### 1 

### BEFORE THE ADMINISTRATOR UNITED STATES ENVIRONMEN TAL PROTECTION AGENCY
In the Matter of: ) ) FINAL RULE, ) AIR QUALITY DESIG NATIONS ) EPA-HQ-OAR-2008-0476; FOR THE 2008 OZONE NATIONAL ) FRL-9668-2, RIN 2060-AP37 AMBIENT AIR QUAL ITY STANDARDS, ) 77 FED. REG. 30,088 (MAY 21, 2012) ) ) ) ANDERSON COUNTY, TENNESSEE, ) BLOUNT COUNTY, TENNESSEE, and ) KNOX COUNTY, TENNESSEE ) ) Petitioners. )

SUPPLEMENTAL PETITION FOR RECONSIDERATION On July 20, 2012, purs uant to Section 307 of the Clean Air Act (“C AA”), 42 U.S.C. § 7607, Anderson County, Tennessee (“Anderson County”), Blount County, Tennessee (“Blount County”), and Knox County, Tennessee (“Knox County”) (colle ctively, “Counties”) filed a Petition for Reconsideration of the Final Rule entitled “Air Quality Designations for the 2008 Ozone National Ambient Air Quality Standards,” 77 Fed. Reg. 30,088 (May 21, 2012) (the “Final Rule”). The Counties, through the undersigned counsel, now file this Supplemental Petition for Reconsideration (the “Supplemental Petition”), which provides further technical analysis in support of the legal and technical ar guments set forth in the Counties’ Petition for Reconsideration.
INTRODUCTION EPA based its nonattainment designation for the Knoxville Combined Statistical Area (“Knoxville CSA” or “CSA”) on the violatin g Look Rock monitor in Blount County. EPA

### 2 

### Technical Support Document, Knoxville, Tennessee Area Designations for the 2008 Ozone National Ambient Air Quality Standards 16 (“TSD”). Look Rock is one of the most highly instrumented and studied ozone monitoring stations in the southeastern United States. Numerous researchers have studied Look Rock data meas ured as a part of the CASTNET and NCore monitoring programs, as well as ot her specialized measurements ma de from time to time. In addition to ozone, the CASTNET monitoring program measures an array of meteorological parameters, 1 

### and the NCore monitoring program measur es several gaseous and particulate air components. 2 

### These researchers have reported extens ively on their studies. In spite of this wealth of information, EPA took a simplistic a pproach to determining which counties in the Knoxville CSA to designate nonattainment and ignored much of what is known about the air quality of this very complex site. Conseque ntly, the rationale undergirding EPA’s designations is seriously flawed. EPA performed a number of analyses ba sed on Look Rock CAST NET data, including analyses that it concluded demonstrated that Look Rock ozone levels are influenced by both valley and regional precursor emi ssions – conditions to tally anomalous and not representative of the vast majority of the Knoxville CSA. See TSD at 13 (noting that, unlike two other Knox County sites and a high elevation site in North Carolina, Look Rock shows a “combination of . . . two signals”: “a typical ur ban pattern of ozone events in the afternoon” and “a typical high elevation site pattern ozone overn ight.”). However, desp ite EPA’s conclusion th at ozone levels at Look Rock are the result of th ese totally anomalous conditions, it used the 2009-2011 Look Rock design value exceedance of the NAAQS to designate the entirety of two counties and a portion of a third as nonattainment.

1 

### See http://epa.gov/castnet/javaweb/index.html for a description of the CASTNET program. 2 

### See http://www.epa.gov/ttnamti1/ncore/index.html for a description of the NCore program.

### 3 

### Because EPA was unaware of, or disregarde d, the wealth of information that exists regarding air quality and meteorological conditions at Look Rock, it attributed the influences it identified as “valley” impacts to Knoxville. This misconception led EPA to conclude erroneously that Knox County and northern Blount County contribute meaningfully to the exceedance of the NAAQS at Look Rock. In addition, EPA made the nonattainment desi gnation despite its beli ef that (1) without designating any of the twelve counties in the Knoxville CSA nonattainment and burdening them with specific additional lo cal emission reductions, NO X 

### and VOC emissions in the Knoxville CSA are projected to decrease significantly due to national and regional emission-reducing rules already in place; and (2) thes e national and regional emissi on reductions will result in all monitors in the Knoxville CSA bei ng well below the ozone NAAQS by 2015. While the aforementioned reductions will result from regional and national emission-reducing rules already in place, they will come at a signifi cant cost to the citizens, businesses, and local governments in the CSA. Designating the entireties of Knox and Blount Counties and a portion of Anderson County as nonattainme nt will stigmatize the Counties and make it much harder for the area to overcome current economic conditions.
TECHNICAL ANALYSIS
I. ADDITIONAL COMMENTS ON EP A’s TECHNICAL ANALYSIS OF THE KNOXVILLE CSA. In its TSD, EPA provided a list of counties in the Knoxville CSA with ozone monitors (Sevier, Blount, and Knox Counties have mu ltiple monitors) along with the 2009-2011 design values for each of those counties. TSD at 6, Table 3. EPA noted that only one county in the CSA has a design value exceeding the ozone NAAQS: Blount County. Without acknowledging the fact that Blount County has two monitors -- one attaining the NAAQS (Cades

### 4 

### Cove with a 2009-2011 design value of 68 ppb) and one exceeding the NAAQS (Look Rock with a 2009-2011 design value of 77) -- EPA conc luded that “Blount C ounty shows a violation of the 2008 ozone NAAQS, therefore this count y is included in the nonattainment area.” Id . at 6. In the Meteorology section of the TSD, EPA provided an analysis of back trajectories using the National Oceanic and Atmospheric Admini stration’s Hybrid Single Particle Lagrangian Integrated Trajectory Model (“HYSPLIT”) to evaluate the potential contribution from nearby areas. The HYSPLIT analysis was done for days that exceeded the NAAQS at the Look Rock monitor during the 2009-2011 timeframe. Id . at 10-11, Figure 3. In addition, EPA discussed (but did not present) an analys is of the predominant wind directions in the area based on an analysis of thirty years’ of ozone season (March through Oc tober) National Weather Service (“NWS”) data from the Knoxville Airport located just 12.5 miles nor th-northeast of Look Rock. As EPA points out, the predominant wind direction during this period is from the southwest and west-southwest with a no rth-northeast component. Id . at 10. The Counties provided EPA with an analysis of the NWS data for this time period, as well as the wind rose summary of that data. Letter from Michael K. Stagg to Gwendolyn Keyes-Fleming (April 5, 2012). Based on the Countie s’ analysis, disregarding the calms (27.25% of the time), the wind is fr om the northwest, north, northeast, and east less than a quarter of the time, while it is from the southeast, south, southwest, and west over three quarters of the time. None of the areas EPA chose to de signate as nonattainment are in the direction from Look Rock from which the winds dominate; th erefore, they do not meaningfully contribute to th e Look Rock monitor exceedance. In the Geography/Topography section of the of the TSD, EPA presented an analysis of wind direction data from the CA STNET monitoring site at Look Rock for the days and times

### 5 

### when the hourly average ozone exceeded 75 ppb. TSD at 13, Figure 6. Fr om this analysis, EPA erroneously drew the conclusion that there ar e “two distinct groups of high ozone events: afternoon ozone from the north to northwest (Knoxv ille) and overnight ozone from the south to southeast (regional transport).” Id . at 13. In its analysis, EPA did not mention that the local measurements of wind direction at the Look Rock CASTNET monitor have been shown by numerous researchers to be influenced by the very localized complex topography surrounding the monitoring site and to not be representative of the area-wide wind patterns. EPA also failed to mention that the local wind data it used in its analysis does not coincide with the wind direction data either from the NWS meteor ological station at the Knoxville Airport or the HYSPLIT back trajecto ries it discusses in the Meteorology section of the TSD. Clearly, EPA ignored information it had readily available to r each a conclusion that wind directions measured at Look Rock indicated that sources in K nox County, northern Blount County, and Anderson County were making a “meaningful” contribu tion to high-ozone events at Look Rock. Also in the Geography/Topography section of the TSD, EPA pr ovided a detailed analysis of ozone concentrations at a high elevation m onitor in North Carolina, the two monitors in Knox County, and the Look Rock monitor. Id. at 13, Figure 5. Based on that analysis, EPA concluded, “The Look Rock site . . . is imp acted by both downwind afternoon ozone formation from Knoxville and high elevation ozone transport. In some cases , these two processes could be affecting the Look Rock monitor simultaneously.” Id . at 13. Again, EPA ignored readily available information, reached an erroneous co nclusion, and used what it considers a totally anomalous situation to designate the entiretie s of Knox and Blount Counties and a portion of Anderson County as nonattainment.

