PM 2.5 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 includ ing point source emissions for Kingston Steam plant and onroad, nonroad, and area emissions for Kingston census track only.

Tennessee Statewide total NO X emissions demonstrate similar decreasing trends between 2002 and 2009 (Table 3- 3). Statewide NO X 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 NO X controls between 2002 and 2009. Point source NO X emissions are projected to be reduced by 43% st atewide. Changes for onroad, nonroad, and area source NO X emissions between 2002 and 2009 are sim ilar in the Knoxville nonattainment area and statewide.

Table 3- 3: Tennessee NO X Emissions in 2002 and 2009

TN NO X 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 18,485 383,33629 3.5. Federal Reference Method Observations

The Federal Reference Method (FRM) PM 2.5 monitors provide a record of PM 2.5 concentrations in the Knoxville, TN area since 2000. Figure 3- 1 shows annual average PM 2.5 at the three FRM monitors located in Knox County from 2000 through 2006.

Annual average PM 2.5 decreased from 2000 to 2004 and then ha s been level or in creased slightly. In 2006 PM 2.5 was at or slightly above the annual standard of 15 μg/m 3 . Trends for the FRM monitors in Blount and Roane Counties show si milar downward trends. Both these monitors currently attain the annual PM 2.5 standard.



### FRM Annual Average Fine Particle Mass - Knoxville, TN

0 5 10 15 20 25

1999 2000 2001 2002 2003 2004 2005 2006Fine Particle Massμg/m3

47-093-0028
47-093-1017
47-093-1020

Figure 3- 1: Annual Average PM 2.5 from 2000-2006 at Three Federal Reference Method Monitors in Knox County, TN

Quarterly and annual average PM 2.5 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. PM 2.5 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 monitori ng 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 deploym ent and calibration. Se veral forest fires in TN, NC, and KY in November 2000 likely cont ributed to the relative high average PM 2.5 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 PM 2.5 at all sites meets or is slightly above the annual standard of 15 μg/m 3

.30 Two additional FRM monitors si ted in the Knoxville, TN PM 2.5 nonattainment area, Knox County monitor 47-093-1013 and Loudon County m onitor 47-105-0108, have incomplete data for the 2000-2004 baseline pe riod that do not meet EPA criteria for 12 comple te quarters of data. These monitors are not included in this NO X 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 PM 2.5 in 2000 through 2006 from Federal Reference Method Monitors in Knox County, TN PM 2.5 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 2006PM2.5(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 2006PM2.5(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 2006PM2.5(μg/m3)

Quarterly Averages Annual Average32 Figure 3- 3: Quarterly and Annual Average PM 2.5 in 2000 through 2006 from Federal Reference Method Monitors for Counties in the Knoxville, TN PM 2.5 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 2006PM2.5(μg/m3)

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 2006PM2.5(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 2006PM2.5(μg/m3)

Quarterly Averages Annual Average33 3.6. Speciated Trends Network Observations

There is only one Speciated Trend Network (S TN) 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 fo r the STN monitor are illustrated in Figure 3- 4.

Knoxville, TN (47- 093-1020) Annual Average and Quarterly Speciated PM 2.5 Mass

0 5 10 15 20 2512341234123412341234
2002 2003 2004 2005 2006STN Mass (μg/m3) Soil
LAC
POM
NO3

NH4
SO4 Ann. Avg.

Figure 3- 4: Quarterly and Annual Average Speciated PM 2.5 Mass from Speciated Trend Network (STN) Monitor for 2002 through 2006 at Spring Hill Elementary School in Knoxville, TN (47-093-1020).

PM 2.5 observations are separated into several components: sulfate (SO 4 ), nitrate (NO 3 ), ammonium (NH 4 ), particulate organic matter (POM), elemental carbon (EC), and crustal materials. Data recovery for the STN mon itor is spotty in 2002 th rough 2004 but improves by 2005 and 2006. Sulfate (SO 4 ) and particulate organic matter (POM) are the dominant contributors to PM 2.5 mass in the Knoxville area. Sulfur dioxide (SO 2 ) emissions, primarily from utility and industrial po int sources, are the primary contributor to SO 4 . SO 4 mass is highest in the summer months, in part due to higher SO 2 emissions in the summer m onths and in part due to more active secondary photochemical formati on during the higher temp eratures, relative humidity, and oxidant loading of the summer months. Particulat e organic matter concentrations are similar across all quarters although carbon analytical studies indicate greater contributions from primary carbon (combustion of fossil fuel s, biomass burning, vegetative detritus, and cooking) in the winter months and greater contributions from secondary organic aerosol (from biogenic and anthropogenic emission s) during the summer months.

Ammonium (NH 4 ) and nitrate (NO 3 ) have comparable contributions in the winter quarters while NO 3 is very small in the spring and summer (s econd and third quarters). Higher amounts of NO 3 are present in the cooler months, with very low concentrations in the summer months. Ammonium nitrate (NH 4 NO 3 ) formation is a temperature-limited process with particle formation favored at lower temperatures. At higher temperat ures nitrogen oxides remain in gaseous form as nitric acid. Through the year, NO 3 makes up only a small fraction of total PM 2.5 mass, insignificant to the total PM 2.5 mass and attainment issues. Th e EC and crustal components of PM 2.5 are generally very small and are also insignificant portions of the total PM 2.5 mass.34 Note that quarterly and annual average PM 2.5 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 PM 2.5 for Federal Reference Method Monitors

To make observations of PM 2.5 between the different monito ring 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. Th e “Sulfate, Adjusted Nitrate, Derived Water, Inferred Carbonaceous mass Hybrid Material Ba lance Approach” or SANDWICH is a method which resolves differences between STN and FRM total PM 2.5 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 met hod used by ASIP is provided in Attachment G, and in the EPA documentation for the Clean Air In terstate Rule. EPA de veloped procedures to apply the SANDWICH method to calculate speci ated 2002 baseline desi gn values for the FRM mass measurements and provided an initial spread sheet with the SANDWICH calculations used for the Clean Air Interstate Rule to the No rth Carolina Division of Air Quality.

Quarterly and annual average 2002 baseline desi gn values (DVB) for the Knoxville, TN, Spring Hill Elementary School FRM monitor (47-093-1020), based on PM 2.5 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 mon itor 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 in terpolation of speciated data.

Table 3- 4 provides the quarterly and annual average speciated PM 2.5 2002 baseline design values (DVB) for six FRM monitors in the Kn oxville, TN nonattainme nt area. The 2002 DVB for the three monitors in Knox Count y exceed the annua l standard for PM 2.5 ; the 2002 DVB for the two monitors in neighbor ing Blount and Roane Count y attain the standard.

Consistent with the STN data , Organic Carbon (OC) and SO 4 make up the most significant portion of the speciated PM 2.5 mass at all sites. The de rived concentrations for NH 4 , elemental carbon (EC), crustal materials, and particle bound water (PBW) are greater than the derived concentration for NO 3 . The contribution of NO 3 to total PM 2.5 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 AvePM2.5 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 PM 2.5 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 PM 2.5 Nonattainment Area

AIRS ID County Quarter FRM Mass Blank Mass Bl an k 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 Knox 47-093-0028 47-009-0011 Blount

47-145-0004 Roane36 The annual average NO 3 mass for the 2002 base design value (DVB) varies from 0.11 to 0.20 μg/m 3 across the five FRM monitors in the Knoxville, TN PM 2.5 nonattainment area. Including ammonium (NH 4 ) and particle bound water (PBW) associated with nitrate, the total contribution of NH 4 NO 3 to PM 2.5 ranges from 0.16 to 0.32 μg/m 3 . NO 3 plus associated NH 4 and particle bound water contributes 0.9 to 2.2% of total PM 2.5 mass for the 2002 DVB for the five FRM monitors in the Knoxville, TN PM 2.5 nonattainment area.

3.8. Speciated Modeled Attainment Test

Another technical demonstration th at is useful in determining NO X significance to PM 2.5 attainment is the Speciated Modeled Attainment Te st (SMAT). This test a llows states to examine whether modeled current or proposed controls will bring nonattainment ar eas into attainment while also allowing the examination of the reductions in the individual species of PM 2.5 . 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 m odeling results for 2002 baseline de sign values (DVB) and 2009 future design values (DVF) for the FRM monitors in the Knoxville nonatta inment 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 mode ling domain are listed by species in Table 3- 5.37 0 2 4 6 8 10 12 14 16 18Blount-0011Knox-0028Knox-1013Knox-1017Knox-1020Roane-0004PM2.5 mass -μg/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 18Blount-0011Knox-0028Knox-1013Knox-1017Knox-1020Roane-0004PM2.5 mass -μg/m3

PBW NH4 Crustal EC OC NO3 SO4

0 2 4 6 8 10 12 14 16 18Blount-0011Knox-0028Knox-1013Knox-1017Knox-1020Roane-0004PM2.5 mass -μg/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 PM 2.5 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 Kno x

47-145-0004 Roane 47-093-1017 Kno x 47-093-1013 Kno x 47-009-0011 Blount

47-093-0028 Kno x

All monitors in the Knoxville nonattainmen t area are projected to meet the annual PM 2.5 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/m 3 for 2009 DVF. The major changes in PM 2.5 are due to reductions in SO 4 and associated NH 4 and PBW.

The annual average concentration of NO 3 for each monitor does not change between 2002 and38 2009. Spatially NO 3 varies between 0.11 and 0.22 μg/m 3 in 2009, the same concentrations as in 2002. The contribution of NO 3 plus associated NH 4 and PBW also remains unchanged at each monitor between 2002 and 2009. Spatially NO 3 with associated NH 4 and PBW ranges from 0.17 to 0.34 μg/m 3 . These values are an insignificant contribution to total PM 2.5 mass. The contribution of NO 3 with associated NH 4 and PBW is 1.2-2.7% of total PM 2.5 in 2009; still an insignificant contribution to total PM 2.5 in the Knoxville nonattainment area.

3.9. NO X Sensitivity Modeling

A final technical demonstration for insignificance is to assess the effects of reducing 2009 NO X emissions on PM 2.5 mass. CMAQ was run a ssuming 100% reduction in NO X emissions from all source categories in Tennessee a nd again assuming 70% reduction in NO X emissions from all sources in Tennessee. These runs were perf ormed 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 spac ing. 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 illustra ted 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 NO X sensitivity runs at 36 km are representative of results if 12-km grid resolution had been used.

While a statewide zeroing out of NO X emissions in Tennessee is impossible to accomplish in reality, it is used to represent th e maximum conceptual effect of NO X emissions on total PM 2.5 mass and to demonstrate that all the NO X emissions in the state do not significantly impact total PM 2.5 . One major caveat is NO X reductions of this magnitude crea te serious inequities in model chemistry. Gaseous species such as ozone (O 3 ) require NO X for oxidation processes. Large reductions of NO X seriously deteriorate O 3 production, especially during the 2 nd and 3 rd quarters. Such large decreases in O 3 reduce associated atmospheric oxidan ts, which in turn decreases OC and SO 4 formation (Figure 3- 7). The conversion of VOCs to secondary organic aerosols (e.g., OC) and the conversion of SO 2 to SO 4 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 NO X emissions was also modeled in addition to the 100% NO X reduction sensitivity run. The 70% NO X reduction simulates the impacts of tremendous NO X removal while still allowing for some summertime O 3 and oxidation processes. Table 3-6 and Table 3-7 show the results for annual average PM 2.5 mass in the Knoxville nonattainment area comparing the 2009 Base G2 si mulation to the 100% (Table 3- 6) and 70% (Table 3-7) NO X reduction sensitivities.

Table 3- 6: Annual Average PM 2.5 for ASIP 2009 Base G2 Future Design Values and for Tennessee Statewide 100% NO X Emissions Reduction for FRM Monitors in Knoxville, TN PM 2.5 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 TN 100% NOx County Difference40 Table 3- 7: Annual Average PM 2.5 for ASIP Base G2 2009 Future Design Values and for Tennessee Statewide 70% NO X Emissions Reduction for FRM monitors in Knoxville, TN PM 2.5 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 TN 70% NOx Difference County

By zeroing out all the Tennessee statewide NO X emissions, 2009 future de sign values (DVF) are projected by the CMAQ model to be reduced by 0.61 to 0.85 μg/m 3 . In comparison, a 70% reduction in NO X emissions is projected to reduce 2009 DVF by 0.24 to 0.30 μg/m 3

. Another way that these NO X sensitivities results can be analyzed is to evaluate the quarterly and annual responses for indi vidual components of PM 2.5 . Table 3- 8 and Table 3- 9 provide the quarterly and annual differences for individual components of PM 2.5 between the 2009 DVF and the 100% (Table 3- 8) and 70% (Table 3- 9) NO X reduction sensitivities for the FRM monitors in the Knoxville, TN PM 2.5 nonattainment area. Figures 3-6-1 and 3.6-2 illustrate the annual responses to 100% (Figure 3- 8) and 70% (Figure 3- 9) NO X reductions for individual PM 2.5 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 Quar terly and Annual Speciated PM 2.5 (μg/m 3 ) Between 2009 Future Design Values and Tennessee Statewide 100% NO X Emissions Reductions for FRM Monitors in Knoxville, TN PM 2.5 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

Roane 47-145-0004 Knox

Knox

Knox 47-093-0028

47-093-1017

47-093-1020

NO 3 concentrations are very low in all quarters with highest valu es in the fourth quarter (0.4 μg/m 3 or less). The 100% NO X reduction run projects ve ry small reductions in NO 3 concentrations in the first and fourth quarters (0.1 μg/m 3 or less) and no change in the second and third quarters. SO 4 is projected to decrease slightly (less than 0.2 μg/m 3 ) in the second and third quarter with corresponding minor changes in NH 4 and PBW. There are essentially no changes in SO 4 in the first and fourth quarters, suggesting that the modeled impact of NO 3 reductions is reduced phot ochemical production of SO 4 from SO 2 . Organic carbon is projected to decrease in all quarters, with small reductions (0.3 μg/m 3 or less) during th e winter quarters and larger reductions (up to 1.2 μg/m 3 ) 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 NO X emissions and thus reduced photochemi cal formation of secondary organic aerosols (Figure 3- 8).