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### II. AN ANALYSIS OF HIGH-OZONE EVENTS AT LOOK ROCK BASED ON WHAT IS KNOWN FROM EXTENSIVE MONITORING AND RESEARCH. As mentioned above, air quality at Look Rock has been studied extensively by various researchers through the years. These studies ha ve demonstrated that localized wind direction measurements at Look Rock do not coincide with area-wide wind patterns. To explain this inconsistency, many researchers rely on the localized wind phenomenon identified by Roger Tanner and others. Roger L. Tanner, Solomon T. Bairai, Kenneth J. Olszyna, Myra L. Valente, and Ralph J. Valente, Diurnal Patterns in PM2.5 Mass and Composition at a Background, Complex Terrain Site, 39 Atmospheric Environmen t 3872 (2005) (hereinafter, “Tanner”); see also Kenneth J. Olszyna, Elizabeth M. Bailey, Romualdas Simonaitis, and James F. Meagher, O 3 

### and NO y 

### Relationships at a Rural Site , 99 J. of Geophysical Research 14,557 (1994) (hereinafter, “Olszyna”); Roger L. Ta nner, Patricia Brewer, Ivar Tombach, Scott Reynolds, Eric Edgerton, Ben Hartsell, and Jim Renfro, Development and Analysis of an Hourly, Chemically Speciated Database for PM 2.5 

### Aerosols in the Southeastern US, Journal of Air and Waste Management Association (submitte d June 18, 2008). Tanner explains that
as expected, the temperature maxima tr ail solar radiation by about 2 hours. Nocturnal boundary breakup begins in the 0500–0600 (EST) timeframe, and boundary layer growth reaches the altitude of the site (about 825m MSL) in the 0800–1000 (EST) timeframe. In the absence of frontal boundaries, extensive cloudiness and/or prec ipitation, this is nearly alwa ys accompanied by a shift in wind direction from southerly (down-sl ope) to the west and north direction (up-slope, up-Valley), along with a mo dest increase in wind velocity. On average, the wind direction drifts toward the south and west during the afternoon hours and collapses to southerl y or southeasterly again around sunset.
Tanner at 3872.

### 7 

### This change in wind direction apparently is due to the orientation of the Look Rock ridge and the prevailing valley airflow. As elevation increases above the valley floor toward the tops of the ridges that define the sides of the valley, wind direction rotates to a lign with winds aloft. Winds aloft are more likely to have a westerly component which causes the wind direction at Look Rock to rotate toward an up-slope configuration. Late in the day, especially in summer, the sun angle is such that the west-facing slope of the Look Rock ridge is heated more than the opposite side which by that time is in shadow . This differential heating warms the slope and the air above it accelerating the up- slope airflow. When the solar heating stops, the western side of the slope cools quickly and th e atmosphere begins to stabiliz e. The stable layer cuts off Look Rock from the westerly ai rflow aloft, and the cooling allows for the formation of a down-slope wind component.
In other words, the local wind direction measurements made at Look Rock are not an indication of the direction from which air ma sses arrive at the Look Rock monitor, but are the result of air flow “up-slope, up-Valley” during the daytime and “down-slope” during the nighttime. It, therefore, is erroneous for EPA to conclude that “afternoon ozone” is from Knoxville when the local CASTNET monitor shows wind direction measurements from the north. Rather, these “north” measuremen ts result from a daily localized “up-slope” wind direction.
To cast additional light on this localized wind direction phenomenon described by Tanner, the Counties examined data from the CASTNET monitor as well as from the NCore monitor, both located at Look Rock. While the CASTNET monitor measures ozone and numerous meteorological conditions (wind sp eed, wind direction, sola r radiation, etc.),

### 8 

### the NCore monitoring system measures the concentr ation of a number of gaseous and particulate air components, including NO, NO 2 

### , total oxides of nitrogen (NO Y 

### ), CO, PM 2.5 

### , and black carbon. Of the twenty-three events during the 2009-2011 ozone seasons when the maximum 8-hour average ozone concentration at Look Rock exceeded 75 ppb, practically complete sets of both CASTNET and NCore data exist for nine of the events. 3 

### These nine events should well represent the twenty-three total ev ents because they occur in the early, middle, and late parts of the ozone season; in each of the three years used to calculate the design value; and on days when the HYSPLIT back trajectories were from practi cally every compass direction. Tables 1 and 2 in Appendix 1 provide a tabulation of the pertinent data used in the Counties’ analysis, while Appendix 2 contains the back trajectories used. A close inspection of the wind direction data from the Look Rock CASTNET monitor and the HYSPLIT back trajectory data reveals th at during the daytime hours, the wind direction measured at the Look Rock CASTNET monitor rare ly coincided with the direction from which the parcels of air were computed by HYSPLIT to be arriving at Look Rock. For instance, on April 15, 2010, the Look Rock CASTNET monitor m easured wind directions from the north and northwest from 1000 through 1900 EST (a condition co nsistent with the explanation provided by Tanner as well as other researchers), while th e back trajectories indicated no air flow to the Look Rock area from that direction. Rather, back trajectories all day were from the south and southeast. Based on EPA’s analysis ( see TSD at 13-15), which relied primarily on the wind direction measurements at Look Rock, EPA would have concluded that the high ozone concentrations during the daytime hours of April 15, 2010, resulted from emissions in

3 

### An “event” often spans two calendar days.

### 9 

### the Knoxville, north Blount, and Anderson Count y areas. However, as noted above, the afternoon wind direction da ta at Look Rock actually measures the change in local winds from up-slope to down-slope as the day progresses, not the actual direction from which the winds arrived. Thus, EPA’s conclusion that emissions came from areas north of Look Rock in this case is erroneous. Likewise, on June 25, 2009 (again, consiste nt with the Tanner description of the meteorology of Look Rock), according to the wind direction measurements made at Look Rock at 1900 (as solar radiation approached zero), the wind began shifting to the east and southeast after having been from the north and northwest since 1000 EST. However, an examination of the back trajectories for this day indicates little change in the wind direction all day, which was from the north to northeast. Th is inconsistency again shows that Look Rock’s wind direction monitor actually measures the da ily cycle of up-slope and down-slope airflows, not actual area-wide wind direct ion. Consequently, the wind direc tion data at Look Rock cannot be relied upon to reach conclusi ons about the sources of precur sor emissions that create high ozone events at Look Rock. To further substantiate the view that Ta nner and other research ers have of diurnal meteorology at Look Rock, the Counties performed an analysis of all the wind direction data from the Look Rock CASTNET monitor for the 2009-2011 timeframe. For this analysis, wind direction data for each compass quadrant (i.e., east -- 45 o 

### to 135 o 

### , south – 135 o 

### to 225 o 

### , west 225 o


### to 315 o 

### , and north 315 o 

### to 45 o 

### ) was correlated with solar radiat ion. Solar radiation was chosen because Tanner and others have observed that wind direction seems to change in the early morning as the sun rises and in the late afternoon when the sun sets. Tann er at 3872. Table 3 in Appendix 1 summarizes the results of this analysis.

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### This analysis demonstrates that wind direc tions from the north and west tend to dominate during the daylight hours (higher average solar ra diation), while wind directions from the east and south tend to dominate during nighttime hours (lower average solar radiation). The pattern is similar for both the periods of time when th e ozone level exceeds 75 ppb and when it does not. However, the predominance of north and west in the daytime and east an d south in the nighttime is much more pronounced when the ozone concentr ation exceeds 75 ppb. Th is too is consistent with the observation made by Tanner that “i n the absence of frontal boundaries, extensive cloudiness and/ or precipitation,” which are the ideal conditions for ozone production, “the wind shifts direction from southerly (down-slope) to the west and north direction (up-slope, up-Valley) as the sun rises and drifts toward the south and west during the afternoon hours and changes to southerly or south easterly around sunset.” Tanner at 3872. EPA’s reliance primarily on the CASTNET wind direction data from Look Rock to infer th at northern Blount County, Knox County, and Tennessee Valley Authority’s (“ TVA”) Bull Run Power Plant are meaningful sources of Look Rock ozone pr ecursors is seriously flawed. 4 

### The Counties conducted an in-depth analysis of the HYSPLIT back trajectories during each of the twenty-three events when the maximum 24-hour ozone concentration exceeded 75 ppb. These back trajectories are shown in Appendix 2, and the in -depth anal ysis is summarized in Table 4 in Appendix 1. As can be seen by this an alysis, during only about a third of the episodes (eight out of twenty-three) di d the back trajectory pass across the densely populated portions of Knox C ounty where emissions of NO X 

### and VOCs from Knox County could have made any contribution to ozone concentrations at Look Rock. See TSD at 10, Figure 2 (showing the “densely popul ated portions of Knox County”).

4 

### As described below, TVA has operated its Bull Run Po wer Plant with selective cat alytic reduction (“SCR”) NOx removal technology (with a 90-95% control efficiency) since 2004.

### 11 

### In addition to the aforementioned analysis conducted by the Counties, TVA performed a detailed statistical analysis of the same twen ty-three high ozone events and concluded that 65% of the Look Rock high ozone events are not a ssociated with or signi ficantly impacted by Knoxville-area emissions. See Stephen F. Mueller, Cluster Analysis of Look Rock High Ozone Events and Related Air Parcel Trajectories for 2009-2011 (hereinafter, “Mueller”) (attached as Appendix 3). 5 

### The conclusions of TVA and the C ounties are consistent and strongly demonstrate that Knox County did not contribute in a meaningful way to high ozone events at Look Rock during the 2009-2011 time period.

III. THE COUNTIES’ ANALYSIS OF EACH HIGH-OZONE EVENT. As noted above, the nine events for which there is complete data from both CASTNET and NCore should well represent the twenty-t hree events in the 200 9-2011 timeframe when the maximum 8-hour ozone concentration at Look Rock exceeded 75 ppb. Consequently, the Counties have conducted an in-depth analys is of these nine events, comparing CASTNET and NCore data with several HY SPLIT back trajectories for the period during the event when the hourly ozone concentration exceeded 75 ppb. Table 4 in Appendix 1 summarizes this detailed analysis. For the Counties’ analysis, the photochemical age of the air mass was used to determine the distance from which the NO X 

### (NO and NO 2 

### ) emissions that co ntributed to the ozone exceedances must have come. Photochemical age has been used extensivel y by researchers to describe the average age of NO X 

### in studies of ozone fo rmation from both point and nonpoint sources. Menachem Luria, Ralph J. Valente, Solomon Bair ai, William J. Parkhurst, and Roger L. Tanner,

5 

### Available at http://www.tva.com/environmen t/pdf/Cluster_Analysis.pdf.

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### Nighttime Chemistry in the Houston Urban Plume , 42 Atmospheric Envi ronment 7544 (2008); Menchem Luria, Ralph J. Valente, Solomon Bairai, Willi am J. Parkhu rst, and Roge r L. Tanner, Airborne Study of Ozone Formation over Dallas, Texas , 42 Atmospheric Environment 6951 (2008) (hereinafter, “Luria”); J. Domm en, A.S.H. Prevot, A.M. Hering, T. Stafflebach, G.L. Kok, and R.D. Schillawski, Photochemical Production and Aging of an Urban Air Mass , 104 Journal of Geophysical Research pages 5493 (1999). Phot ochemical age is computed by dividing the concentration of non-NO X 

### (NO + NO 2 

### ), or more highly oxidized fo rms of nitrogen in an air mass, by the total concentration of all odd-nitrogen oxidized forms. It is normally identified as
NO Z 

### /NO Y 

### . NO Z 

### /NO Y 

### varies from 0.0 to 1.0 with the older photochemical ages being nearer 1.0. A photochemical age near 0 would indicate that al l, or almost all, of the oxidized nitrogen in the air mass is present as NO X 

### , while a photochemical age of 1.0, would indicate that none of the oxidized nitrogen in the air mass is present as NO X. 

### Olszyna has found that there is little additional ozone formation in an air mass w ith a photochemical age of 0.7 or greater. Olszyna at 14,561. Further, a lower photochemical age gene rally implies that near by sources are more influential, while a higher photochemical age ge nerally implies that sour ces farther away have had more impact. See Mueller at 5-6. Therefore, for this analysis, air ma sses arriving at Look Rock with average photochemical ages below 0.5 were considered young, still capable of pr oducing quite a lot of ozone, and the sources of NO X 

### in the air mass being nearby; air masses with photochemical ages of 0.5 to 0.7 were considered moderately age d, still capable of producing some ozone, and the sources of NO X 

### being some distance away; and air ma sses with photochemical ages above 0.7 were considered well-age d, no longer producing much ozone, and the sources of NO X 

### being a long distance away.

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### In addition to photochemical age, the concentr ations of CO from th e NCore data set were used as indicators of the source of ozone precurs or emissions. Emissions from mobile sources are relatively high in CO, while em issions from most industrial point sources, certainly electric generating units (“EGUs”), are re latively low in CO. Luria at 6598. Therefore, an air mass arriving at Look Rock with a relatively high conc entration of CO would indicate that the sources of the ozone precursors were heavily influenc ed by mobile sources, while air masses with relatively low CO concentrations would be more indicative of ozone precursor source regions with a low density of mobile sources. Air masses predominated by mobile source emissions have been shown to have CO c oncentrations in excess of 140 ppb. Luria at 6953. An analysis of all the CO data available for 2009- 2011 at Look Rock (not just the data for the nine events, but the entire data set for the three-year period) indicates the average CO concentration to be 180 ppb with a standard deviation of 50 ppb. Ther efore, a CO concentration at Look Rock of 0-130 ppb was considered low and indicative of a small influence by mobile sources, a CO concentration of 131-230 wa s considered high and indicative of substantial influence from mobile sources, and a CO concentration greate r than 230 was considered extremely high and strongly influenced by mobile sources.
A

. June 25-26, 2009. During the high-ozone event on June 25-26, 2009, the photochemical ages of the air masses arriving at Look Rock were genera lly in the old range (ages ranged from 0.69 to 0.92 with an average of 0.78), and the CO concentr ations were moderately high (CO ranged from 134 to 207 ppb with an average of 161 ppb). The back trajectories were generally from the northeast to north during the period. Based on this analys is, it appears likely that the sources of the NO X 

### emissions that created the high ozone even t were from a combination of mobile and

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### point sources in the valley northeast of Look Rock, potentially from as far away as the Tri-Cities area, as well as areas in Ha mblen and Jefferson Counties along the Interstate 81 corridor, in Cocke County along the Interstate 40 corridor , and in western Sevier County and eastern Knox County. With a photochemical age averaging 0.78, it is not likely th at substantial ozone was produced from nearby NO X 

### emissions in Blount County. B. April 2-3, 2010. During the high-ozone event on April 2-3, 2010, the photochemical ages of the air masses arriving at Look Rock were generally in the old range (ages ranged from 0.47 to 0.93 with an average of 0.81), and the CO concentrations we re extremely high (CO ranged from 256 to 327 ppb with an average of 278 ppb). The back traj ectories generally were from the south during the period. Based on this analysis, it a ppears likely th at the sources of the NO X 

### emissions that created the high ozone event were primarily the result of mobile sources. Examining the back trajectories strongly suggests th ese mobile source emissions em anated from north Georgia, possibly as far away as the Atlanta area. Becau se the air masses arriving at Look Rock during this event should not have received fresh NO X 

### emissions during the last twelve hours prior to arriving at Look Rock (because they basically pa ssed over the remote, forested areas of north Georgia, southeast Tennessee, and southwestern North Carolina), and because the photochemical ages of the air masses generally were in the old range, one can conclude that ozone may be transported to a site like L ook Rock from vast distances. C. April 13-14, 2010. During the high-ozone ev ent on April 13 and the morning of April 14, 2010, the photochemical ages of the air masses arriving at Look Rock averaged in the moderate range (ages ranged from 0.08 to 0.91 with an average of 0.60), and the CO concentrations were high

### 15 

### (CO ranged from 189 to 240 ppb with an average of 221 ppb). With regard to the photochemical age, the air masses arriving at Look Rock were generally old, except for the period 1900 – 2100 when NO X 

### levels increased dramatically. This dramatic increase in NO X 

### levels coincided with sundown and a slight incr ease in CO levels. These changes suggest impacts from nearby mobile sources. The back trajectories were generally from the south and west during the period. Specifically, the air mass arriving at Look Rock during the hour when the NO X 

### levels were the highest and the photochemical age the lowest spent the preceding th ree hours over extreme southeastern Loudon County and extreme southweste rn Blount County. Based on this analysis, it appears likely that the sources of the NO X 

### emissions that created the high ozone event were primarily the result of mobile sources southwest a nd west of Look Rock, particularly in Monroe County and along the I-75 co rridor in McMinn County. D. April 14, 2010. During the high-ozone event on the afte rnoon and evening of April 14, 2010, the photochemical ages of the air masses arriving at L ook Rock were generally in the old range (ages ranged from 0.50 to 0.88 with an average of 0.80), and the CO c oncentrations were extremely high (CO ranged from 224 to 242 p pb with an average of 233 ppb). The air masses arriving at Look Rock during the 1700 – 2000 timef rame had slightly higher NO X 