The results of the 70% NO X reduction run (Table 3- 9) provid e notably smaller decreases in OC (0.1 μg/m 3 or less in the winter qu arters and less than 0.6 μg/m 3 in the third quarter) than the 100% reduction run. SO 4 decreases for the 70% NO X reduction run are 0.1 μg/m 3 or less with largest responses projected for the third quarter a nd essentially no change for the winter quarters. These results suggest that NO X chemistry is highly nonlin ear and that reducing all NO X emissions produces unrealistically large changes in atmospheric photochemistry that would not42 occur under maximum feasible NO X reductions.

The annual average responses to 70% NO X reductions are a 0.2 μg/m 3 decrease in OC and a 0.05 μg/m 3 decrease in SO 4 . These reductions are still greater than could feasibly be implemented, but the responses are clearly insign ificant compared to the total PM 2.5 . We conclude that NO X is an insignificant contributor to PM 2.5 in the Knoxville nonattainment area.

Table 3- 9: Changes in Quar terly and Annual Speciated PM 2.5 (μg/m 3 ) Between 2009 Future Design Values and Tennessee Statewide 70% NO X Emissions Reductions for FRM Monitors in Knoxville, TN PM 2.5 Nonattainment Area 70% reduction in Tennessee statewide NOx emissions (change in PM2.5 - ξ g/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 PM 2.5 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/m 3 while the scale for Figure 3- 9 is 0.05 to – 0.35 μg/m 3

.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 47-145-0004Delta (μg/m^3) PBW
NH4 Crustal EC OC NO3 SO4

Figure 3- 8: Annual Average Speciated Response to Tennessee Statewide 100% NO X

Reduction in 2009 for FRM Monitors in Knoxville, TN PM 2.5 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 47-145-0004Delta (μg/m^3) PBW
NH4 Crustal EC OC NO3 SO4

Figure 3- 9: Annual Average Speciated Response to Tennessee Statewide 70% NO X Reduction in 2009 for FRM Monitors in Knoxville, TN PM 2.5 Nonattainment Area44 3.10. Summary

Tennessee has demonstrated that NO X emissions are an insignifican t precursor for total annual PM 2.5 using evidence from inventory, monitoring a nd modeling data. Emissions inventories demonstrate that statewide NO X emissions will be reduced 33% between 2002 and 2009. Within the Knoxville nonattainment area, NO X 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 NO 3 at the FRM monitors within the Knoxville nonattainment area range from 0.1 to 0.2 μg/m 3 in both 2002 and 2009. The highest concentrations of particulate NO 3 are observed in winter m onths, when formation of NO 3 more readily occurs. Particulate NO 3 is barely measurable during the other portions of the year. Including ammonium (NH 4 ) and particle bound water (PBW) a ttributable to nitrate, total contributions from NH 4 NO 3 in both 2002 and 2009 range from 0.15 to 0.32

 μg/m 3 . These contributions are 0.9 to 2.2% of the total PM 2.5 in 2002 and 1.2 to 2.7% of the total PM 2.5 in 2009.

Model attainment demonstrations based on cu rrent and future emission controls clearly demonstrate that all the FRM mon itors in the Knoxville, TN nonatta inment area will be attaining by 2009. Reductions in SO 2 emissions are responsible for the reduced PM 2.5 concentrations. Further reductions in PM 2.5 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 NO X is insignificant to total annual PM 2.5 mass. Total removal of NO X emissions resulted in decreases in secondary sulfate a nd secondary organic carbon during the photochemically activ e third quarter. We believe these modeled reductions to be unrealistic due to unrealistic changes in atmospheric chemistry. Substantial (70%) NO X reductions resulted in re latively minor (0.3 μg/m 3 or less) changes in total PM 2.5 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 NO X , as a precursor to PM 2.5 concentrations, is insignificant.

3.11. Addendum to Section 3.0

EPA has indicated that the Agency con tinues to have concerns regarding NO X insignificance demonstrations, and that the information presente d within this section may not be sufficient to overturn the presumption of NO X significance as a PM 2.5 precursor pollutant. Tennessee will incorporate the measures indicated in Attachment Q (NO X Addendum) as an enforceable part of this SIP. If Tennessee obtains sufficient additi onal information to overturn the presumption of NO X 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 NO X provisions.45 4.0 EMISSION INVENTORIES

The emission inventory is a comprehensive quantif ication 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 de veloped from the base. EPA recommended 2002 as the baseline year in a letter dated November 18, 2002 12 , since a National Emission Inventory and monitored PM 2.5 values were both available for this year. A regional emissions invent ory was developed by the ASIP work group, refined over several ite rations as stakeholde rs provided improved emissions estimates 13,14 , 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 em ission inventory consisted of thre e 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 NH 3 emission estimates for livestock and fertilizers and paved road PM emissions.

Development of a typical year fire inventory provided the capabil ity of using a comparable data set for both the base year and future years. Since fire emissions are not easily grown or projected, VISTAS determined th at a typical year fire invent ory was needed to effectively represent fires in base- and future-year inventor ies. Development of the “typical” year fire inventory covered wildfire, prescribed burning, agri cultural fires and land clearing fires. Typical year fire emissions were developed from actual fire acreage data and em issions were calculated for each State in the ASIP region.

The second component of the area source invent ory was the incorporation of CERR data submitted by States to EPA. The CERR data wo rk involved: 1) obtaining data from EPA; 2) evaluating reported pollutants and emissions to avoid double-c ounting; 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 fertilizer s 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 Invent ory SIP Planning: 8-hr ozone, PM 2.5 , and Regional Haze Programs,” signed by Lydia N. Wegman
13 A detailed discussion of inventory deve lopment is provided in the “Documentati on of the Base G 2002 Base Year, 2009 and 2018 Emission Inventories for VISTAS” (July 2, 2007). A copy of th is document is provided in Attachment A.
14 Concurrently with the prehearing draft ve rsion of this SIP, the ASIP work group released the air quality modeling results ba sed upon the ASIP States’ Best and Final emission i nventory, which contains minor updates to the Ba se 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. Sectio n 8.0 of the final SIP presents the attainment demonstration results for both Base G2 and Base G4 emission inventorie s, and the Best and Final cha nges to the Base G2 emission inventory are de tailed in Attachment N.46 livestock and fertilizer emissions. For paved road PM estimates, ASIP used the most recent EPA estimates developed in the Na tional Emission Inventory (NEI) 15

.
4.1b. Mobile Sources

The MOBILE6 module of the Sparse Matrix Op erator Kernel Emissions (SMOKE) model was used to develop the on-road mobile source emissions estimates for CO, NO X , NH 3 , SO 2 , PM, and VOC emissions. The MOBILE6 parameters, vehicle fleet descriptions, and VMT estimates were combined with gridded, episode-specific temperatur e data to calculate th e gridded, temporalized emission estimates. The emission factors model included the fo llowing 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 emi ssions into separate source categories;

• VMT, fleet turnover, and changes in fuel composition and Reid vapor pressure.

The primary input to MOBILE6 was the MOBILE sh ell 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 allowe d for the representati on of day-of-the-week variability in the on-road motor vehicles the meteorological variabilit y in each month. The modeled weeks were selected from mid-mont h, avoiding inclusion of major holidays.

Emissions from nonroad mobile sources were es timated by developing emissions for sources included in the NONROAD model were developed a nd by estimation of emissions from sources not included in the NONROAD mode l. An initial 2002 base y ear emissions inventory for nonroad engines and equipment covered by th e 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 a nd to accurately reflect gasoline sulfur contents for 2002.

4.1c. Non-EGU Point Sources

The starting point for the 2002 Base G2 emi ssion inventory was EPA’ s 2002 National Emission Inventory (NEI). The 1999 data was supplemente d 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 NE I. The 2002 Base G2 emission inventory was released in August 2006 and inco rporated updates and correcti ons to the 2002 NEI inventory. Changes for Tennessee included the correction of la titude and longitude va lues; identif ication 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 em issions 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. Th e 2002 “typical” baseline emi ssion inventory for EGUs was developed using CAMD data to develop norma lization factors for th e 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 th e actual 2002 heat i nput 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 year s from 2000-2004, then the average heat input was calculated for the years in which the unit did ope rate. Actual emissions for 2002 were multiplied by the normalization factor 16 to determine the typical emissions for 2002, as follows:

Typical Emissions = (2002 actual emissions)(Normalization Factor)

For the entire ASIP region, actual 2002 SO 2 emissions were about 0.5 percent higher than the typical year emissions. The differe nces on a State-by-State basis ra nged from actual emissions 6.6% lower in Florida to 10.9% higher in Mississippi. Tennessee’s 2002 actual SO 2 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 star ting point for projections. For non-agricultural sources, the ASIP contractor worked with Stat es 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 cal culate 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 fact ors 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 adjustment s to allow for special circumst ances. For example, total emissi ons were zero for units that did not operate in 2002. If the unit had been pe rmanently retired prior to 2002, then the typical year inventor y 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 hea t 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 invent ory data and obtained State-sp ecific 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 AS IP States for review and comment.

The 2009 emissions inventory for fi res was updated to account fo r increased prescribed fire burning by Federal agencies in future years. AS IP developed an updated Ba se G2 fire inventory for 2009 to capture the pr ojected 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 programs 17 . 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 contro l data, supplemented with State/Local agency input and updated fuel use forecast data from th e U.S. Department of Energy. Post-2002 facility shutdowns were also note d in the 2009 inventory.

For both sectors, 2009 and 2018 in ventories were generated us ing 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 invent ory that included all “on-the-books” control programs and 2) an “on-the-way” inventory that includ ed 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 eval uation years, the 2009 inventory was developed, to the maximum extent practical, using methodol ogies identical to those employed in developing the 2002 on-road portion of the re vised 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 fo recasts of least-cost capacity expansion, electricity dispatc h, and emission control strategies for meeting energy dema nd and environmental, transmis sion, dispatch, and reliability constraints. IPM was u sed to evaluate the cost and emissions impacts of SO 2 and NO X reductions in the CAIR rulemaking.
IPM runs were used to predict future electric utility emissions for VISTAS regional haze work and ASIP PM 2.5 modeling. However, ASIP States reviewed IPM-predicted control strategies a nd made changes as necessary to ensure accu racy. These changes are described in mor e detail in Attachment A49 1. All estimates started from the final VMT es timates used for the 2002 revised base year inventory.

2. Initial 2009 VMT estimates were based on linea r 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 di esel) rulemaking.

In general, Tennessee estimates were based on th e HDD rule growth rate described in step 2. Independent VMT estimates for 2009 for the Knoxville PM 2.5 Nonattainment Area were used in place of the HDD rule-derived estimates. Th e Knoxville Area VMT proj ections are shown in Table 4- 1 below:

Table 4- 1: Total 2009 Annual Vehicl e Miles Traveled in the Knoxville PM 2.5 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 develope d 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 mode l to be reflective of the projection year.

2. Revise the fuel sulfur content for ga soline and diesel powered equipment.

3. Implement a limited number of local contro l program changes (most national control program changes are handled internally w ithin 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 c ontent 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 Sulfu r Input Used in NONROAD

Diesel Sulfur (ppm) 2002 2009 Land-based 2,500 348 Marine-based 2,500 40850 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 PM 2.5 emissions inventories for the 2002 baseline year are summarized in Table 4- 3 and Table 4-4.

Table 4- 3: 2002 SO 2 Emissions

County 2002 SO 2 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 PM 2.5 Emissions

County PM 2.5 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 SO 2 emission inventory for 2002 i ndicates that point sources were responsible for the overwhelm ing majority (98%) of actual SO 2 emissions in 2002, and point sources with greater than 100 tons/year of SO 2 emissions accounted for virtually all (99.8%) of point source SO 2 emissions in the inventory. About 89% of point source SO 2 in the nonattainment area (119,759 actual tons, Table 4- 5) was emitted from TVA’s Bull Run and51 Kingston Fossil Plants in Ande rson and Roane Counties.

Table 4- 5: Point Sources in the Knoxvill e Nonattainment Area with > 100 tons/year SO 2 Emissions, Sorted by Rank (2002 Actual Emissions)

County Facility Description SO 2 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 SO 2 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 PM 2.5 , point sources accounted for about 73% (actual emissions basis) of the nonattainment area’s emissions in 2002, and sour ces with greater than 100 tons/year of direct PM 2.5 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 PM 2.5 , emitting 64.2% of total point source emissions. While point sources still make up the largest fraction of directly emitted PM 2.5 in the nonattainment area, direct PM 2.5 emissions from area sources are more significant than was observed with SO 2
. Table 4- 6: Point Sources with > 100 tons/year PM 2.5 Emissions Sorted by Rank (2002 Ac tual Emissions Basis)

County Facility Description PM 2.5 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 PM 2.5 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/Reverber atory 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 PM 2.5 emissions inventories for 2009 are summarized in Table 4-7 and Table 4- 8. The 2009 emissions inve ntories 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 SO 2 and PM 2.5 emissions estimates presented in Table 4-7 an d Table 4-8 represent the level of emissions modeled in the annual PM 2.5 control strategy for the K noxville nonattainment area to demonstrate that the area will attain the annual PM 2.5 NAAQS in 2009.

Table 4- 7: 2009 SO 2 Emissions

County SO 2 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 emis sions” inventory for EGUs. See Section 5.0 of this documen t 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 PM 2.5 Emissions

County PM 2.5 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 emis sions” inventory for EGUs. See Section 5.0 of this documen t 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 sulf ur dioxide emissions between 2002 and 2009. Most of the projec ted 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 th is rule). Significant reductions (as a percentage of 2002 emissions) are also achieved from the onroad and nonroad mobile source sectors. These re ductions offset a slight growth in emissions from area sources.