### levels and younger photochemical ages. Again, this increase in NO X 

### levels coincided with sundown and, in this case, a dramatic shift in local wi nd direction. Since there was no change in the direction of the back trajectories, it is apparent that this sh ift in wind direction was due to the localized phenomenon identified by Tanner and is related to a shift in winds from up-slope to down-slope as the boundary layer settled below the Look Rock monitor. The back trajectories were generally from the south to the southwest duri ng the entire period. Based on this analysis,

### 16 

### it appears likely that the sources of the NO X 

### emissions that created the high-ozone event were primarily the result of mobile sources s outh and southwest of Look Rock, particularly in Hamilton, McMinn, and Monroe Counties. E. April 15, 2010. During the high-ozone event on April 15, 2010, th e photochemical ages of the air masses arriving at Look Rock were generally in the mo derate range (ages ranged from 0.32 to 0.85 with an average of 0.66), and the CO concentrations were in the high range (CO ranged from 199 to 248 ppb with an average of 217 pp b). As during some of the aforementioned events, the air masses arriving at Look Rock during 1900 – 2300 timeframe had slightly higher NO X 

### levels and younger photochemical ages. Again, this increase in NO X 

### levels coincided with sundown and a dramatic shift in local wind direction. As wi th the April 14 event, there was no change in the direction of the back trajectorie s during this period; therefore, it is apparent that this localized shift in wind direction was due to a shift in winds from up-slope to down-slope as the boundary layer settled below the Look Rock monitor. The back trajectories were generally from the southwest during the entire period. Based on this analysis, it appears li kely that the sources of the NO X 

### emissions that created the high-ozone ev ent were primarily the result of mobile sources southwest of Look Rock, particularly along the I-75 corridor in Hamilton, Bradley, McMinn, and Monroe Counties. F. May 5-6, 2010. During the high-ozone event on May 5 and the morning of May 6, 2010, the photochemical ages of the air masses arriving at Look Rock were generally in the moderate range (ages ranged from 0.59 to 0.72 with an aver age of 0.63), and the CO concentrations were in the high range (CO ranged from 190 to 213 ppb with an average of 199 ppb).

### 17 

### The back trajectories were generally from the south and southwest durin g the entire period and did not cross heavily populated areas or major transportation corridors afte r crossing over the I-75 corridor in north Geor gia eighteen to twenty-four hours before the high-ozone event. Based on this analysis, it appears likely that the sources of the NO X 

### emissions that created the high-ozone event were primarily the resu lt of mobile sources southwest of Look Rock, possibly in the north Georgia area. G. May 6-7, 2010. During the high-ozone event on the afternoon of May 6 and May 7, 2010, the photochemical ages of the air masses arriving at Look Rock were generally in the moderate range (ages ranged from 0.13 to 0.90 with an aver age of 0.60), and the CO concentrations were in the high range (CO ranged from 202 to 228 ppb w ith an average of 213 ppb). As with some of the aforementioned events, the NO X 

### levels increased and the photochemical age declined at sundown as the local winds shifted from up-slope to down-slope. The back trajectories during the event began primarily from the south and shifted during the event toward the west and northwest. Based on this an alysis, it appears likely th at the sources of the NO X 

### emissions that created the high-ozone event were primarily the result of mobile sources from the I-75 corridor southwest of Look Rock and from Monr oe, Loudon, southern Knox, and northwestern Blount Counties. H. October 11-12, 2010. During the high-ozone event on October 11-12, 2010, the photochemical ages of the air masses arriving at Look Rock were generally ol d (ages ranged from 0.78 to 0.88 with an average of 0.82), and the CO concentrations were in the high range (CO ranged from 158 to 169 ppb with an average of 164 ppb). The back trajecto ries during the event were generally from

### 18 

### the southwest during the entire even t. Based on this analysis, it a ppears likely that the sources of the NO X 

### emissions that created the high-ozone event we re primarily the result of mobile sources from Bradley, McMinn, and Monroe Counties al ong the I-75 corridor and potentially from the Chattanooga and North Georgia areas. I. August 3, 2011. During the high-ozone event on August 3, 2011, th e photochemical ages of the air masses arriving at Look Rock were gene rally old (ages ranged from 0.71 to 0.90 with an average of 0.83), and the CO concentrations were extremel y high – some of the highest measured in the 2009-2011 timeframe (CO ranged from 454 to 567 ppb with an average of 332 ppb). The back trajectories during the event were genera lly from the southwest during the entire event. Based on this analysis it appears likely that the sources of the NO X 

### emissions that created the high ozone event were primarily the result of mobile sources from Bradley, McMinn, and Monroe Counties along the I-75 corridor and potentially from the Chattanooga area or farther south. In summary, the back trajectory information for these nine events is consistent with the data from the NWS meteorological monitori ng station at the Knoxville Airport in that the predominant direction from which air masses arri ve at Look Rock is the south and southwest. Generally, the photochemical age of the air masses arriving at Look Rock is in the old range, although during several of the nine events as the sun set and localized wind directions (measured at Look Rock) shifted from up-slope to down-slope, NO X 

### levels increased and photochemical age decreased. During those period s, however, wind directions base d on back trajectories were normally not from Knox, northern Blount, or Anders on Counties. Also, CO levels were generally

### 19 

### high, which indicates that the s ources of ozone precursors during these nine high ozone events were likely primarily mobile sources as opposed to industrial point sources.

IV. CSAPR and 2008 STANDARD MODELING. In her September 22, 2011 memorandum to EP A Regional Air Division Directors, Assistant Administrator Gina McCarthy stat es that “EPA’s mode ling indicates that approximately half of the 52 ar eas [not attaining the 2008 sta ndard] would attain the 0.075 ppm standard by 2015 (the expected dead line for Marginal areas) as a result of the emission-reducing rules already in place.” Memorandum from Gina McCarthy to Ai r Division Directors (Sept. 22, 2011) 2 (“McCarthy Mem o.”). Later in that same memorandum, Ms. McCarthy lists some of the “emission-reducing rules” to which her earlier statement refers, such as the Cross-State Air Pollution Rule (“CSAPR”), 6 

### the Portland Cement Rule, the Light and Heavy Duty Vehicle standards, the Boiler Maximum Achievable Control Technology, the Mercury and Air Toxics Standard s for power plants, the New S ource Performance Standards for Commercial Incinerators/Solid Waste Incinerators and the Oil/Gas sector, and the Tier 3 vehicle and fuel standards. Id . She notes, “These federal actions w ill ensure steady forward progress to clean up the nation’s air and protect the health of American families, while minimizing and in many cases eliminating the need for states to use their scarce resources on local actions.” Id

. In support of these statements, Ms. McCart hy refers to modeling described in the Spreadsheet projecting the hypothetical 8- hour ozone nonattainment areas for the 75 ppb NAAQS to 2015 to estimate the number of margi nal nonattainment areas that are expected to

6 

### In light of several petitions for review of CSAPR, the U.S. Appeals Court for the D.C. Circuit stayed CSAPR on December 30, 2011, and ordered that the Clean Air Interstate Rule (“CAIR”) remain in effect pending resolution of the petitions for review. On Augu st 21, 2012, the D.C. Circuit v acated CSAPR and reinstated CAIR. See Order, EME Homer City Generation, L.P. v. EPA , No. 11-1302 (D.C. Cir. Aug. 21, 2012).

### 20 

### attain the NAAQS by thei r attainment date of 2015 , (EPA-HQ-OAR-2010-0885-0064). In that document, EPA describes how it used CSAPR m odeling to make projections for the ozone monitors across the country for 2015. Ba sically, the approach projects the 2008

‐ 2010 ozone design values to 2015 using the modeled average pe rcent per year change in ozone from the 2014 CSAPR final rule modeling (i.e ., the CSAPR remedy case). The CSAPR modeling used a base year of 2005 and a future year of 2014 – a ni ne-year projection. EPA pro-rated the percent average annual ozone changes over the nine-year period to estimate the expected change in ozone between the 2008

‐ 2010 period and 2015, the year Marginal nonattainment counties must attain the 2008 standard. Because there are five years between 2010 a nd 2015, EPA used 5/9ths of the modeled percent change (between 2005 a nd 2014) and applied this pro-rated factor to the 2008-2010 design value for each monitor. The CSAPR modeling is described in detail in Air Quality Modeling Final Rule Technical Support Document , US EPA, OAQPS, Ai r Quality Assessment Division, Research Triangle Park, NC (June 2011). EPA used 2005 as the base year for the CSAPR modeling because it was the most current year for which EPA had a complete National Emissions Inventory (“NEI”) available. Id . at 2. In addition to the 2005 ba se case, three future scenarios were modeled – 2012 base case, 2014 base case, and 2014 remedy. Id . The 2014 remedy case contained the emission reductions resulting from CSAPR plus all the other “emission-reducing rules” expected to come into effect between 2012 and 2014. Id . at 50 n.55. In contrast, the other future scenarios were based on just the othe r “emission-reducing rules” coming into effect between 2012 and 2014. Id

. The details of the emission inventories used in creating the emissions inputs for the modeling are described in Emissions Inventory Final Rule Technical Support Document , US

### 21 

### EPA, OAQPS, Air Quality Assessment Division, Research Triangle Park, NC (June 28, 2011). According to this document, emission inputs fo r the 2012 and 2014 scenarios generally take into account “Federal and State measures already promulgated before emissions processing on the Transport Rule [CSAPR] began in December, 2010.” Id . at 68. With respect to electric generating unit (“EGU”) emissions, the docu ment states that “the emissions reflect state rules and federal consent decrees through December 1, 2010.” Id . For mobile sources, “all national measures for which data were availabl e at the time of the modeling” were included. Id. However, for non-EGU point sour ces and nonpoint sources, local control programs that might have been necessary for areas to attain the 1997 PM 2.5 

### annual NAAQS, the 2006 PM 2.5 

### 24-hour NAAQS, and the 1997 ozone NAAQS were generally not included in the future scenarios. Id. The Emissions Inventory Final Rule Technical Support Document’s “Emissions Summaries” 7 

### spreadsheet provides the specific emissi on levels used in the CSAPR modeling by type of emission source and by state. The Coun ties used the values in this spreadsheet to perform the technical analysis described below. Table 5 in Appendix 1 summarizes the NO X 

### and VOC emission levels used in the modeling along with the percentage of emission reductions by emission source type for Tennessee. As can be seen, emissions of ozone precursors are projected to drastically decrease across Tennessee between 2005 and 2014 due to nation-wide “emission-reducing rules” includ ed in the CSAPR modeling. NO X 

### emissions are projected to decrease by about 43% in that timeframe while VOC emissions are projected to decrease by about 23%.

7 

### Available at http://www.epa.gov/airtransport/techinfo.html.

### 22 

### Using an approach similar to that ta ken by EPA for comparison with the 2008 ozone NAAQS, the Counties extrapolated the CSAPR modeling for 2014 to 2015 8 

### by taking the average annual 2005 to 2014 emission reduction percentages for Tennessee listed in Table 5 in Appendix 1 and applying th em to the corresponding 2008 emission s for the twelve counties in the Knoxville CSA. In other words, the C ounties divided the 2005 to 2014 emission reduction percentages in Table 5 in Appe ndix 1 by nine (for the nine-y ear period between 2005 and 2014) and multiplied the resulting average annual em ission reduction percentage by seven (for the seven years between 2008 and 2015). The county-level emissions us ed in the analysis are from the 2008 NEI, v2. 9 

### These 2008 emission levels vary so mewhat from the emission levels referenced by EPA in its attachment to Gwendolyn Keyes Fleming’s December 8, 2011 letter to Governor Bill Haslam (concerning EPA’s intenti ons to designate certai n counties in Tennessee as nonattainment) due to EPA’s use of an earlier version (v1.5) of the 2008 NEI. Version 1.5 is no longer available. Tables 6 and 7 in Appendix 1 summarize the results of the Counties’ analysis of the projected NO x 

### and VOC reductions in the CSA from 2008-2015. As can be seen in Tables 6 and 7 in Appe ndix 1, based on this analysis, emissions of NO X 

### and VOCs are projected by EPA to drastically decrease in th e twelve counties making up the Knoxville CSA. Of note is that NO X 

### emissions are projected to decrease by about 32% in the three counties EPA has designated as nonattai nment (Knox, Blount, and Anderson), while VOC emissions are projected to decrease by about 16%. These are significant reductions and will come at a cost to the citizens a nd businesses in the Knoxville area.

8 

### See pages 20-21 supra , describing the approach used in Spreadsheet projecting the hypothetical 8-hour ozone nonattainment areas for the 75 ppb NAAQS to 2015 to estimate the number of marginal nonattainment areas that are expected to attain the NAAQS by their attainment date of 2015 , (EPA-HQ-OAR-2010-0885-0064)). 9 

### Available at http://www.epa.gov/ttn/chief/net/2008inventory.html.

### 23 

### With regard to EGU emissions in the K noxville CSA, TVA has al ready significantly reduced NO X 

### emissions at both its Bull Run Power Pl ant in Anderson Count y and its Kingston Power Plant in Roane County. NO X 

### emissions have been reduced at Bull Run by about 89% on an annual basis, while annual emissions have b een reduced by about 91% at Kingston. In both cases these reductions exceed the 55.7% reduction the Counties assumed in their analysis. These reductions have been achieved by adding SCR to a ll units at both plants. Table 8 in Appendix 1 summarizes the NO X 

### emissions levels and rates for Bull Run Power Plant for the last seven years, and Table 9 in Appendix 1 summarizes the emission levels and rates for Kingston. Note that the annual NO x 

### emission rates have decreased at Bull Run and Kingston by about 80% and 74%, respectively. Neither NO x 

### emissions nor the NO x 

### emission rate from the Bull Run or Kingston Power Plants is expected to increase through the foreseeable future due to (1) the continued effect of CAIR; 10 

### (2) the requirements of a federa lly enforceable consent decree ( See Consent Decree, Alabama v. TVA , No. 3:11-cv-00170 (E. D. Tenn. June 6, 2011) (requiring TVA to, inter alia , cap system-wide NO x 

### emissions through 2018 and each year thereafter); and (3) TVA’s own commitments to reduce its load grow th and install emission reduction equipment and new technology to control emissions from ove r 80% of fossil generation in the next ten years. ( See “2010 Review of TVA’s 2008 Environmental Policy” 8, attached hereto as Appendix 4). Table 10 in Appendix 1 summarizes the resu lts of the modeling done for CSAPR and the extrapolations made by EPA for the 2008 ozone NAAQS for the Knoxville CSA from Spreadsheet projecting the hypothetical 8- hour ozone nonattainment areas for the 75 ppb NAAQS to 2015 to estimate the number of margi nal nonattainment areas that are expected to

10 

### On August 21, 2012, the D.C. Circu it vacated CSAPR and reinstated CAIR. See Order, EME Homer City Generation, L.P. v. EPA , No. 11-1302 (D.C. Cir. Aug. 21, 2012).

### 24 

### attain the NAAQS by thei r attainment date of 2015 , (EPA-HQ-OAR-2010-0885-0064). These ozone levels represent the improvements to air quality projected to result from the emission reductions EPA projects will be made in the Knoxv ille area, as well as across the region. As can be seen, all nine of the monitors in the ar ea are projected to be well below the 2008 ozone NAAQS by 2014 and 2015, including Look Rock, based on EPA’s modeling. As described above and mentioned in the McCarthy Memo, thes e monitors are projected to be 7-16% below the NAAQS by 2015 due to “emission-reducing rules al ready in place” and without “the need for states to use their scarce re sources on local actions.”
CONCLUSION Only one monitor out of nine in the Knoxville CSA had a 2009-2011 design value that exceeded the NAAQS. That monitor is located at Look Rock in Blount County. Blount County has a second monitor located just nine miles fr om Look Rock -- the Cade s Cove monitor -- with a design value well below the NAAQS. As noted above, Look Rock is one of th e most instrumented and studied ozone monitoring stations in the southe astern United States. Howeve r, instead of re lying on readily available (and extensive) Look Ro ck research, EPA took a simplis tic approach to determining which counties in the Knoxville CSA to designat e nonattainment and ignored much of what is known about the air quality and meteorology of this very complex Look Rock site. EPA itself concluded in the TSD that high-ozone events at Look Rock were due to totally anomalous conditions, not repres entative of the vast major ity of the Knoxville CSA. Nonetheless, it used the 2009-2011 Look Rock design value exceedance of the NAAQS to designate the entirety of two counties and a portion of a third as nonattainment.