Direct emissions of PM 2.5 (Table 4- 11 and Table 4- 12) ar e 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.55Table 4- 9: 2002-2009 SO2Emission ReductionsTons per year and % Change from 2002 Baseline(Actual Emissions Basis for2002 Point Source Inventory)AreaNonroadOnroadPointTotalCountyTonsChange*from 2002TonsChange*from 2002TonsChange*from 2002TonsChange*from 2002TonsChange*from 2002Anderson 10 4% -57 -83% -98 -88%-33,609 -75% -33,754 -75%Blount 5 9% -61 -48% -104 -87% 493 12% 333 7%Knox 7 17% -314 -74% -610 -89% 33 3% -884 -36%Loudon 1 8% -58 -52% -106 -88% -134 -3% -297 -7%Roane** 0.1 3% -1 -45% -10 -89%-6,451 -8% -6,462 -8%Totals 246%-491-67%-927-89%-39,669 -30% -41,063 -31%* Negative numbers indicate emissions reduction,positive numbers indicate emissions growth.** Nonattainment portion onlyTable 4- 10: 2002-2009 SO2Emission ReductionsTons per year and % Change from 2002 Baseline(Typical Emissions Basis for 2002 Point Source Inventory)AreaNonroadOnroadPointTotalCountyTons/yearChange*from 2002Tons/yearChange*from 2002Tons/yearChange*from2002Tons/yearChange*from 2002Tons/yearChange*from2002Anderson 10 4% -57 -83% -98 -88%-28,150 -72% -28,294 -71%Blount 5 9% -61 -48% -104 -87% 493 12% 333 7%Knox 7 17% -314 -74% -610 -89% 33 3% -884 -36%Loudon 1 8% -58 -52% -106 -88% -134 -3% -297 -7%Roane** 0.1 3% -1 -45% -10 -89%-4,936 -6% -4,946 -7%Totals 24 6% -491 -67% -927 -89% -32,694 -26% -34,089 -27%* Negative numbers indicate emissions reduction,positive numbers indicate emissions growth.** Nonattainment portion only56Table 4- 11: 2002-2009 PM2.5Emission ReductionsTons per year and % Change from 2002 Baseline(Actual Emissions Basis for2002 Point Source Inventory)AreaNonroadOnroadPointTotalCountyTons/yearChange*from 2002Tons/yearChange*from 2002Tons/yearChange*from 2002Tons/yearChange*from 2002Tons/yearChange*from 2002Anderson 33 7% -8 -14% -13 -29%302 15% 314 12%Blount 27 4% -4 -3% -9 -22% -227 -13% -212 -8%Knox 50 11% -57 -18% -114 -40% -43 -9% -163 -11%Loudon 20 6% -10 -16% -21 -35% -34 -8% -45 -5%Roane** 0.2 4% -0.2 -19% -1 -42%174 5% 173 5%Totals 131 7% -78 -14% -158 -36% 172 2% 66 1%* Negative numbers indicate emissions reduction,positive numbers indicate emissions growth.** Nonattainment portion onlyTable 4- 12: 2002-2009 PM2.5Emission ReductionsTons per year and % Change from 2002 Baseline(Typical Emissions Basis for 2002 Point Source Inventory)AreaNonroadOnroadPointTotalCountyTons/yearChange*from 2002Tons/yearChange*from 2002Tons/yearChange*from 2002Tons/yearChange*from 2002Tons/yearChange*from 2002Anderson 33 7% -8 -14% -13 -29%544 30% 556 23%Blount 27 4% -4 -3% -9 -22% -227 -13% -212 -8%Knox 50 11% -57 -18% -114 -40% -43 -9% -163 -11%Loudon 20 6% -10 -16% -21 -35% -34 -8% -45 -5%Roane** 0.2 4% -0.2 -19% -1 -42%235 7% 234 7%Totals 131 7% -78 -14% -158 -36% 475 6% 369 4%* Negative numbers indicate emissions reduction, positive numbers indicate emissions growth.** Nonattainment portion only57 4.5. Statewide Emission Inventories for 2002 and 2009

Statewide SO 2 emission inventories for Te nnessee are summarized in Table 4- 13. This table projects that Statewide SO 2 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 la rgest 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 SO 2 Emission Inventory for Tennessee

Year SO 2 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 PM 2.5 emission inventories for Tennessee are summ arized in Table 4- 14. Overall, the emission inventory projects no si gnificant reductions in PM 2.5 emissions from EGUs and other point sources, and Statewide PM 2.5 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 emi ssions are projected to grow by 3.6% between 2002 and 2009.

Table 4- 14: Statewide PM 2.5 Emission Inventory for Tennessee

Year PM 2.5 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 basis58 5.0 CONTROL MEASURES

The Fine Particle Implementation Rule states that virtually all nonattainme nt problems appear to result from a combination of local emissions a nd transported emissions from upwind areas. The Clean Air Act requires EPA to deve lop national rules for sources that significa ntly contribute to local air quality problems, and the Act also provides for States to address emissions sources on an area-specific basis through such requirement s as Reasonably Availa ble Control Technology (RACT), Reasonably Available Control Measures (RACM), and Reasonable Further Progress (RFP). This section discusses th e control measures that were used in the modeled attainment
test.

5. 1. Point Sources - Clean Air Interstate Rule 18

In a rulemaking action published in the Fe deral Register on May 12, 2005, EPA found that certain States must reduce emissions of SO 2 and/or NO X because those emissions contributed significantly to downwind areas in other St ates that are not meeting the annual PM 2.5 NAAQS or the 8-hour ozone NAAQS. The resulting Clean Air In terstate Rule (CAIR) required 28 States and the District of Columbia to revise their St ate Implementation Plans (SIPs) to reduce specified amounts of SO 2 and/or NO X emissions. The following paragraphs summarize trends in SO 2 emissions prior to the CAIR rulemaking, EPA’s a ssessment of the contri bution of interstate transport to PM 2.5 nonattainment, and the development of emissions budgets to reduce SO 2 emissions from EGUs.

Between 2000 and 2006, sulfur dioxide emissions from electricity ge nerating units (EGUs) decreased by about 842,000 tons (15.0% reducti on based on 2000 emissions) in Tennessee and surrounding States 19,20 (Table 5- 1), while heat input from the same States grew modestly (2.1%) during the same period 21 . Analysis of the year-to-year variation in SO 2 emissions indicates that this decline is not uniform, with the great est 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); Revisi ons to Acid Rain Program; Revisions to the NO X 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, SO 2 emissions are presented for Alabama, Geor gia, 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, Kent ucky, North Carolina, Ohio, Tennessee, and West Virginia59 observed for TVA’s Bull Run and Kingston fossil plan ts - the two coal-fired utilities located in the nonattainment area (Figure 5- 2).

Table 5- 1: SO 2 Emissions 2000-2006 (Acid Rain Program Data)

State SO 2 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 SO 2 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 SO 2 Emissions

0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000

2000 2001 2002 2003 2004 2005 2006SO2Emissions (tons)

TVA Bull Run TVA Kingston Total Figure 5- 2: Change in SO 2 Emissions at TVA Bull Run and Kingston, 2000-2006

The overall decrease in SO 2 emissions is consistent with a gradual decline in emissions since 1995, when the first caps under the Acid Rain Program became effective. Total SO 2 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. Impl ementation of CAIR in 2010 and subsequent years will accelerate this trend, as a tighter SO 2 emissions cap is implemented across the CAIR region and the Title IV allowan ce bank is depleted.

The PM 2.5 NAAQS is based upon annual averages, and because PM 2.5 precursors are carried by wind currents for long distances, the collective c ontribution from multiple upwind States is a pronounced feature of PM 2.5 transport. This transport occu rs throughout the entire year and across a range of wind patterns, small individual contributions from multiple States can significantly impact PM 2.5 attainment. It is likely that at least some nonattainment areas would find it difficult or impossible to attain the sta ndards without upwind reduc tions. In the CAIR rulemaking, EPA used air quality modeling to “remove” an upwind State’s anthropogenic SO 2 and NO X emissions and to determine which downwi nd nonattainment areas received the largest61 ambient impact from upwind emission sources, based on a metric of 0.2 μ g/m 3 PM 2.5 (1% of the annual standard, rounded to one significant digit). The results of EPA’s 2010 Base Case 22 and zero-out modeling runs are indicated in Table 5- 3, which shows the maximum contribution from each upwind State to Tennessee’s PM 2.5 nonattainment counties. The highest modeled contribution to a nona ttainment county in Tennessee (from an upwind State) was 1.27 μg/m 3 (contribution from Georgia to the Hamilton County nonattainment area). Conversely, Te nnessee’s highest contribution to a downwind nonattainment area (not shown in Table 5- 3) was 0.65 μg/m 3 to Walker County Georgia (part of the Chattanooga nonatt ainment area).

Table 5- 3: PM 2.5 Contributions to Tennessee Nonattainment Counties 2010 Base Case

Upwind State Magnitude of Contribution (μg/m 3 ) 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, Ai r Quality Modeling Analyses, Appendix H

Results are shown for States that contribute significantly to at least one nonattainment county in Tennessee. A contribution o f <0.2 μg/ m 3
(rounded to one decimal point) is not considered significant. EPA’s CAIR modeling indicated th at Arkansas, Mississippi, Missou ri, and Virginia contribute less than <0.2 μg/ m 3 to nonattainment in Tennessee, and those St ates were not included in this analysis.

EPA established CAIR emission budgets for SO 2 (Table 5- 4) to reduce the contribution of upwind States to downwind nonattainment areas to below the signifi cance threshold of 0.2
μ g/m 3 . 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 w ill occur in 2015, br inging the total SO 2 reduction to 65 percent from Title IV Phase II allowance levels. The magnitude of SO 2 reduction required to meet the 2010 CAIR budget is about three times greater than the observed emissions reductions between 2000 and 2006, but actual SO 2 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 th at reduction of inters tate transport of PM 2.5 precursors will reduce ambient PM 2.5 concentrations by 1.28 μg/m 3 in the Knoxville area 23

, 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, a nd various estimates and projections for nonEGU and stationary area source emissions. The 2010 and Base Case reflects the net eff ects of economic growth and emissions red uctions, compared to the 2001 emission inventory.

23 See Table VI-10 in the CAIR final rule.62 Table 5- 4: CAIR Annual SO 2 State Trading Budgets for Tennessee and Surrounding States

State CAIR Annual SO 2 State Trading Budget for 2010- 2014 (tons) CAIR Annual SO 2 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 leas t one nonattainment county in 201 0 base case, based on EPA CAI R air quality modeling results. CAIR SO 2 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 contro ls or purchasing emi ssion allowances. The Tennessee Valley Authority has be gun engineering or construction on several EGUs in the TVA system, as indicated in Table 5- 5. Projected changes in TVA’s SO 2 , NO X , and particulate matter emissions are shown in Table 5- 6.

Table 5- 5: CAIR SO 2 Controls at Tennessee Valley Authority EGUs

Facility 2006 SO 2 Emissions (tons) 2006 SO 2 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 thisfacility 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 PM 2.5 Emissions (tons) SO 2 Emissions (tons) NO X 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 5,558 108,7 89 102,302 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 mob ile source emissions reduction initia tives will result in reduced emissions from nonroad sources, including lawnmowe rs and garden equipment, farm equipment and construction equipment.

In 1994, EPA adopted the first set of emission st andards (Tier 1) for a ll 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 “Tie r 3” standards for engi nes between 37 and 560 kW (50 and 750 horsepower) from 2006 to 2008. The EPA estimates these standards will further reduce nonroad diesel engi ne emissions by 60% for NO X and 40% for particulate matter from the 1994 Tier 1 emission levels 24

.

In addition to controls on nonroa d diesel engines, EPA is phasing in a set of controls for nonroad spark ignition engines. Starting in 2007, manuf acturers will need to meet more stringent standards which will result in a 90% reduction in NO X , HC, and CO emissions 25 . Additional controls will reduce evapor ative hydrocarbon emissions from gasoline fuel tanks.

5. 3. Onroad Mobile Sources

Onroad mobile sources in the Knoxville Nona ttainment Area are estimated to contribute only about 2.5% of the tota l directly emitted PM 2.5 in 2009. Several Federal motor vehicle control measures in place will substantia lly decrease the amount of polluti on from new cars and trucks. These measures will significantly reduce polluti on from the onroad mobile source sector in the future.

New federal emissions standards for onroad heavy-duty diesel engi nes and vehicles, beginning in 2004, will contribute significantly to reductions in NO X 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 Po llution 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 NO X and particulate matter reduc tions of around 90%. As the fleet of vehicles nationally, and in the Knoxville area, is re placed 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 Ve hicles (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 standard s. Federal Tier 2 vehicle emission standards will re quire all passenger vehicles in a manufacturer’s fleet, including light-duty trucks and Sport Utilit y Vehicles (SUVs), to meet an average standard of 0.07 grams of NO X per mile in 2007 26 . 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 su lfur 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 occu rs naturally in gasoline but interferes with the operation of catalytic converters on vehicles, resulting in higher NO X 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 NO X 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-dut y highway engines, and will also reduce highway diesel fuel sulfur content to 15 ppm, a llowing for additional emi ssion 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 NO X emissions for these new engines using ultra low sulfur diesel, compared to ex isting engines using highe r sulfur content diesel 27

.

5.3c. Statewide Motor Vehicle Anti-Tampering Rule

Effective in 2005, the Tennessee Air Pollution C ontrol Board promulgated a statewide motor vehicle anti-tampering rule. This rule, define d in Chapter 1200-3-36, Mo tor Vehicle Tampering, was promulgated to reduce the air pollution caused by tampering with a motor vehicle’s emissions control system. The area of applicabi lity 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 identi fies 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 Ga soline 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 fo r reasonably available control measures (RACM), reasonably available contro l technology (RACT), and reasonable further progress (RFP), as necessary to demonstrate attainme nt. States must demonstrate that they have adopted all reasonably available control measur es (including RACT for stationary sources) necessary to demonstrate attainment as exped itiously as practicable and to meet any RFP requirements. The SIP revision must contain the list of control meas ures considered by the State, and information and analysis sufficient to suppor t the State's judgment that it has adopted all RACM, including RACT. In determining whether sp ecific control measures must be adopted as RACM, States must consider the cumulative imp act of implementing the available measures. Potential measures that are reasonably availabl e considering technical and economic feasibility must be adopted as RACM if, considered collec tively, they would advan ce the attainment date by one year or more.

The PM 2.5 Implementation Rule provides additional guidance for the identification of appropriate RACT and RACM. The guidance states that a St ate must consider RACT and RACM for all of its nonattainment areas, but that if the State projects that an ar ea will attain the standard within five years of designation as a result of existi ng 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 sign ificant emissions reduc tions 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 contro l measures that would advance the attainment date by one year or more.