### 25 

### Because EPA was unaware of or disregarde d the wealth of information that exists regarding air quality and meteorological conditions at Look Rock, it attributed the influences it identified as “valley” impacts to Knoxville. EPA’s erroneous conclusion concerning the source areas of ozone precursors during high ozone events led it to designate th e entirety of Knox and Blount Counties and a portion of Anderson County nona ttainment. However, the back trajectory analyses conducted by both the Counties and TVA clearly demonstrate that air masses arriving at Look Rock during the high-ozone periods come from a variety of directions, most often from the south to southwest. Thus, EPA’s determination that ozone exceedances will decrease as a result of reducing Knoxville-area emissions (through the nonattainment designation) is arbitrary and capricious. In addition, EPA’s modeling fo r CSAPR projects significant NO X 

### and VOC emission reductions in the twelve-count y Knoxville CSA between 2005 a nd 2014. EPA’s modeling for implementation of the 2008 standard extrapol ated the CSAPR modelin g to 2015 and found that approximately half of all currently nonattaini ng areas nationwide would meet the 2008 standard in 2015, due to national and regional “emission -reducing rules already in place” and without “the need for states to use their scarce reso urces on local actions.” McCarthy Memo. at 2. The Counties calculated the county-by-county em issions projected for the Knoxville CSA by 2015 and found that NO X 

### emissions in the CSA are projected to decrease by over 25,000 tons per year or about 33% between 2008 and 2015 and that VOC emissions are projected to decrease by over 10,000 tons per year or about 19% over the same time period. See Tables 6 and 7 in Appendix 1. Based on the CSAPR modeling a nd EPA’s 2008 ozone standard modeling, all monitors in the Knoxville CSA are projected to be well below the 2008 ozone NAAQS by 2014 and 2015.

### 26 

### The Counties’ analysis of nine high-ozone ev ents at Look Rock indicated that the ozone precursor NO X 

### emissions that contributed to the high ozone levels were primarily from mobile sources. The Counties’ analysis of emission reductions that re sult from national and regional emission-reducing rules indicates that between 2008 and 2015, mobile source NO X 

### emissions across the twelve-county Knoxville CSA are proj ected to decrease by 15,695 tons per year or about 33%, while mobile source VOC emissions are projected to decrease by 8,880 tons per year or about 33%. Further, TVA already has reduced NO X 

### emissions at both its Bull Run Power Plant and its Kingston Power Plant to levels well below what is reflected in the CSAPR modeling by adding SCRs to all units at both plants (emi ssions in 2009, 2010, and 2011 we re already at this level). EPA promised to “minimize the regulatory burdens on the States” in making its ozone designations. McCarthy Memo. at 1. None theless, EPA has designated Blount County, Knox County, and a portion of Anderson County nonattainment when (1) EPA’s analysis indicates that high-ozone events at the lone (high-altitude) nonattainme nt monitor are due to anomalous conditions; and (2) EPA’s modeling s hows that the entire K noxville CSA will be in attainment with the 2008 standard in 2015. EPA ha s acted arbitrarily, capriciously, in abuse of its discretion, and otherwise not in accord ance with law in making its Knoxville CSA nonattainment designations, and the Counties ask for reconsideration of the Final Rule.

### 28 

### Appendix 1
Data Tables.29Table 1: Pertinent Nitrogen Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3) NOZ/NOYNO(μg/m3)NO2(μg/m3)NOX(μg/m3)NOZ(μg/m3)NOY(μg/m3)20090625 13:00 70 0.79 0.05 0.5 0.55 2.09 2.6420090625 14:00 79 0.82 0.05 0.58 0.63 2.81 3.4420090625 15:00 88 0.77 0.05 0.9 0.95 3.19 4.1420090625 16:00 92 0.81 0.05 0.87 0.92 3.82 4.7420090625 17:00 93 0.75 0.32 1.01 1.33 3.91 5.2420090625 18:00 89 0.79 0.22 0.84 1.06 3.88 4.9420090625 19:00 81 0.76 0.12 0.6 0.72 2.22 2.9420090625 20:00 81 0.72 0.22 0.55 0.77 1.97 2.7420090625 21:00 76 0.78 0.05 0.47 0.52 1.82 2.3420090625 22:00 76 0.69 0.32 0.49 0.81 1.83 2.6420090625 23:00 76 0.75 0.05 0.47 0.52 1.52 2.0420090626 0:00 75 0.92 0.05 0.13 0.18 2.02 2.2Ave. 81.3 0.78 0.13 0.62 0.75 2.59 3.34Max. 93 0.92 0.32 1.01 1.33 3.91 5.24Min. 70 0.69 0.05 0.13 0.18 1.52 2.0430Table 1: Pertinent Nitrogen Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3) NOZ/NOYNO(μg/m3)NO2(μg/m3)NOX(μg/m3)NOZ(μg/m3)NOY(μg/m3)20100402 13:00 0.85 0.12 0.91 1.03 5.81 6.8420100402 14:00 0.90 0.12 0.41 0.53 4.61 5.1420100402 15:00 79 0.88 0.22 0.37 0.59 4.15 4.7420100402 16:00 81 0.86 0.22 0.48 0.70 4.34 5.0420100402 17:00 79 0.84 0.12 0.64 0.76 3.88 4.6420100402 18:00 80 0.77 0.32 0.84 1.16 3.78 4.9420100402 19:00 89 0.47 2.92 1.2 4.12 3.62 7.7420100402 20:00 87 0.69 1.02 0.65 1.67 3.77 5.4420100402 21:00 81 0.89 0.05 0.41 0.46 3.58 4.0420100402 22:00 81 0.90 0.05 0.34 0.39 3.65 4.0420100402 23:00 84 0.93 0.05 0.25 0.30 3.94 4.2420100403 0:00 83 0.84 0.35 0.37 0.72 3.72 4.4420100403 1:00 79 0.78 0.55 0.33 0.88 3.06 3.9420100403 2:00 77 0.80 0.15 0.72 0.87 3.47 4.3420100403 3:00 76 0.80 0.15 0.66 0.81 3.33 4.1420100403 4:00 74 0.80 0.05 0.76 0.81 3.33 4.14Ave80.7 0.81 0.40 0.58 0.99 3.88 4.87Max89 0.93 2.92 1.20 4.12 4.34 7.74Min74 0.47 0.05 0.25 0.30 3.06 3.9431Table 1: Pertinent Nitrogen Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3) NOZ/NOYNO(μg/m3)NO2(μg/m3)NOX(μg/m3)NOZ(μg/m3)NOY(μg/m3)20100413 15:00 74 0.84 0.42 0.23 0.65 3.34 3.9920100413 16:00 76 0.85 0.32 0.26 0.58 3.41 3.9920100413 17:00 79 0.91 0.05 0.34 0.39 3.80 4.1920100413 18:00 81 0.67 1.52 0.36 1.88 3.81 5.6920100413 19:00 81 0.08 17.42 0.79 18.21 1.48 19.6920100413 20:00 81 0.10 8.52 0.33 8.85 0.94 9.7920100413 21:00 81 0.43 4.02 0.44 4.46 3.33 7.7920100413 22:00 82 0.68 1.22 0.3 1.52 3.17 4.6920100413 23:00 79 0.66 1.32 0.29 1.61 3.08 4.6920100414 0:00 79 0.70 1.01 0.4 1.41 3.27 4.6820100414 1:00 78 0.74 0.71 0.74 1.45 4.13 5.5820100414 2:00 76 0.80 0.21 0.91 1.12 4.36 5.4820100414 3:00 73 0.78 0.05 1.27 1.32 4.76 6.08Ave78.5 0.63 2.83 0.51 3.34 3.30 6.64Max82 0.91 17.42 1.27 18.21 4.76 19.69Min73 0.08 0.05 0.23 0.39 0.94 3.9932Table 1: Pertinent Nitrogen Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3) NOZ/NOYNO(μg/m3)NO2(μg/m3)NOX(μg/m3)NOZ(μg/m3)NOY(μg/m3)20100414 11:00 74 0.83 0.21 0.6 0.81 4.07 4.8820100414 12:00 79 0.86 0.11 0.67 0.78 4.60 5.3820100414 13:00 83 0.88 0.11 0.51 0.62 4.76 5.3820100414 14:00 84 0.88 0.21 0.51 0.72 5.16 5.8820100414 15:00 86 0.88 0.11 0.59 0.70 5.38 6.0820100414 16:00 84 0.85 0.31 0.57 0.88 4.80 5.6820100414 17:00 85 0.80 0.61 0.65 1.26 5.02 6.2820100414 18:00 85 0.73 1.11 0.86 1.97 5.31 7.2820100414 19:00 82 0.50 2.71 1.08 3.79 3.79 7.5820100414 20:00 78 0.72 0.51 0.79 1.30 3.38 4.6820100414 21:00 71 0.82 0.11 0.53 0.64 2.84 3.48Ave 81.0 0.80 0.56 0.67 1.22 4.46 5.69Max 86 0.88 2.71 1.08 3.79 5.38 7.58Min 71 0.50 0.11 0.51 0.62 2.84 3.4833Table 1: Pertinent Nitrogen Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3) NOZ/NOYNO(μg/m3)NO2(μg/m3)NOX(μg/m3)NOZ(μg/m3)NOY(μg/m3)20100415 14:00 75 0.84 0.14 0.58 0.72 3.92 4.6420100415 15:00 78 0.85 0.14 0.57 0.71 4.13 4.8420100415 16:00 79 0.81 0.44 0.59 1.03 4.31 5.3420100415 17:00 80 0.83 0.05 0.77 0.82 3.92 4.7420100415 18:00 80 0.80 0.05 0.81 0.86 3.48 4.3420100415 19:00 75 0.67 0.44 1.31 1.75 3.49 5.2420100415 20:00 75 0.32 3.24 0.89 4.13 1.91 6.0420100415 21:00 74 0.55 1.64 0.97 2.61 3.13 5.7420100415 22:00 76 0.42 2.34 0.76 3.10 2.24 5.3420100415 23:00 73 0.52 1.84 0.55 2.39 2.55 4.94Ave 76.5 0.66 1.03 0.78 1.81 3.31 5.12Max 80 0.85 3.24 1.31 4.13 4.31 6.04Min 73 0.32 0.05 0.55 0.71 1.91 4.3434Table 1: Pertinent Nitrogen Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3) NOZ/NOYNO(μg/m3)NO2(μg/m3)NOX(μg/m3)NOZ(μg/m3)NOY(μg/m3)20100505 18:00 74 0.62 0.58 0.6 1.18 1.92 3.1020100505 19:00 77 0.61 1.08 0.4 1.48 2.32 3.8020100505 20:00 76 0.63 0.88 0.45 1.33 2.27 3.6020100505 21:00 76 0.60 1.08 0.49 1.57 2.33 3.9020100505 22:00 80 0.63 1.08 0.5 1.58 2.72 4.3020100505 23:00 86 0.59 1.48 0.57 2.05 2.95 5.0020100506 0:00 84 0.72 1.01 0.4 1.41 3.69 5.1020100506 1:00 73 0.65 1.01 0.43 1.44 2.66 4.10Ave 78.3 0.63 1.03 0.48 1.51 2.61 4.11Max 86 0.72 1.48 0.60 2.05 3.69 5.10Min 73 0.59 0.58 0.40 1.18 1.92 3.1035Table 1: Pertinent Nitrogen Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3) NOZ/NOYNO(μg/m3)NO2(μg/m3)NOX(μg/m3)NOZ(μg/m3)NOY(μg/m3)20100506 11:00 68 0.84 0.41 0.07 0.48 2.52 320100506 12:00 80 0.87 0.31 0.16 0.47 3.23 3.720100506 13:00 81 0.88 0.31 0.1 0.41 2.99 3.420100506 14:00 82 0.90 0.21 0.14 0.35 3.25 3.620100506 15:00 79 0.89 0.21 0.13 0.34 2.86 3.220100506 16:00 78 0.85 0.31 0.2 0.51 2.89 3.420100506 17:00 77 0.83 0.41 0.18 0.59 2.81 3.420100506 18:00 76 0.61 1.21 0.26 1.47 2.33 3.820100506 19:00 80 0.13 5.11 0.34 5.45 0.85 6.320100506 20:00 79 0.47 2.71 0.46 3.17 2.83 620100506 21:00 80 0.32 3.01 0.48 3.49 1.61 5.120100506 22:00 79 0.24 5.31 0.35 5.66 1.74 7.420100506 23:00 76 5.11 0.67 5.7820100507 0:00 77 3.28 0.68 3.9620100507 1:00 76 0.49 2.08 0.39 2.47 2.36 4.8320100507 2:00 76 0.40 1.98 0.57 2.55 1.68 4.2320100507 3:00 75 0.37 2.08 0.58 2.66 1.57 4.23Ave77.6 0.61 2.00 0.34 2.34 2.37 4.37Max82 0.90 5.31 0.68 5.78 3.25 7.40Min68 0.13 0.21 0.07 0.34 0.85 3.0036Table 1: Pertinent Nitrogen Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3) NOZ/NOYNO(μg/m3)NO2(μg/m3)NOX(μg/m3)NOZ(μg/m3)NOY(μg/m3)20101011 17:00 75 0.82 0.05 0.2 0.25 1.13 1.3820101011 18:00 79 0.80 0.05 0.26 0.31 1.27 1.5820101011 19:00 77 0.78 0.05 0.26 0.31 1.07 1.3820101011 20:00 75 0.78 0.05 0.23 0.28 1.00 1.2820101011 21:00 76 0.82 0.05 0.2 0.25 1.13 1.3820101011 22:00 78 0.85 0.05 0.18 0.23 1.35 1.5820101011 23:00 78 0.83 0.05 0.23 0.28 1.40 1.6820101012 0:00 77 0.84 0.05 0.18 0.23 1.24 1.4720101012 1:00 78 0.88 0.05 0.14 0.19 1.38 1.5720101012 2:00 75 0.83 0.05 0.17 0.22 1.05 1.27Ave 76.8 0.82 0.05 0.21 0.26 1.20 1.46Max 79 0.88 0.05 0.26 0.31 1.40 1.68Min 75 0.78 0.05 0.14 0.19 1.00 1.2737Table 1: Pertinent Nitrogen Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3) NOZ/NOYNO(μg/m3)NO2(μg/m3)NOX(μg/m3)NOZ(μg/m3)NOY(μg/m3)20110803 12:00 73 0.89 0.06 0.05 0.11 0.93 1.0420110803 13:00 80 0.84 0.05 0.16 0.21 1.13 1.3420110803 14:00 78 0.90 0.05 0.11 0.16 1.48 1.6420110803 15:00 77 0.88 0.05 0.16 0.21 1.53 1.7420110803 16:00 76 0.90 0.06 0.1 0.16 1.38 1.5420110803 17:00 82 0.82 0.05 0.21 0.26 1.18 1.4420110803 18:00 78 0.84 0.05 0.13 0.18 0.96 1.1420110803 19:00 77 0.81 0.05 0.09 0.14 0.60 0.7420110803 20:00 78 0.72 0.05 0.1 0.15 0.39 0.5420110803 21:00 72 0.71 0.05 0.05 0.10 0.24 0.34Ave 77.1 0.83 0.05 0.12 0.17 0.98 1.15Max 82 0.90 0.06 0.21 0.26 1.53 1.74Min 72 0.71 0.05 0.05 0.1 0.24 0.3438Table 2: Pertinent Meteorological, Carbon, and Particulate Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3)WindDirection(degrees)SigmaTheta(degrees)WindSpeed(m/s)SolarRadiation(Wh/m2)CO(μg/m3)PM2.5(μg/m3)BlackCarbon(ng/m3)20090625 