6.1. SO 2 and Direct PM 2.5 RACT for Point and Area Sources

Tennessee has established specific limits on partic ulate 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 TAP CR 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 establis hed by rulemaking, a rule change is required to implement more stringent SO 2 or PM 2.5 emission limits for most existing sources 28 . This is a lengthy process, which includes preparation of draft rule cha nges, public participation, and adoption by the Tennessee Air Pollu tion Control Board, followed by detailed review of the rule changes by Tennessee’s Attorney General and Secretary of St ate. Tennessee’s rulemaking

28 Tennessee can establish more stri ngent particulate matter and SO 2 emission limits for new sources that are subject to Tennessee’s Prevention of Significant Deterioration (PSD) or Nonattain ment New Source Review (NNSR) programs.67 experience indicates that this pr ocess requires at least twelve m onths, 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 Knoxvill e nonattainment area, which is included with Attachment I.

6.2. PM 2.5 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 re gulatory RACT/RACM requirement for a PM 2.5 SIP revision can be found at 40 C.F.R. Section 51.1010:

(a) For each PM 2.5 nonattainment area, the State sh all submit with the attainment demonstration a SIP revision demonstra ting that it has adopted all reasonably available control measures (including RA CT for stationary s ources) necessary to demonstrate attainment as expeditiously as practicable and to meet any RFP requirements. The SIP revision shall cont ain the list of the potential measures considered by the State, and informati on and analysis sufficient to support the State's judgment that it has a dopted 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 PM 2.5 from onroad and nonroad engine s would not be practical, cost effective, or achievable in a timely fashion to expedite attainment of the PM 2.5 NAAQS in the Knoxville PM 2.5 Nonattainment Area. All onroad and nonroad engines combined are expected to contribute less than seven percent of the total PM 2.5 emissions in the projected 2009 emissions inventory. Any control measure for th ese engines would provide a negligible amount of reductions, which would not expedite attainment of the PM 2.5 NAAQS. There are significant reductions expected from these sectors from ex isting Federal measures affecting both fuels and engines. In addition, an I/M pr ogram for onroad heavy-duty diesel engines is not viable since a large proportion of heavy-duty diesel trucks (tra ctor-trailer type) trav el 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 nona ttainment area. For onroad light-duty vehicles, an I/M program is not practical since the to tal impact from onroad vehicles to the PM 2.5 inventory in the Knoxville PM 2.5 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 additiona l control measures that could be adopted by January 1, 2009 that would lead to earlier attainment. Further, existing measures, and those68 planned for implementation by 2009, are expected to bring the region to attainment with the PM 2.5 NAAQS. As such, no further actio ns on RACT/RACM are warranted.

The modeled attainment demonstration presented in Section 8.0 demonstrat es that the cumulative impact of the control measures described in Section 5.0 will be sufficient to comply with the PM 2.5 NAAQS by April 2009. Therefore, the Knoxv ille area has implemented all of the necessary measures to demonstrate attainment as expeditiously as practi cable and to meet any RFP requirements, and no additiona l measures are necessary.

As demonstrated by the emissi on inventory, modeled attainment demonstration, and contingency measures, PM 2.5 in the Knoxville area results primarily from emissions of sulfur dioxide and organic carbon. Substantial reduc tions of local and regional SO 2 emissions will occur by 2009 as utilities install controls to comp ly with CAIR. The available info rmation 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 m easures described in Section 5.0 to attain the PM 2.5 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. Th e MVEB was developed th rough consultation with the Interagency Consultation Partners. The annual vehicle miles travelled for 2009 were obtained from the Knoxville Transportation Pl anning Organization’s (TPO) most recent conformity determination as presented in Ta ble 7- 1. Further discussion is included in Attachment D of the SIP documentation.

Table 7- 1: Total 2009 Annual Vehicl e Miles Traveled in the Knoxville PM 2.5 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 M obile Source Emissions Inventories for PM 2.5 Nonattainment Areas for Use in SIPs and Conformity 29 was followed to develop the onroad emissions inventories. Key planning assu mptions were developed through interagency consultation. For example, it was determined that an annual average m odeling run to generate emission factors is a reasonable representation of the annual emissions for PM 2.5 and its precursors. Additionally, annual average minimu m and maximum temperatures were developed during the initial PM 2.5 transportation conformity determ ination 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 documen tation. 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 c ounty are summarized in Appendix B.5 of this same document. The Off-Model Analysis for Roane County is

29 EPA420-B-05-008, August 200570 contained in the Air Quality Conformity Determination (March 22, 2006), Appendix E; the VMT and emission factors are c ontained in Appendix C2.6.

7.2. PM 2.5 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 decide d through Interagency Consultation (IAC) that a regional emissions budget would be the most appr opriate for the Knoxville nonattainment area.

The mobile inputs used to develop the attainme nt demonstration modeling as well as the MVEB were developed through interagenc y consultation with the transportation partners for this area. Emissions developed through the attainment demons tration modeling were us ed in evaluating the various precursors since precu rsor information was availabl e and extensive modeling and sensitivity analysis was conducted on this i nventory. The MVEB is developed from modeling conducted by the Knoxville Transportation Pla nning Organization (TPO) so that the MVEB development is as consistent as possible with th e methods used to determine conformity. Note, however, the Onroad Mobile emissions estimate s 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 numbe r 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 hinde r the timely attainment of the NAAQS.

Pursuant to the EPA’s transpor tation 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 PM 2.5 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 accep table air quality in the Knoxville area. This MVEB applies to th e entire Knoxville PM 2.5 nonattainment area, including the donut area contained in Roane County.

Table 7- 2: PM 2.5 MVEB for 2009

Pollutant: 2009 MVEB (tons/year) PM 2.5 283.6371 7.3. Presumed Precursors for PM 2.5

EPA’s Clean Air Fine Particul ate Implementation Rule 30 (Implementation Rule) in §51.1002 outlines EPA’s presumptive policy that SO 2 and NO X are significant unless demonstrated otherwise by the State. Specifical ly, the Implementation Rule states:

“(1) The State must addre ss sulfur dioxide as a PM 2.5 attainment plan precursor and evaluate sources of SO 2 emissions in the State for control measures.”

SO 2 has been considered for control programs from point sources. SO 2 emissions from onroad mobile sources are discussed below.

The rule continues:

“(2) The State must address NO X as a PM 2.5 attainment plan precursor and evaluate sources of NO X emissions in the State for control measures, unless the State and EPA provide an a ppropriate technical demonstr ation for a specific area showing that NO X emissions from sources in the State do not significantly contribute to PM 2.5 concentrations in the nonattainment area.”

Tennessee believes NO X to be an insignificant PM 2.5 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 PM 2.5 attainment plan precursor and evaluate sources of VO C 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 PM 2.5 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 Ru le provides that Stat es do not need to a ddress ammonia as a PM 2.5 attainment plan precursor:

“(4) The State is not require d to address ammonia as a PM 2.5 attainment plan precursor and evaluate sources of amm onia unless: (i) the State provides an appropriate technical dem onstration for a specific area showing that ammonia emissions from sources in the St ate significantly contribute to PM 2.5 concentrations in the nonattainment area, and such demonstration is approved by EPA; or (ii) The EPA provides su ch 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-AK7472 Road and construction dust is al so discussed below. The St ate concurs with EPA’s opinion outlined in the Implementation Rule that road a nd construction dust, or “crustal material” is “only a minor part of the PM 2.5 annual average concentratio ns.” as discussed below.

7.3a. Volatile Organic Compounds (VOC)

EPA’s final implementation rule explains that States are not required to address VOC in PM 2.5 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 PM 2.5 concentrations in a given nonattainment area.

EPA’s Clean Air Fine Particulate Implementation Rule explicitly states that “significant contribution” to the nonattainment area’s PM 2.5 concentration means that a significant change in emissions of the precursor from sources in the st ate would be projected to provide a significant change in PM 2.5 concentrations in the nonattainment area” 31

.

Tennessee has examined the sources of VO C emissions and their contribution to PM 2.5 in Knoxville Nonattainment Area. Due to the gene rally 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 sour ce of VOC emissions in Tenness ee and accounts for the majority of VOC emissions.

Tennessee believes that highway mobile VOC s are insignificant contributors to PM 2.5 formation in the Knoxville nonattainment area. Emission estim ates 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 co ncept to the transportation pa rtners, and agr eed through the interagency consultation, that VOC emissions ar e insignificant. Therefore, Tennessee will not set a MVEB for VOC for the K noxville nonattainment area.

7.3b. Ammonia (NH 4 )

EPA’s policy on ammonia presumes that ammonia is not a PM 2.5 attainment plan precursor. The State is not required to address ammonia in its attainment pl an or evaluate sources of ammonia emissions for reduction measures unless a techni cal demonstration by th e State or EPA shows that ammonia emissions from sources in the State significan tly contribute to PM 2.5 concentrations in a given nonatta inment area or to downwind air quality. Tennessee agrees with EPA’s policy regarding the uncertainty regard ing the emissions inventories and potential efficacy of control measures for ammonia.

7.3c. Nitrogen Oxides (NO X )

Nitrogen Oxides as a PM 2.5 precursor was discussed in Section 3.0, NO X Insignificance. As indicated in Section 3.11, EPA has indicated that NO X should be considered a significant

31 EPA Clean Air Fine Particle Implementation Rule 40 CFR Part 51 EPA-HQ-2003-0062; FRL-RIN 2060-AK7473 precursor to PM 2.5 formation. A motor vehicle emissions budget for NO X 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 PM 2.5 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 PM 2.5 compared to PM 10 in general.

Further in the same rule, on page 40036 EPA st ates 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 PM 2.5 annual average concentrations.” From SANDWICH data illustrated in the NO X Insignificance Demonstra tion, all crustal material constitutes from three to six percent of the total PM 2.5 mass captured at area monitors. Road and construction dust constitute a small fraction of this amount.

Tennessee’s temperate climate and relatively fe w unpaved roads leave littl e opportunity for road or construction dust to become significant contributors to PM 2.5 . In addition, generally regular rainfall removes dust from paved roads and helps keep unpaved roads from b ecoming a source of significant PM 2.5 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 insigni ficant 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, in cluding the percentage of motor vehicle emi ssions in the context of the total SIP inventory, the cu rrent state of air quality as de termined 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 (SO X )

EPA’s Clean Air Fine Particle Implementation Rule states: “Sulfur oxides are mostly emitted from the combustion of fossil fuels in boilers opera ted by electric utilities and other industry. Less than 20 percent of SO 2 emissions nationwide are from othe r sources, mainly other industrial processes such as oil re fining and pulp and paper production” EP A also states that sulfur dioxide emissions from motor vehicles would not necess itate 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 decl ine in the future due to the implementation of requirements fo r low-sulfur gasoline (which bega n in 2004) and for low sulfur diesel fuel (beginning in 2006).” Tennessee agrees with EPA, and therefor e, there will not be a74 motor vehicle budget set for SO X
. An affirmative insignificance finding from the EPA only relieves the transportation partners from a regional emissions analysis for insignifica nt emissions for this area and does not relieve them of the other transportation conformity requirements. The tr ansportation partners will need to note the insignificance findi ng (if found adequate and appr oved by the EPA) in future conformity determinations.75 8.0 MODELED ATTAINMENT DEMONSTRATION

A modeled attainment demonstration consists of analyses whic h estimate whether selected emissions reductions will result in ambient c oncentrations that meet the NAAQS and an identified set of control measures which will result in the require d emissions reductions. Emission reduction strategies are typically simula ted by reducing emissions from specific source categories. The amount of emission reduction n eeded to demonstrate attainment of the NAAQS is estimated using the modeled attainment test . EPA suggests that Stat es consider a broader set of model results and perform corroboratory an alyses to support whether a proposed control strategy will lead to atta inment of the NAAQS.

8.1. ASIP Workgroup

Southeastern States Air Resource Managers, Inc. (SESARM), is a Georgia corporation organized and operated under the provi sions 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 re gulations 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 St ates to collabor ate in regional analyses of the haze problem. The SESARM member agencies, plus Virginia and West Virginia, determined that a collaborative effort was appropriate for regiona l haze and formed the Visibility Improvement State and Tribal Association of the Southeas t (VISTAS). VISTAS member agencies work together on a variety of engineering, administ rative, and organizational haze-related tasks.

On December 17, 2004, EPA designated at leas t one area as nonattainment for the PM 2.5 NAAQS in seven southeastern States: Alabama, Georgia, North Carolina, Kentucky, Tennessee, Virginia, and West Virginia. EPA guidance i ndicates that a significa nt requirement of PM 2.5 SIPs will be attainment demonstrations using m odeling and other analyses to define effective emissions control strategies and to confirm attainment with the NAAQS.

Because the PM 2.5 attainment demonstration requires m odeling 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 PM 2.5 work. The name of this collaborat ive effort is the Association for Southeastern Integrated Planning (ASIP). SESA RM was awarded a grant from EPA on February 8, 2005, to conduct ASIP work.

PM 2.5 modeling was performed by the ASIP workgr oup for ten Southeastern States, including Tennessee. This modeling was conducted as i ndicated 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 PM 2.5 modeling:

• MM5: The Pennsylvania State University/Nat ional Center for Atmospheric Research (PSU/NCAR) Mesoscale Meteorologica l Model (MM5) is a nonhydrostatic, prognostic meteorological model routinely used for urban- and regional-scale photochemical, fine particulate, and re gional haze regulatory modeling studies.

• SMOKE : The Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system is an emissions modeling system that ge nerates hourly gridded speciated emission inputs of mobile, nonroad, area, point, fi re and biogenic emission sources for photochemical grid models.

• CMAQ: EPA’s Models-3/Community Multiscale Air Quality (CMAQ) modeling system is a ‘One-Atmosphere’ photochemi cal grid model capable of addressing ozone, particulate matter (PM), visibility a nd acid deposition at regional scale for periods up to one year.

8.2a. MM5 Overview

The non-hydrostatic MM5 model is a three-dime nsional, limited-area, primitive equation, prognostic model that has been used widely in re gional 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 a nd research models. In the non-hydrostatic MM5, sigma levels are defined according to the initial hydrostatically-balanced re ference state so that the sigma levels are also time-invariant. Th e gridded meteorological fields produced by MM5 are directly compatible with the input requirement s 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 in terpolation, followed by a mass-conservation readjustment.

Distinct planetary boundary layer (PBL) para meterizations 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 fi rst-order scheme for unstable regimes. The other uses a prognostic equation for the second-o rder turbulent kinetic energy, while diagnosing the other key boundary layer terms.

Initial and lateral boundary conditio ns are specified for real-dat a cases from mesoscale threedimensional analyses performed at 12-hour interv als on the outermost grid mesh selected by the user. Surface fields are analyzed at three-hour intervals. A Cre ssman-based techni que is used to77 analyze standard surface and radiosonde obse rvations, 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 re gulatory 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 altern ative models.

The configuration used for this modeling demonstra tion, as well as a more detailed description of the MM5 model, can be found in the ASIP Mode ling Protocol (Attachment C) and in the MM5 Report (Attachment J).

8.2b. SMOKE Overview

The SMOKE Emissions Processing System Protot ype was originally de veloped 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 s ources, its purpose is to provide an efficient, modern tool for convertin g emissions inventory data into the formatted emission files required by an air quality simu lation 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 algor ithms. Indeed, SMOKE is the fastest emissions processing tool currently availa ble 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 us ed in previous systems. The processing is flexible because the processing steps of tempor al projection, controls, chemical speciation, temporal allocation, and spatial allocation have been separate d into independent operations wherever possible. The results from these steps are merged together at a final stage of processing.

SMOKE contains a number of ma jor features that make it an attractive component of the modeling system. The model supports a variet y of input formats from other emissions processing systems and models. It supports bot h 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 4.5 33 . 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 modeli ng system capable of addressing ozone, fine particulate matter, visibility and acid deposition within a co mmon 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-scien ce representations of atmospheric processes in a high performance computing environmen t. EPA completed the initial stage of development with Models-3 and rele ased CMAQ in mid-1999 as the initial operating science model under the Models-3 framework. The most recent rendit ion is CMAQ version 4.4, which was released in October 2004.

Another reason for choosing CMAQ as the atmo spheric model is the ability to do oneatmospheric modeling. Since the same modeling exercise for the ozone and PM 2.5 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 mode l well suited for annual PM modeling.

The configuration used for this modeling demonstra tion, 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 PM 2.5 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 re sponse to changes in emissions. The year 2002 was selected as the base year for several reasons.

EPA’s guidance on PM 2.5 modeling identifies specific goals to consider when selecting one or more episodes for use in demonstrating attainment of the PM 2.5 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 PM 2.5 NAAQS;

• To the extent possible, the modeling da tabase 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 CMA Q to include important SOA processes missing in the standard CMAQ m odel. The updates significantly improved the OCM performance in the summer. The processes missing in the current standard versions of CMAQ, which were included as pa rt of the SOAmods enhancement , are described in Section 1.3.3.3.1 of Attachme nt C (ASIP Modeling Protocol). EPA intends to address SOA issues in the fall 2008 CM AQ release, which is too late for PM 2.5 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 PM 2.5 modeling, the preferred approach is to model a full, representative year. EPA also lists several other considerations to bear in mind when choosing PM 2.5 modeling episodes including: (a) use of periods that have al ready 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 cr iteria as possible in the maximum number of nonattainment areas. The ASIP workgroup adopt ed a logical, step wise approach in implementing the EPA guidance, in order to identify the most preferable year for PM 2.5 modeling.

The ASIP work group adopted a logical, stepwise approach inimplementing 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 ch aracteristics and data sets in the ASIP region directly relevant to the evaluati on of candidate annua l modeling episodes.

• Initial Episode Typing: At the time of selection in 2003, meteorological and air quality data were available for 2002 for model input s and model performance evaluation. ASIP used Classification and Regression Tree (CAR T) analyses to evaluate the candidate modeling years (Atta chment K). The year 2002 was found to be representative of conditions in the other years. Subsequentl y, 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 200 0-2004 baseline period. This analysis confirmed that visibility and PM 2.5 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 PM 2.5 , meteorological, and emissions data and re presentativeness of alternative baseline modeling periods from a regulatory standpoi nt. Additionally, 2002 was the year that EPA required States to provi de emissions inventory da ta for the Comprehensive Emissions Reporting Rule (CERR), and the us e of 2002 as the modeling year allowed the ASIP work group to take adva ntage 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 modeli ng. All of EPA’s criteria for model year selection were considered in this process, as well as other considerat ions (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 continen tal United States (US) domain with a 36-km horizontal grid resolution was used, and th e CMAQ domain was nested in the MM5 domain. Figure 8- 1 shows the MM5 horizontal domain a nd the nested CMAQ 36-km domain. To achieve finer spatial resolution in the AS IP States, a one-way nested hi gh resolution grid (12-km grid resolution) was used (Figure 8- 2).

Figure 8- 1: MM5 Horizontal Domain (B lue) with Nested CMAQ 36-km Domain81 Figure 8- 2: ASIP Region 12-km Grid

8.4b. Vertical Modeling Domain

The CMAQ vertical structure is primarily de fined by the vertical grid used in the MM5 modeling. The MM5 model employed a terrain-follo wing coordinate system defined by pressure, using 34 layers that extend from the surface to th e 100 mb. Table 8- 1 lists the layer definitions for MM5 and CMAQ. A layer averaging sche me is adopted for CMAQ to reduce the computational cost of the CMAQ simulations. The effects of layer averag ing were evaluated in the VISTAS Phase I modeling effort and found to have a relatively mi nor 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 Collapsi ng 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 ba sis for the ASIP modeling. These data were founded on 2002 Consolidated Emission Reporting Rule (CERR) inventories submitted to VISTAS and were reviewed by VISTAS stake holders for completeness and accuracy. NonVISTAS state emissions were based on representati ve inventories obtained from other RPOs or EPA. Stationary source data were supplem ented 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 and83 future year emission runs were based on “typical year” inventor ies for 2002 and future years.

Emissions data were converted to Inventory Data Analyzer (IDA) formatted versions and processed for air quality modeling using Versi on 2.1 of the Sparse Matrix Operating Kernel Emissions (SMOKE) model. Temporal and specia tion profiles and cross-reference data were included in these runs, augmented with r ecommended and approved emission profile data provided by the emissions invent ory contractor, obtaine d 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 deve loped for the National RPO grid.

8.6. Ozone Column Data

Additional data used in the air quality mode ling 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 period s 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 A ugust 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 th e 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-speci fic 3-hour averages from a 2002 GEOS-CHEM global simulation model out put. 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 gui dance on developing a Quality Assurance Project Plan (QAPP) for modeling st udies 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-cy cle development process that minimizes errors;

• clear documentation of assumptions, theory, an d parameterization that is detailed enough so others can fully unde rstand the model output;

• input data and parameters that are accu rate and appropriate for the problem;

• output data that can be used to help inform decision making;

• documentation of any changes from th e original quality assurance plan;

EPA’s guidance specified that the required qu ality assurance would depend on the intended application of the model, a nd 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 tim e consuming and involves complex manipulation of many different types of large da ta 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 pe rform quality assurance activities on emission inventory data obtained from the ASIP emissions inventory contra ctors and inventory data used for modeling outside of th e Southeastern States.

The Emissions Gatekeeper reviewed the content a nd format of emission inventories to ensure an appropriate appraisal of the data . Other tasks included additional translation from mass emissions files into the emissions mode ling input file structure. Th e Study Team supplemented these activities with QA checks on the intermediate a nd model output files, us ing internal and public domain visualization an d 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 indepe ndent review and qual ity assurance of the meteorological modeling and related data se ts 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 informa tion 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 emissi ons 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 i nput 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 us ed to run each model.

• Evaluation of results to verify that model out put is reasonable and consistent with general expectations.

• Processing of ambient monitoring data for use in the model performance evaluation.

• Evaluation of the CCTM results ag ainst concurrent observations.

• Backup and archiving of cr itical model input data.

8.10. Model Performance Evaluation 34

A critical component of every air quality mode ling 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 indica tion of its reliability. The first step in the modeling process is to verify the model’ s ability to correctly predict ambient PM 2.5 concentrations, including the correct mixture of individual components (e.g., sulfate, nitrate, ammonium, organic carbon, el emental carbon, and other PM 2.5 ). Model predictions for the base year simulation are compared to the ambient data observed in the histor ical episode, using a combination of statistical and graphical evaluati ons. If the model appears to correctly predict ambient PM 2.5 concentrations at various locations, then th e model can be used as a predictive tool to evaluate the effect of control strategies on ambient PM 2.5 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 PM 2.5 and its component species in PM 2.5 nonattainment areas (NAAs), building upon prior work by the ASIP workgroup (formerly VISTAS 35 ) for regional haze and ozone evaluations 36 . The VISTAS regional haze components and the ASIP urban ozone model performance evaluations are directly relevant to the ASIP PM 2.5 evaluation, since they share many of the same precursor/product species and atmospheri c processes that produce elevated PM 2.5 levels in the

34 This section is a summary of the Environ Model Performance Evaluation (January 2008), Chapter 3. For the full document, inc luding relevant citations, see Attachment F.
35 Visibility Improvement State and Trib al 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 mor e 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 PM 2.5 mass and PM 2.5 component species model performance evaluation. Appendix C of Attachment F provides a qualitative evaluation of the CMAQ base case for PM 2.5 components and total mass86 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) m odeling 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 Ca rbon Mass (OCM)38, the ba sic 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 pe rformance evaluation were compared with observational data from various monitoring netw orks. VISTAS focused primarily on the air quality model’s performance with respect to individua l components of fine particulate matter (PM 2.5 ), 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 performan ce evaluation focuses on ozone and PM 2.5 performance in urban and nonattainment areas (NAAs). The ASIP PM 2.5 evaluation is summarized in A ttachment 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, PM 2.5 and regional haze modeling guida nce calls for a comprehensive, multi-layered approach to model performance tes ting, consisting of the four major components: operational, diagnostic, mechanistic (or sc ientific) and probabilis tic. The CMAQ model performance evaluation effort for PM 2.5 focuses on the first two components of the EPA’s recommended evaluation approach, namely:

• Operational Evaluation : Tests the ability of the model to estimate PM 2.5 mass concentrations and the components of PM 2.5 (sulfate, nitrate, ammonium, organic carbon matter, elemental carbon, and other inorganic PM 2.5 ). This evaluation examines whether the measurements are properly represente d 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 includi ng PM precursors (e.g., SO 2 , NO X , and NH 3 ) 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 regiona l 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 CMA Q to include important SOA processes missing in the standard CMAQ model that significantly improved the OCM performance in the summe r. The processes missing in the current standard versions of CMAQ, which were included as part of the SO Amods enhancement, are describ ed in Section 1.3.3.3.1 of Attachment C. EPA intends to address S OA issues in the fall 2008 CMAQ release, which is too late for PM 2.5 SIP work. Thus, both VISTAS and ASIP have adopted CMAQ version 4.51 with SOAmods updates as th e core model for the modeling analysis.87 absorption). The diagnostic evaluation also includes the performance of diagnostic tests to better understand model pe rformance and to identify potential flaws in the modeling system that can be corrected.

This model performance evaluation emphasizes th e 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 distribu tions, and has performed numerous diagnostic sensitivity tests to investigate and improve model performance a nd test the model assumptions.

8.10c. Particulate Matter and Component Species

PM 2.5 attainment is based on PM 2.5 mass measurements using Federal Reference Method (FRM) monitoring devices, which measure the following PM 2.5 components:

• Sulfate (SO 4 )

• Nitrate (NO 3 )

• Ammonium (NH 4 )

• Organic Carbon Matter Carbon (OCM)

• Elemental Carbon (EC) [also called Black Carbon ]

• Other Inorganic PM 2.5 (also referred to as soil, crustal material, fine soil, major metal oxides, or other PM 2.5 )

• 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 mon itoring networks available to evaluate the PM 2.5 component of the CMAQ are: (a) Intera gency Monitoring of Protected Visual Environments (IMPROVE); (b) Clean Air St atus and Trends Network (CASTNET); (c) Southeastern Aerosol Research and Character ization (SEARCH); (d) EPA Federal Reference Method (FRM) PM 2.5 and PM 10 Mass Networks (EPA-FRM); (e) EPA Speciation Trends Network (STN) of PM 2.5 species; and (f) National Acid Deposition Network (NADP). Table 8-2 and Figure 8- 3 summarize the spec ies 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 PM 2.5 and PM 10 1 in 3 days; 24 hr
CASTNET Speciated PM 2.5 , Ozone Hourly, Weekly; 1 hr, Week

SEARCH 24-hr PM 25 (FRM Mass, OC, BC, SO 4 , NO 3 , NH 4 , Elem.); 24-hr PM coarse (SO 4 , NO 3 , NH 4 , elements); Hourly PM 2.5 (Mass, SO 4 , NO 3 , NH 4 , EC, TC); and Hourly gases (O 3 , NO, NO 2 , NO y , HNO 3 , SO 2 , CO) Daily, Hourly;

NADP WSO 4 , WNO 3 , WNH 4 Weekly
EPA-FRM Only total fine mass ( PM 2.5 ) 1 in 3 days; 24 hr
EPA-STN Speciated PM 2.5 Varies; Varies AIRS/AQS CO, NO, NO 2 , NO X , O 3 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 statisti cal 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 sta tistical 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 Attain ment of Air Quality Goals for Ozone, PM 2.5 , and Regional Haze . The ASIP model performance evalua tion considered several statistical performance measures and displays and reviewed numerous metrics to evaluate their descriptive capabilities for summarizing the relevant features of the mo del performance evaluation.

Although numerous model performa nce statistics measures are routinely used, ASIP has found that the fractional bias and frac tional gross error provide the best descriptive power over a wide range of concentrations. The fractional bias a nd error are expressed as a percentage and are normalized by the average of th e predicted and observed values . Consequently, they are bounded statistics, with the fractional bias boun ded 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 goa ls 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 O P O P
N 1 2 Reported as %

Mean Fractionalized Bias (Fractional Bias) MFB 

## ∑

= ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛

+ − N

i i i i i O P O P
N 1 2 Reported as %

Table 8- 4: ASIP Model Perfor mance Goals and Criteria for PM 2.5 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 concen tration fractional bias and error across the ASIP 12-km grid region for the IMPROVE, ST N, CASTNet, SEARCH Daily and SEARCH Hourly monitoring networks for sulfat e, nitrate, organic carbon, other PM 2.5 /soil, and total PM 2.5
.90Table 8- 5: Regional Model Performance Evaluation Summary of ResultsComponentModel Performance ResultsSulfate (SO4) Underprediction bias is clearly evident across most ofthe year and monitoring networks with the lowest SO4bias occurring in October.Underprediction bias is notsevere (almost always within ±20% and always within ±25%), and almost always achieves the PM model performance goals for bias/error (i.e., within ±30% forfractional bias and 50% for fractional error), except for the comparison with the SEARCH Hourly network (exhibits a positive overprediction bias for severalmonths).SO4monthly fractional error values are usually under 40% and, withone exception, always under 50%. The exception is comparisonwith the SEARCH Hourlynetwork (error values ranging from 50% to 70%). SEARCH hourly SO4measurements are made with research grade monitoring equipment and are probablysubject to greater uncertainties than the other monitoring networks. Summer SO4underprediction bias is due in part tooverstated convective precipitation in theMM5 simulations. This is somewhat confirmed by the SO4wet deposition model performance evaluation thatexhibits near zero bias during the winter (whenprecipitation is dominated by synoptic weather events) but has a positive overprediction biasduring the summer (when convective precipitation is greatest).Nitrate (NO3) Monthly fractional bias time series plot for NO3clearly shows a seasonal dependence of this performance measure. Summer underprediction bias is fairly severe (-100% to -150%). Winter bias values are generally within ±50%.Fractional error values also exhibit a seasonal dependence. Error is 80% in the winter peakingand is 160% error with a bell-like distribution in the summer. Large summer underprediction bias occurs when NO3concentrations are extremely low (< 1.0μg/m3). When the average observed NO3concentration exceeds 1μg/m3,the model mostly achieves the model performance goal and almost always achieves themodel performance criteria for bias. The model performance goal and criteria are achieved less often for NO3fractional error, but the goal is always achievedacross the CASTNet and usually achieved across the IMPROVE monitoring networks.Organic Carbon Mass (OCM) Fairly good performance across the IMPROVEmonitors, with bias usually within ±15% and errors between 40% and 50%. Model exhibits a large OCMunderprediction bias of -35% to -60% at urban STN sites. Underprediction bias at the STN sites may be due to multiple factors,such as measurement uncertaintiesor over-dilution of urban OCM emissions by the model through the coarse 12-km grid. Underprediction of urban OCM is a common problem in PM modeling andmay point to uncertainties in the OCM and SOA precursor emission inventories.OCM performance was a concern in the preliminary CMAQ evaluationsusing early VISTAS Phase I and II databases, due to a large summer OCMunderprediction bias and the importance of OCM to the visibilityextinction and PM budgets. VISTAS conducted a focused research study on the causes ofsummer OCM underprediction, the identification of missing processes in the CMAQ model, and the development of the SOAmods enhancement to CMAQ, whichgreatly improved the CMAQ OCM model performance. The CMAQ Version 4.51 with the SOAmods enhancements was used in the ASIP modeling.Elemental Carbon (EC) Bias and error are lower in the first andlast quarters of the year. During the summer and adjacent months EC performance across the IMPROVE networks exhibitsa large underprediction bias (-40% to -80%) that peaks in June.EC performance across the SEARCH network is somewhat similar to IMPROVE, but with lowerunderprediction bias in the summer. Model performance comparedto the STN network has fairly low EC fractional bias during quarters 1, 3 and 4 (< ±15%), withlarger underprediction bias during quarter 2 (-20% to -40%). The comparison to the STN network very low EC bias during most ofthe year suggests that theanthropogenic EC emissions inventory may beadequately characterized in urban areas.Other PM2.5or SoilSeasonal dependence of the Soil model performance across the IMPROVEand STN monitors is clearlyevident, with a large overprediction bias (> 100%) in thewinter and near zero (IMPROVE) or much lower (SEARCH) bias inthe summer. Modeled Soil values tend to be between 0 and 2μg/m3year round, but observedvalues are much lower inthe winter (0 to 0.5μg/m3) and are comparable to modeled values in summer.Poorer winter Soil model performance is likely due toincorrect emission temporal adjustment factors.Fine Particulate (PM2.5)The model generally exhibits good performance for total PM2.5mass concentrations. During the first and lastquarters of the year the model performs well forPM2.5, with low fractional bias (<±20%) and error (<40%) except for theSEARCH Hourly network. Underprediction bias (-20% to -45%)and errors are largerfrom April to July, due in part to the SO4underprediction bias discussed above (SO4is a major component of PM2.5in the southeastern U.S. during summer).91 8.10g. PM 2.5 Attainment Test for Tennessee

CMAQ predicts the observed SO 4 concentrations in Tennessee wi th bias and error values that achieve, or nearly achieve, the most stringent ozone 39 performance goal (Figure 8- 4). CMAQ 12-km results are slightly better than 36-km pred ictions. Unlike other States, where the largest underprediction bias was obser ved in July, Tennessee’s SO 4 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 (SO 4 ) 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 w ith nitrate predictions (Figure 8- 5) and a large underprediction bias 40 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 performa nce (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 Oct ober, but tends to under-predict in April and July (Figure 8- 8).

Figure 8- 5: Scatter Plots of Predicted and Observed Nitrate (NO 3 ) 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 P redicted and Observed Ammonium (NH 4 ) 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 Ac tual Base Case Simulation95 Figure 8- 8: Scatter plots of Predicte d 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 Ac tual Base Case Simulation

Tennessee’s PM 2.5 mass performance across the STN and FR M networks is illustrated in Figure 8- 9 and Figure 8- 10. Across the STN networks, performance for PM 2.5 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 mode l performs better acro ss the FRM network for PM 2.5 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 (PM 2.5 ) Concentrations for January, April, July and October 2002, STN Sites in Tennessee and the CMAQ 2002 36 and 12 km Base G2 Ac tual Base Case Simulation97 S f f( ) Figure 8- 10: Scatter Plots of Predicte d and Observed Fine Particulate Mass (PM 2.5 ) Concentrations for January, April, July and October 2002, FRM Sites in Tennessee and the CMAQ 2002 36 and 12 km Base G2 Ac tual Base Case Simulation

The monthly fractional bias a nd error Soccer Plot for FRM PM 2.5 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 b ecause 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 PM 2.5 Mass at FRM Monitors in Tennessee for the CMAQ 12-km 2002 Base G2 Actual Base Case Simulation

8.11. PM 2.5 Projections for 2009 41

Attainment for the Knoxville area was demonstrat ed using EPA’s Speciated Modeled Attainment Test (SMAT), following the requirements of EP A’s April 2007 guidance. In order to perform the recommended modeled attainment test, observed mass concentrations of PM 2.5 were divided into seven components, plus passively collected mass:

Sulfate (SO 4 ); Nitrates (NO 3 ); Ammonium (NH 4 ); 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 attainme nt test may be found in Attachment G.99 EPA has published final modeling guidance 42 that includes recommen dations on the use of modeling results to pr oject future-year PM 2.5 levels. EPA recommends use of the modeling results in a relative fashion to scale the observed current-year PM 2.5 Design Value (DVC) to project a future-year PM 2.5 Design Value (DVF). The model- derived scaling factors are called Relative Response Factors (RRFs) a nd are defined as the ratio of th e future-year to current-year modeling results. The future-year PM 2.5 Design Values (DVF) are obtained from the currentyear PM 2.5 Design Values (DVC ) by applying the RRF:

DVF = DVC x RRF

RRFs are site-specific and are de rived from modeling results “nea r” each monitor. Separate RRFs are applied to five components of the PM 2.5 DVC to obtain future-year PM 2.5 estimates from which the DVF is derived that is compared with the PM 2.5 NAAQS.

PM 2.5 attainment is based on PM 2.5 mass measurements collected at FRM monitoring sites. In order to apply the species-specific RRFs, PM 2.5 mass measurements must be speciated into individual components. Two sp eciation networks are operated in the U.S.: (1) the Speciated Trends Network (STN); and (2) the Interagency Monitoring of Protected Visual Environments (IMPROVE) networks. PM 2.5 speciation data from these networks must be mapped to the FRM measurements in order to project future-year PM 2.5 Design Values with RRFs. Two major components are required to project future-y ear design values from modeling results:

SANDWICH Method : Both the FRM PM 2.5 mass and STN/IMPROVE PM 2.5 speciation measurements have positive and negative artifacts that must be accounted for when mapping observed speciation data to the FRM mass measurements. PM 2.5 attainment is based solely on the FRM PM 2.5 mass measurements, and the STN/IMPROVE PM 2.5 speciation measurements must be adjusted to mimic the FRM measurements. EPA has developed the Sulfate Adjusted Nitrate, Deri ved Water Inferred Carbon Hybrid material balance approach (SANDWICH) to estimate the PM 2.5 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 PM 2.5 design values to a future year, using the relative changes in modeled concentrations.

8.11a. SANDWICH Speciation of STN PM 2.5 Components

The SANDWICH procedure is designed to map STN/IMPROVE PM 2.5 speciation measurements to FRM mass measurements and to account for the artifacts and sampling pr otocol variations of both sampling networks. The SANDWICH procedure assumes that the FRM PM 2.5 mass consists of the following components:

42 Guidance on the Use of Models and Other Analyses for Dem onstrating Attainment of Air Quality Goals for Ozone, PM 2.5 and Regional Haze , EPA, 2007.100 FRM PM 2.5 Mass = [SO 4 ] + [EC] + [NO 3FRM ] + [NH 4FRM ] + [OCM mb ] + [water] + [crustal] + [blank correction]

Where:

[SO 4 ] = measured sulfate ion, SO 4 fraction of the STN PM 2.5 from the STN site associated with the FRM monitor;

[EC] = measured elemental carbon from the associated STN monitor;

[NO 3FRM ] = nitrate retained on the FRM filter af ter a portion has been volatilized in the FRM measurement process;

[NH 4FRM ] = NH 4 retained on the FRM filter after partial volatilization;

[OCM mb ] = organic carbon material, obtained as the difference between the FRM PM 2.5 mass measurements and the remainder of the PM 2.5 components;

[water] = particle bound water;

[crustal] = soil and other inorga nic fine particulate matter; and

[blank correction] = passively collected PM material in the STN measurement process, assumed to be 0.5 μ g/m 3

.
8.11a(i). Retained Particulate Nitrate [NO 3FRM ]

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 component s 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 speci ation concentrations, combined with hourly ambient temperature and humidity measurements. Nitrate is typically retained at low temperatures and high humidit y, 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 conditi ons (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 nitrat es, the SANDWICH approach assumed that all retained nitrate was ammonium nitrate, as is lik ely over most of the ASIP region. Assuming that all particulate nitrate is in the form of ammonium nitrate, the am monium associated with nitrates was derived from the FRM retained NO 3FRM as:

NH 4 NO 3 = 0.29 * NO 3FRM101 Similarly, the dry PM 2.5 mass associated with ammoni um nitrate was calculated as:

[Retained dry FRM Ammonium Nitrates] = 1.29 * NO 3FRM

8.11a(iii). Ammoniated Sulfate Mass

Sulfates may not be fully neutralized throughout th e year. In winter, when nitrates are prevalent in the ambient aerosol, sulfates tend to be fu lly neutralized and exist as ammonium sulfate [(NH 4 ) 2 SO 4 ]. Less ammonia is available for reacti on during the summer, when sulfates are higher. The resulting aerosol can be acidic an d the form of sulfates can include ammonium bisulfate [NH 4 SO 4 ] or even H 2 SO 4 . The amount of ammonium asso ciated with th e sulfate ion was estimated as:

NH 4 (SO 4 ) = NH 4adj - 0.29 * NO 3FRM ,

Where: 0.29 = molar ratio of NH 4 to NO 3 and NH 4FRM and NO 3FRM reflect the amounts retained on the FRM filter.

The amount of NH 4 (SO 4 ) may not exceed the fully neutra lized amount of 0.375 multiplied by the estimated sulfate ion concentration. Because of uncertainties in NH 4 speciation measurements, and because the IMPROVE monitoring network does not measure NH 4 , NH 4 was calculated by deriving the degree of sulfate neutra lization (DON) from the estimated NH 4 (SO 4 ) as:

DON = NH 4 (SO 4 ) / SO 4

The DON was assumed to remain constant from the current-year to future-y ear. Values of DON, sulfate and estimated FRM nitrate (adjusted n itrate) were used to estimate the adjusted ammonium at each FRM site as follows:

NH 4FRM = DON * SO 4 + 0.29*NO 3FRM
where, DON, SO 4 and NO 3 FRM were the quarterly average values at each FRM site.

In the default EPA PM 2.5 Design Value projection approach, in terpolated DON values were used to estimate ammonium, due to un certainties in the ammonium m easurements and the lack of NH 4 measurements at IMPROVE sites. However, for the ASIP SANDWICH/SMAT application, the DON, SO 4 and NO 3adj 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 hygroscopi c, the retained sulfate and nitrate mass will include water 43 . Particle bound water (PBW) wa s estimated using the Aerosol Inorganic Model (AIM), using the quarterly aver age FRM concentrations of sulfate, ammonium, and nitrate and typical filter equi libration conditions of 35% RH a nd 22° C. Application of AIM at the specified FRM filter e quilibration conditions indicated th at PBW was more dependent on sulfate concentrations (compared to nitrate) and that the relations hip varied somewhat by season. There was proportionally less esti mated PBW water for winter aerosol, which has higher NH 4 and NO 3 and lower SO 4
.
8.11a(v). Passively Collected PM 2.5 Components (Blank Correction)

Passively collected mass was represented by the typical field blank c oncentration of 0.3-0.5
μ g/m 3 . 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 es timated carbon by mass balance (OCM mb ), comparing precisely measured FRM PM 2.5 mass with the sum of its non-carbon components (sulfates, ammonium, nitrates, particle bound water, crustal material plus 0.5 μ g/m 3 passively collected mass). Because of uncertainties in speciati on measurements, a lower limit (floor) for OCM mb was set so that OCM mb 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 OCM mb concentration was less than the lower limit, it was set equal to the lower limit.

8.11b. Summary of PM 2.5 Composition Calculations

In summary, the SANDWICH species data was generated in the following order:

1. Adjusted nitrate was calculated using hour ly meteorology and 24-hour average nitrate
measurements.

2. Quarterly averages were calcula ted for adjusted nitrate, sulf ate, elemental carbon, degree of sulfate neutraliza tion (DON), crustal mass , and measured OCM.

3. Quarterly average ammonium wa s calculated from the adjusted nitrate, sulfate, and DON values (or in the case of ASIP the NH 4adj is used directly).

4. Calculated ammonium, sulfate, and nitrate valu es were input into the water equation to derive particle bound water concentrations.

43 Note that some organic carbon (OC) species are also likely hy groscopic but, due to various uncertainties, the PBW associated with hygroscopic OC species is not accounted for.103 5. Carbon mass by difference (OMC mb ) was calculated from the PM 2.5 mass, adjusted nitrate, ammonium, sulfate, water, elemen tal carbon, crustal, and blank mass values.

6. The sum of these species plus bla nk mass was equal to the FRM mass.

8.11c. Defining Current-Year PM 2.5 Design Values (DVC)

The PM 2.5 component species fractions ar e applied to current-year PM 2.5 Design Values (DVC), which are projected to the future using model-derived RRFs. EPA’s PM 2.5 modeling guidance recommends using the average of the three years of PM 2.5 design value periods that straddle the emissions year.

Quarterly average values are needed for each FRM site to derive the average PM 2.5 design values for future projections. Quarterly averag e FRM values were derived as follows.

1. The analysis began with qua rterly average FRM data fo r all quarters from 2000-2004.

2. A quarterly average three-year design valu e was calculated for each design value period in which a site had 12 quarters of co mplete 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 c onsisted 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 th e baseline inventory year (e.g., the average of the 2000-2002, 2001- 2003, and 2002-2004 design value periods for a 2002 base line 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 PM 2.5 DVB is determined, as well as component-sp ecific DVB for each quarter.

8.12a(i). Mean PM 2.5 Baseline Design Values

To begin the SMAT process, a mean PM 2.5 DVB is calculated on a quarterly basis for each Federal Reference Method (FRM) monitor in the PM 2.5 nonattainment area. Concentrations are calculated based on calendar quarters (e. g., Q1: Ja nuary - March; Q2: Ap ril - June; etc.) to facilitate comparison with the annual NAAQS and to allow States to examine the differences in PM 2.5 composition during i ndividual seasons.104 Table 8- 6 contains the quarterly average PM 2.5 concentration for the FRM monitors in the nonattainment areas. This quarterly data was av eraged, using the weighted scheme suggested by EPA, to produce a 5-year weighted DVB. Th e Loudon County FRM site (47-105-0108) was not operational for most of the baseli ne period, and the attainment te st was not performed for this monitor (see Section 9.0 for a discussion of this mon itor). Only two years of data were available for FRM monitor 47-093-1013 (1403 Davanna Street). Per the Attainment Guid ance, 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 PM 2.5 DVBs for the nonattainment areas.

Table 8- 6: Knoxville-Area Quarterly Average PM 2.5 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 12.84105 Table 8- 7: Observed Quarterly Mean PM 2.5 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 PM 2.5 utilizes total PM 2.5 and individual PM 2.5 component species. Because a separate RRF is calculated for each PM 2.5 species, States must divide observed PM 2.5 mass concentrations into seven components, plus passive mass:

1. Mass associated with sulfates (SO 4 ); 2. Mass associated with nitrates (NO 3 ); 3. Mass associated with ammonium (NH 4 ); 4. Mass associated with organic carbon (OC); 5. Mass associated with elemental carbon (EC); 6. Mass associated with pa rticle bound water (PBW); 7. Mass associated with “other” primary inor ganic particulate matter (Crustal); and 8. Passively collected mass (ma ss of the blank filter: 0.5 μ g/m 3 )

The second part of the process is to speciate the quarterly mean PM 2.5 DVBs into individual components to calculate the quarterly mean c oncentrations of these components at the FRM sites. This need to speciate the FRM data presents two issues:

8.12a. FRM measurements and speciated PM 2.5 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 expl ain how these issues were overcome to produce the speciated values needed for this at tainment demonstration.

8.12a(iii). SANDWICH Speciation Method

As the Attainment Guidance notes, recent data an alyses have noted that the FRM monitors do not measure the same components and do not retain all of the PM 2.5 that is measured by routine speciation samplers. Therefore, the FRM monitors cannot be di rectly 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 ammoni um nitrate and other semivolatile materials (negative sampling artifacts)106 percent contributions to PM 2.5 mass), which may be different than the ambient levels of some PM 2.5 chemical constituents.

To resolve the differences between FRM and ST N total mass, EPA recommends the “sulfate, adjusted nitrate, derived water, inferred carbonaceous material balance approach” or SANDWICH approach. This approach adjusts n itrate mass to account for volatilization, based on hourly meteorology parameters. Subsequently, qua rterly average nitrate, sulfate, elemental carbon, and crustal mass, and the Degree of Neutrali zation (DON) of sulfates can be calculated. Quarterly average NH 4 can be calculated from the adjusted nitrate mass, sulfate mass, and sulfate DON. The mass of particle bound water can be calculated from DON, su lfate, nitrate, and ammonium values. Finally, organic carbon may be calculated as the difference between the PM 2.5 mass measured at the FRM monitor and th e calculated component mass (i.e. OC from mass balance ([OCMmb]) = PM 2.5FRM - {[EC] + [SO 4 ] + [NO 3 ] + [NH 4 ] + [water] + [crustal material] + [passive mass]}).

8.12a(iv). Speciated Profiles

While the SANDWICH method rec onciles the differences betwee n 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 ta ken to resolve the lack of speciated data:

8.12a. Use of concurrent data from a nearby speciated monitor 8.12b. Use of representative data (f rom a different time period) 8.12c. Use of interpolation techni ques to create a spatial field using ambient speciation data 8.12d. Use of interpolation techniques to creat e spatial fields, and gridded modeling outputs to adjust the sp ecies concentrations

Of the four methodologies, EPA recommends th e use of spatial inter polation techniques to estimate species concentrations at FRM sites th at do not have speciation data (items 3 and 4 above). EPA is developing a so ftware tool called “Modeled Atta inment Test Software” (MATS) that will perform the spatial analysis, but the PM 2.5 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 Inte rstate Rule (CAIR) SMAT tool 45

.

The CAIR SMAT tool uses data from both the Interagency Monitoring of Protected Visual Environments (IMPROVE) and EPA’s Specia tion Network (ESPN) to derive mean concentrations for six PM 2.5 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 PM 2.5 species. Major species for ESPN include EC, OC, NH 4 , SO 4 , NO 3 , and crustal material (whi ch includes the five tr ace elements aluminum, calcium, iron, silicon, and titanium). The major species for IMPROVE are the same except for NH 4 , which is not routinely measured in the IMPROVE protocol.

and includes particle bound water associated with sulfates, nitr ates and other hygroscopic sp ecies (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 PM 2.5 FRM monitoring sites using a technique called Voronoi Neighbor Averaging (VNA).

As a result of the CAIR SMAT process, quarter ly species fractions were generated for the FRM sites, which are presented in Table 8- 8 belo w. These fractions were applied to observed quarterly mean PM 2.5 values to determine quarterly compone nt-specific concentrations (Table 8- 9) shows the quarterly DVBs for crustal, EC, OC, SO 4 , NO 3 , NH 4 and PBW, assuming a constant passive mass of 0.5 μ g/m 3

. Table 8- 8: Quarterly Species Fr actions from the CAIR SMAT Tool

AIRS ID County Site Name Qtr. blank DON Frac. Crustal Frac. EC Frac. OC Frac. SO 4 Frac. NO 3 Frac. NH 4 Frac. H 2 O

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 0.0861108 Table 8- 9: Quarterly and Annual Average Component-Specific Concentrations for the FRM Monitors in the Knoxville, TN PM 2.5 Nonattainment Area

AIRS ID County Quarter FRM Mass Blank Mass Bl an k 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 Knox 47-093-0028 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 PM 2.5 for each quarter. Simply put, the RRF is the quarterly average future y ear concentration near a monitor divided by the quarterly average base year concentr ation near the same monitor, or:

X" " Monitor Near" " ion Concentrat Year Base Modeled Mean Quarterly X" " Monitor Near" " ion Concentrat Year Future Modeled Mean Quarterly

= RRF

Instead of focusing on the individua l 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 th e 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 “near by” cells for grid systems having cells of various sizes. Since the modeling for the attain ment 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 PM 2.5 SMAT, quarterly RRFs are calculated fo r each component. The concentration for each PM 2.5 component is extracted from the base year and future year mode ling output near the FRM monitoring sites for each day. The daily co mponent concentrations from the 3x3 array are averaged to develop a mean daily component ma ss for each day in both the base and future years. These mean daily component concentrati ons 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 PM 2.5 component. The quarterly RRFs for the FRM monito rs in the Knoxville PM 2.5 nonattainment area are presented in Table 8- 11. The CAIR SMAT tool estimates the future mass of NH 4 and PBW from the estimated future mass of SO 4 and NO 3 , in lieu of using RRFs, per the following equations:

NH 4 = DON * SO 4 + 0.29*NO 3
PBW = (-0.002618) + (0.980314*NH 4 ) + (-0.260011* NO 3 ) + (-0.000784* SO 4 ) + (-0.159452* (NH 4 ^2)) + (-0.356957* NO 3 * NH 4 ) + (0.153894* (NO 3 ^2)) + (0.212891* SO 4 * NH 4 ) + 0.0444366* SO 4 * NO 3 ) + (-0.048352* (SO 4 ^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 SO 4 NO 3

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 0.7669110 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 Quarte rly Concentration Calculation

The next step in the SMAT process is to calcula te future quarterly mean concentration estimates for each PM 2.5 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 PM 2.5 nonattainment areas are provided in Table 8- 12.

Table 8- 12: Future Quarterly Component Con centrations for Monito rs in the Knoxville, Tennessee Nonattainment Area (Base G4a)

AIRS ID County Site Name Qtr. DVF (Base G4a)
Crustal EC OC SO 4 NO 3 NH 4 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 calculated111 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 PM 2.5 values. Table 8- 13 displays the quarterly mean PM 2.5 values for the FRM sites in the Knoxville nonattainment area.

Table 8- 13: Quarterly Mean PM 2.5 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 Aven ue 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 PM 2.5 values were averaged to produc e a future year annual average PM 2.5 estimate for each FRM site in the nonattainment ar ea (Table 8- 14). These values estimated annual PM 2.5 values were compared to the NAAQS (15.0 μ g/m 3 ), and since predicted future concentrations values at each FRM site in the nonattainment area are less than 15.0 μ g/m 3 , the attainment test is passed.

Table 8- 14: Estimated Annual Mean 2009 PM 2.5 Mass Compared to the DVB

AIRS ID County Site Name Modeled PM 2.5 Concentrations in μg/m 3

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 Re sults: Base G2a vs. Base G4a

A comparison of the 2009 Base G2a and 2009 Base G4a attainment te st results is presented in Table 8- 15. As this table indicates, a minima l 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 PM 2.5 Concentrations in μg/m 3

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 com ponent of the modeling process, including meteorological data, emissions processing, a nd CMAQ modeling files. Data backup and archiving will be performed at each of the modeling centers (E NVIRON 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 modeli ng files, MM5, SMOKE, and CMAQ on external drives, and an external drive containing all sup porting 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 PM 2.5 Design Value is between 14.5 and 15.5 μ g/m 3 . As indicated in Table 8- 14 and Table 8- 15, the projected future de sign value is above 14.5 μg/m 3 for one monitor in the Knoxville nonattainment area, and a we ight of evidence analys is is required. The weight of evidence analysis is presented in the following section.113 9.0 WEIGHT OF EV IDENCE 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, PM 2.5 , and Regional Haze discusses basic requirements for weight of evidence analyses. This guidance states that St ates should review the results of the modeled attainment test and of seve ral different types of air quality analyses. Each analysis should be weighed according to its credib ility and its ability to assess the adequacy of the proposed attainment strategy, and the conclu sions 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/m 3 at one or more monitoring sites, the guidance states that a weight of evidence de monstration should be conducted to determine whether the aggregate supplemental analyses suppor t the modeled attainment test. As indicated in Table 8- 15, the predicted fu ture design value at one monito r in the Knoxville nonattainment area is greater than 14.5 μg/m 3 , and Tennessee is conducting a wei ght 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 cap acity 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 determina tion 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 eviden ce, 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 additiona l supporting comments in the following paragraphs.

9.1. Air Quality Trends

The Knoxville nonattainment area has seen a significant downwar d trend in annual average PM 2.5 concentrations since 1999, with a corresponding decrease in three-year design values (see Figure 2- 6). The decline in ambient PM 2.5 concentrations was contemporaneous with significant decreases in SO 2 emissions from electric utilities in Tennessee and other States (Table 5- 1 indicates that SO 2 emissions from Tennessee and surr ounding States decreased by about 836,000 tons/year between 2000 and 2006); declining SO 2 emissions from the two electric utilities located in the nonattainment ar ea (see Figure 5- 2); and decr easing emissions from mobile sources due to tighter st andards and fleet turnover 46 . Quarterly air quality monitoring results for all monitors in the Knoxville nonattainmen t area are presented in Attachment E.

46 See Sections 5.0 and 7.0 and Attach ment D for further discussion of emis sion controls for mobile sources.114 9.2. Correlation of Ambient Monitori ng Data with Regional SO 2 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 ch anges appear to be wellcorrelated with reductions in ambient PM 2.5 concentrations at the Knoxville-area monitors. Comparison of ambient monitoring data for the Knoxville area with utility SO 2 emissions data from the Acid Rain Program strongly suggest a linear relationshi p between ambient PM 2.5 levels and local, State, and regional SO 2 emissions. These data suggest that continued SO 2 reductions from electric utilities will result in fu rther declines in ambient PM2.5 levels.

9.3. Emissions Inventory: Changes in Direct PM 2.5 and Precursor Emissions

The Knoxville-area emission inventory was revi ewed to determine wh ether the predicted emission reductions are: 1) significant (i. e., ar e 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 installa tion of wet scrubber controls at TVA’s Bull Run Fossil plant for CAIR compliance. Although the CAIR ru le does not require em ission controls at specific facilities, there is a high probability that these emission reductions will occur as predicted, since physical cons truction of the wet scrubber is almost complete.

Sulfur Dioxide – Mobile Sources : Emissions from nonroad and onr oad mobile sources are also predicted to decline. Mobile source emission s 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 SO 2 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 SO 2 Emissions by Category

Category 2002 SO 2 Emissions, % of Total Inventory % Change in SO 2 Emissions, 2002-2009 2009 SO 2 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 PM 2.5 Emissions : The emission inventory predic ts some growth in direct PM 2.5 emissions between 2002 and 2009, primarily as a result of point source emissi ons growth. Across the entire nonattainment area, the increase in PM 2.5 emissions is offs et by declining SO 2 emissions. However, the inventory predicts significant decreases in PM 2.5 emissions from mobile sources, and these ground-level reductions should have a positive impact on PM 2.5 concentrations within the city of Knoxville and in other high-traffic areas.115 Table 9- 2: 2009 Change in PM 2.5 Emissions by Category

Category 2002 PM 2.5 Emissions, % of Total Inventory % Change in PM 2.5 Emissions, 2002-2009 2009 PM 2.5 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 SO 2 emissions that were not included in the 2009 emission inventory (Table 9- 3). These reductions are expected to have a positive impact on PM 2.5 attainment.

Table 9- 3: Additional SO 2 Reductions Not Included in 2009 Emission Inventory

Facility SO 2 Control Technology Projected SO 2 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 PM 2.5 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 Loudo n County Monitor (47-105-0108)

FRM monitor 47-105-0108 in Loudon County began co llecting data in 2003 and did not collect sufficient data during the 2002-2004 baseline pe riod to be included in the attainment demonstration. Comparison of the PM 2.5 design values at this monitor with other FRM sites in the Knoxville area (Table 9- 4), shows that PM 2.5 concentrations at the Loudon monitor from 2003-2005 are higher than concentra tions at all other Knoxville-ar ea 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 sli ghtly higher than the three-year averages measured at the Francis Road and Mildred Drive sites in Knox County.

The design value for the L oudon site is significantly infl uenced by the lack of PM 2.5 data in 2003. Historically, the highest PM 2.5 concentrations for Tenness ee are observed in the third quarter. The average actual data collected fo r the Loudon site in 2004 through 2006 for the first and second quarters, if substituted for the mi ssing quarters in 2003, confirms that the site’s design value is not significantly higher than othe r Knox county monitors th at have traditionally116 experienced elevated levels of PM 2.5 (Table 9- 5) 47

.

Table 9- 4: Sorted PM 2.5 Design Values at Knoxv ille-Area FRM Monitors

AIRS ID Address County PM 2.5 Design Value in μg/m 3
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 An alysis 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 A nnual 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 quarter s 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 PM 2.5 concentrations for these monitors from 2003 through 2006 (Table 9- 6, Figure 9- 1) s uggests that annual average PM 2.5 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 PM 2.5 concentration at th e 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 wh ere some of a monitoring data is not p resent. In this case substitution is used for illustrative purpose only and helps in properly identifying the impact the lack of data has in de veloping a design value for this site.117 Table 9- 6: Comparison of Annual Average PM 2.5 Concentrations

AIRS ID Address County Number of Observations and Annual Average PM 2.5 Concentration (μg/m 3 )
2003 2004 2005 2006
# Obs. PM 2.5 # Obs. PM 2.5 # Obs. PM 2.5 # Obs. PM 2.5 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 PM 2.5 Concentrations

As discussed in Section 8.0, the attainment test for the Knoxvill e-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 th e 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 SO 4 NO 3

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 K noxville-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 PM 2.5 in the Knoxville area consis ts 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 th e Loudon monitors will attain the annual PM 2.5 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. SO 2 : 42,188 tons (actual), 36,729 tons (typical)

NO X : 17,909 tons (actual), 15,592 tons (typical) SO 2 : 8,657 tons** NO X : 2,078 tons** SO 2 : 28,072 tons NO X : 13,514 tons

TVA Kingston Fossil Plant Year-round operation of existing SCRs for CAIR compliance, beginning in 2009. NO X : 26,089 tons (actual), 25,678 tons (typical) NO X : 3,238 tons** 22,440 tons

* Data source: EGUs - ASIP 2002 actual and typical emissions inventories, ASIP 2009 emi ssions inventory. Change in emissions from 2002 to 2009 is calculated as (2009 emissi ons) – (2002 typical emissions)120Table 9- 9: Qualitative Weighting of Evidence (Not Including Modeled Attainment Demonstration)AnalysisData SourceKey Assumptions andOutcomesQualitative WeightingSupports Attainment in2009?Air Quality Monitoring DataFRM monitoring datafor Knoxville,Tennessee area.Downward trend in ambient PM2.5levels from 1999 to 2006. Designvalue at the controlling monitordecreased by about 25% between1999-2001 and 2004-2006.Monitoring data is collected perEPA specifications and isconsidered highly reliable.High weighting – monitoringdata shows downward trend inPM2.5emissions, consistent withknown reductions. Yes.1999-2006 SO2Emissionsfrom TVA Bull Run andKingston Fossil Plants,Statewide Utility SO2Emissions in Tennessee,Regional Utility SO2EmissionsAcid Rain Programmonitoring data from1999 to 2006.Data is based on continuousemissions monitoring for ARPcompliance and is considered tobe valid and highly reliable.High weighting – comparison ofemission trends with ambientPM2.5monitoring suggests astrong relationship betweendeclining SO2emissions andimprovements in ambient PM2.5between 1999 and 2006. YesProjected Emission Controlsat TVA Bull Run Fossil PlantTVA-stated constructionschedule, visualconfirmation of start ofconstruction.Significant reduction in SO2emissions by 2009. Physicalconstruction of the scrubber isunderway, analysis assumescompletion. Startup of the wetscrubber at this facility isexpected to occur December2008. The emission inventoryprojects that SO2emissions fromthis source will be reduced from36,729 tons/year (2002 typicalemissions basis) to 8,657tons/year in 2009.High weighting – Physicalconstruction demonstrates alarge capital investment inemission controls and makesprojected emission reductionshighly likely. Yes121Table 9- 9 (Continued)AnalysisData SourceKey Assumptions and OutcomesQualitative WeightingSupports Attainment in2009?CAIR Modeling ResultsCAIR Final Rule andassociated technicalsupport documentsCAIR modeling results showimprovement in ambient PM2.5,while predicting that Knoxvillearea will remain nonattainment in2009.Low to medium weighting – CAIRmodeling shows a change in ambientPM2.5due to SO2controls on electricutilities, but CAIR modeling is basedon a different year (2010). CAIRmodeling also indicates that PM2.5design value in 2010 will be higherthan is currently indicated byambient monitoring in the Knoxvillearea.CAIR modeling resultstaken by themselves,without ambientmonitoring data, would notsupport attainment in 2009.CAIR results do support anexpected decline inambient PM2.5levels asSO2emission reductionsbecome effective.Other SO2EmissionInventory ChangesVISTAS/ASIP Base G2Emission InventorySmall growth in area source SO2emissions is offset by eliminationof most SO2emissions frommobile sources between 2002 and2009. Point sources are stillresponsible for most SO2emissionsin 2009.Low to medium weighting – mobileand area source emissions are a smallfraction of total SO2emissionsinventory. SO2reductions frommobile sources may have a positiveimpact on attainment in high-trafficareas. YesPM2.5Emission InventoryChangesVISTAS/ASIP Base G2Emission InventorySome reductions from nonroad andonroad mobile sources are offsetby gains from area and pointsources. Small overall increase indirect PM2.5emissions.Low weighting – direct PM2.5emissions from all source categoriesare much lower than SO2emissions.Emissions reductions from mobilesources may have a positive impactin high-traffic areas.Direct PM2.5emissionsinventory changes do notsupport 2009 attainment.However, the relativelysmall emissions changesare not sufficient tooverturn the attainmentdemonstration result whenall evidence is taken intoaccount.SO2Reductions at U. S.DOE Oak Ridge.VISTAS/ASIP Base G2Emission Inventory andfacility constructionpermit application.About 2,000 tons/year of SO2(2002 actual emissions) will beeliminated.Low weighting – emissionsreductions were considered forRACT analysis, but the impact onattainment was not quantified. Thereductions should have some degreeof positive impact on ambient PM2.5levels. These reductions were notmodeled as part of the 2009attainment demonstration. Yes.122Table 9- 9 (Continued)AnalysisData SourceKey Assumptions andOutcomesQualitative WeightingSupports Attainment in2009?SO2Reductions at TVAKingston (see Section 10.0).TVA constructionschedule, onsiteverification thatscrubber construction isunderway.Startup of scrubber for Kingstonunits 1-4 may reduce emissions in2009 if construction is finishedahead of schedule.Low weighting – startup ofscrubber is not expected beforethe end of 2009. Based onexisting construction schedule,scrubber installation is notexpected to support attainmentfor the year 2009, if constructionproceeds as scheduled. Kingstonscrubbers will providesignificant support to Knoxvilleattainment in 2010 andsubsequent years. Physicalconstruction demonstrates alarge capital investment inemission controls and makesprojected emission reductionshighly likely.No effect on 2009 attainmentbased on existingconstruction schedule.Reductions from the scrubberinstallation at TVA Kingstonwere not modeled for 2009and were not included in themodeled attainmentdemonstration. Supportsattainment in 2010 andbeyond. Scrubberinstallation would support2009 attainment if earlystartup is achieved.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 PM 2.5 NAAQS by its attainment date. As discussed in the preamble to the PM 2.5 implementation rule, the key re quirements associated with contingency measures are:

• Contingency measures must be fully adopted ru les 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 ot her control measures for the area that are not included in the control strategy for the SIP.

• The measures should provide for emission redu ctions equivalent to about one year of reductions needed for RFP, based on the ove rall 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 m easures that would not be incl uded 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. fe deral mobile source measures based on the incremental turnover of the motor vehicle fleet each year).

10.1. Contingency Measures for SO 2
Tennessee has elected to use a portion of the SO 2 emission reductions obtai ned pursuant to the Clean Air Interstate Rule (40 CFR 96 S ubparts AAA through III and TAPCR 1200-3-14-.04) to comply with the contingency plan requirements of the PM 2.5 Implementation Rule. Specifically, Tennessee will use the reductions at Units 6 th rough 9 of Tennessee Valley Authority’s Kingston Fossil Plant to comply with th e contingency plan requirements 48

.

• The CAIR rules were adopted by Tennessee a nd filed with the Secretary of State on August 10, 2006. Tennessee’s request to inco rporate 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 Ru n is projected to be complete by the end of 2008, and the sc rubber is projected to be operational throughout 20 09. The ASIP attainment modeling for th e Knoxville nonattainment area assumed that th e scrubber at Bull Run would be operational. Since Tennessee used Bull Run’s pr ojected reductions to demonstrate attainment in 2009, the Sta te may not use the same reductions as a contingency measur e. The situation for TVA’s Kingston Fossil Plant is different, as explained below.124 Implementation Plan 49 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 rules 50 and implementation of the rules is currently underway. The emission reduc tions 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 furthe r action by the State or by EPA. For the SO 2 reductions at TVA Kingston, th e 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 PM 2.5 design value for 2009 would attain the NAAQS, but th is modeling assumed that we t scrubber controls for the Kingston facility would not be in place during the attainment year. The SO 2 reductions at Kingston comply with the requirement that c ontingency measures should consist of other control measures for the area that are not incl uded in the control strategy for the SIP.

• The emission reductions in the contingency pl an provide for greater than one year of reductions needed for RFP, based on the ove rall 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: SO 2 Reductions from Contingency Measures

Actual SO 2 emissions from all source categories (area, nonroad, onroad, and point sources) in 2002 baseline year 134,218 tons

Projected SO 2 emissions from all source categories (area, nonroad, onroad, and point sources) in 2009 attainment year 93,155 tons

SO 2 reductions required from proposed contingency measures 5,866 tons 51 Projected SO 2 reductions from TVA Kingston Units 6-9 after scrubber installation 30,224 tons 52

49 Tennessee requested adoption of the CAIR ru les 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 SO 2 reductions from Units 6-9 of TVA’s Kingston Fossil Plant we re calculated from the ASIP emission inventories by (1) comparing 2002 actual emissions and 2009 emi ssions from TVA’s Bull Run Fossil Plant; (2) estimating a control efficiency for TV A Bull Run based on 2002 and 2009 emissions; (3) assuming the same control e fficiency for TVA Kingston Units 6-9 upon installation and sta rtup of the scrubber (TVA’s Kingston and Bull Run Fossil Plants will have th e same control equipment); and (4) using the TVA Kingston’s 200 2 actual emissions and the assumed control efficiency to project the 2009 emissions for Units 6-9. The results are summarized in the fo llowing table:

Actual SO 2 Emissions for TVA Bull Run in 2002 (tons) 36,729 Projected SO 2 Emissions for TVA Bull Run in 2009 (tons) 8,657 Projected SO 2 Control Efficiency for TVA Bull Run in 2009 76.4% Actual SO 2 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 SO 2 Emissions for TVA Kingston Units 6-9 (tons) 39,559125 • Direct PM 2.5 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 PM 2.5 emissions, no contingency measures are proposed for this pollutant.

Tennessee notes that the SO 2 emission reductions relied upon for contingency planning will be of greater magnitude than SO 2 or direct PM 2.5 emission reductions that could be obtained from any other source category. Tennessee al so notes that these reductions will be achieved more quickly than reductions from other source categories, si nce contingency rulemaking would need to allow a schedule of three years or more for implementa tion of equivalent measures (assuming that such equivalent reductions could be obt ained from other sources).

10.2. Contingency Measures for NOX

Contingency measures for NO X are discussed in Attachment Q of the SIP.

Projected SO 2 Control Efficiency for TVA Kingston (based on TVA Bull Run) 76.4% Projected SO 2 Emissions for TVA Kingston After Scrubber Installation (tons) 9,335 Projected SO 2 Reduction for TVA Kingston Units 6-9 After Scrubber Installation (tons) 30,224126 REASONABLE FURTHER PROGRESS

Clean Air Act §172(c)(2) requires plans for nona ttainment areas to requ ire “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 na tional ambient air quality standa rd 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, consis tent with CAA §172(c)(2), St ate Implementation Plans for PM 2.5 nonattainment areas must demonstrate r easonable further progress as provided in §51.1009(b) through (h). Paragraph (b) of that secti on states that “if the State submits to EPA an attainment demonstration and State implementati on plan for an area which demonstrates that it will attain the PM NAAQS within five years of the date of designation, th e State is not required to submit a separate RFP plan. Compliance w ith 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 no nattainment area will attain the annual PM 2.5 NAAQS within five years of designation. Ther efore, 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.