13:00 70 338 17 3.1 891 190.9 31.4 60920090625 14:00 79 335 19 2.7 871 196.9 15.5 66920090625 15:00 88 330 16 2.3 752 207.4 18.5 73520090625 16:00 92 337 19 1.8 586 172.9 24.0 66820090625 17:00 93 7 21 0.9 417 166.2 23.420090625 18:00 89 360 16 0.8 213 142.8 14.4 47220090625 19:00 81 37 20 1.7 46 133.9 17.9 43720090625 20:00 81 52 28 1 0 141.5 13.6 46820090625 21:00 76 48 22 1.9 0 138.7 12.6 44020090625 22:00 76 79 30 0.7 0 144.0 13.1 42620090625 23:00 76 151 8 1.2 0 150.8 18.6 46620090626 0:00 75 151 10 0.8 0 143.4 21.2 434Ave. 81.3 19 1.6 160.8 18.7 529Max. 93 30 3.1 207.4 31.4 735Min. 70 8 0.7 133.9 12.6 42639Table 2: Pertinent Meteorological, Carbon, and Particulate Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3)WindDirection(degrees)SigmaTheta(degrees)WindSpeed(m/s)SolarRadiation(Wh/m2)CO(μg/m3)PM2.5(μg/m3)BlackCarbon(ng/m3)20100402 13:00 28 90 0.8 109 295.4 NA 97620100402 14:00 334 25 2.2 532 266.5 NA 34620100402 15:00 79 311 22 3 584 262.2 NA 105620100402 16:00 81 311 24 2.6 372 268.8 NA 108020100402 17:00 79 309 17 2.2 193 268.4 NA 53720100402 18:00 80 299 17 2.3 31 274.7 NA 118020100402 19:00 89 248 31 0.8 0 288.4 NA 77920100402 20:00 87 148 11 3 0 284.4 NA 144720100402 21:00 81 160 10 4.6 0 269.0 NA 124920100402 22:00 81 161 13 4.5 0 274.7 NA 96020100402 23:00 84 160 11 5.1 0 318.3 NA 109720100403 0:00 83 160 18 3.7 0 326.7 NA 177720100403 1:00 79 172 34 3 0 279.4 NA 74320100403 2:00 77 168 21 4.5 0 256.3 NA 109620100403 3:00 76 166 16 5 0 258.6 NA 105220100403 4:00 74 162 13 6.5 0 259.7 NA 678Ave 80.7 23 3.4 278.2 NA 1003Max 89 34 6.5 326.7 NA 1777Min 74 10 0.8 256.3 NA 53740Table 2: Pertinent Meteorological, Carbon, and Particulate Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3)WindDirection(degrees)SigmaTheta(degrees)WindSpeed(m/s)SolarRadiation(Wh/m2)CO(μg/m3)PM2.5(μg/m3)BlackCarbon(ng/m3)20100413 15:00 74 324 41 1.9 671 189.0 16.4 35820100413 16:00 76 308 31 2 478 196.7 18.3 35520100413 17:00 79 329 24 2.2 264 209.2 17.720100413 18:00 81 315 32 1.2 75 220.6 14.5 49220100413 19:00 81 240 30 0.2 1 234.1 15.4 46120100413 20:00 81 289 5 1 0 237.7 16.4 44720100413 21:00 81 280 18 0.9 0 229.0 18.1 44820100413 22:00 82 298 8 1.5 0 220.3 16.3 45720100413 23:00 79 248 30 1 0 216.3 15.5 43720100414 0:00 79 323 24 0.8 0 216.9 18.5 43520100414 1:00 78 11 15 2.6 0 227.7 18.420100414 2:00 76 359 10 2.1 0 230.8 19.6 56320100414 3:00 73 346 6 2.4 0 240.1 18.9 592Ave 78.5 21 1.5 220.6 17.2 459Max 82 41 2.6 240.1 19.6 592Min 73 5 0.2 189.0 14.5 35541Table 2: Pertinent Meteorological, Carbon, and Particulate Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3)WindDirection(degrees)SigmaTheta(degrees)WindSpeed(m/s)SolarRadiation(Wh/m2)CO(μg/m3)PM2.5(μg/m3)BlackCarbon(ng/m3)20100414 11:00 74 331 22 3.4 859 234.1 23.8 60020100414 12:00 79 330 19 3.8 903 242.9 21.5 60920100414 13:00 83 333 22 3.8 881 233.0 21.4 54620100414 14:00 84 342 26 3.9 799 235.5 22.920100414 15:00 86 341 26 3.9 658 228.7 18.2 62320100414 16:00 84 350 30 3.2 475 224.2 19.6 52720100414 17:00 85 354 29 2.5 264 230.3 19.8 52820100414 18:00 85 22 22 2 80 236.2 17.9 51720100414 19:00 82 110 29 1.4 1 229.8 17.8 48220100414 20:00 78 144 11 2.9 0 234.9 17.4 50620100414 21:00 71 146 6 3.2 0 235.2 18.8Ave 81.0 22 3.1 233.2 19.9 549Max 86 30 3.9 242.9 23.8 623Min 71 6 1.4 224.2 17.4 48242Table 2: Pertinent Meteorological, Carbon, and Particulate Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3)WindDirection(degrees)SigmaTheta(degrees)WindSpeed(m/s)SolarRadiation(Wh/m2)CO(μg/m3)PM2.5(μg/m3)BlackCarbon(ng/m3)20100415 14:00 75 315 20 3.3 812 247.9 19.620100415 15:00 78 333 22 3.1 677 242.2 20.1 63220100415 16:00 79 337 26 2.6 492 222.6 19.4 56520100415 17:00 80 320 18 2.8 283 217.6 18.0 58620100415 18:00 80 314 11 3.1 84 210.9 14.3 51720100415 19:00 75 343 18 2.7 1 208.5 13.8 45820100415 20:00 75 76 23 0.4 0 199.0 15.2 41320100415 21:00 74 171 16 1.4 0 200.5 18.8 43520100415 22:00 76 191 42 1.1 0 213.1 16.120100415 23:00 73 228 62 0.8 0 209.2 16.1 482Ave 76.5 26 2.1 217.2 17.1 511Max 80 62 3.3 247.9 20.1 632Min 73 11 0.4 199.0 13.8 41343Table 2: Pertinent Meteorological, Carbon, and Particulate Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3)WindDirection(degrees)SigmaTheta(degrees)WindSpeed(m/s)SolarRadiation(Wh/m2)CO(μg/m3)PM2.5(μg/m3)BlackCarbon(ng/m3)20100505 18:00 74 281 42 1.1 134 191.2 10.6 36920100505 19:00 77 251 32 1.5 8 195.2 11.3 38720100505 20:00 76 256 35 1.5 0 195.9 10.8 37820100505 21:00 76 205 59 0.6 0 195.6 11.420100505 22:00 80 170 56 0.9 0 190.3 13.2 38820100505 23:00 86 181 63 0.7 0 207.4 14.0 50920100506 0:00 84 207 65 0.7 0 212.5 14.3 55220100506 1:00 73 235 56 1 0 204.6 14.8 484Ave78.3 51 1.0 199.1 12.6 438Max86 65 1.5 212.5 14.8 552Min73 32 0.6 190.3 10.6 36944Table 2: Pertinent Meteorological, Carbon, and Particulate Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3)WindDirection(degrees)SigmaTheta(degrees)WindSpeed(m/s)SolarRadiation(Wh/m2)CO(μg/m3)PM2.5(μg/m3)BlackCarbon(ng/m3)20100506 11:00 68 300 26 1.7 909 208.9 17.1 39820100506 12:00 80 309 25 2 945 209.5 17.1 43520100506 13:00 81 308 29 2 927 208.1 18.7 43620100506 14:00 82 310 28 2.3 845 207.7 14.8 45620100506 15:00 79 314 24 2.4 708 207.7 16.7 42520100506 16:00 78 315 26 1.6 525 202.4 17.2 42720100506 17:00 77 307 25 1.3 321 206.1 17.9 43120100506 18:00 76 302 49 0.7 123 210.1 14.3 42120100506 19:00 80 240 29 0.7 8 227.7 16.7 41520100506 20:00 79 193 13 0.9 0 212.6 16.4 41320100506 21:00 80 179 9 1 0 210.0 15.6 36720100506 22:00 79 160 53 0.2 0 221.5 16.120100506 23:00 76 138 14 1.1 0 217.2 16.4 40820100507 0:00 77 156 14 1.4 0 215.7 16.0 41020100507 1:00 76 163 33 1.1 0 215.1 16.0 41220100507 2:00 76 165 34 1.1 0 216.0 16.7 41620100507 3:00 75 151 17 1.7 0 219.2 17.4 421Ave 77.6 26 1.4 212.7 16.5 418Max 82 53 2.4 227.7 18.7 456Min 68 9 0.2 202.4 14.3 36745Table 2: Pertinent Meteorological, Carbon, and Particulate Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3)WindDirection(degrees)SigmaTheta(degrees)WindSpeed(m/s)SolarRadiation(Wh/m2)CO(μg/m3)PM2.5(μg/m3)BlackCarbon(ng/m3)20101011 17:00 75 255 39 0.9 34 157.7 18.820101011 18:00 79 176 33 1 0 162.7 18.0 38120101011 19:00 77 157 21 1.6 0 161.9 17.4 38220101011 20:00 75 172 52 0.8 0 165.7 17.3 38020101011 21:00 76 168 45 1 0 168.7 19.3 39520101011 22:00 78 166 42 1 0 163.4 23.0 42420101011 23:00 78 166 36 1.2 0 164.4 18.5 41520101012 0:00 77 163 30 1.6 0 162.1 17.7 41220101012 1:00 78 169 42 1.3 0 165.9 18.0 41520101012 2:00 75 181 61 0.8 0 165.1 18.2Ave 76.8 40 1.1 163.8 18.6 401Max 79 61 1.6 168.7 23.0 424Min 75 21 0.8 157.7 17.3 38046Table 2: Pertinent Meteorological, Carbon, and Particulate Data Used in the Counties’ Analysis.Date TimeOzone(μg/m3)WindDirection(degrees)SigmaTheta(degrees)WindSpeed(m/s)SolarRadiation(Wh/m2)CO(μg/m3)PM2.5(μg/m3)BlackCarbon(ng/m3)20110803 12:00 73 314 31 2.4 815 331.5 20.0 41120110803 13:00 80 321 41 1.3 927 365.8 20.1 43620110803 14:00 78 231 74 0.3 871 444.1 20.220110803 15:00 77 187 58 0.7 635 527.8 17.9 42420110803 16:00 76 246 67 0.6 479 567.3 20.9 40320110803 17:00 82 259 64 0.7 325 551.8 17.8 46520110803 18:00 78 253 45 1.1 128 513.1 17.9 40820110803 19:00 77 260 49 1 12 465.8 15.5 40320110803 20:00 78 243 63 0.8 0 408.2 16.8 38420110803 21:00 72 193 70 0.7 0 367.8 361Ave 77.1 56 1.0 454.3 18.6 411Max 82 74 2.4 567.3 20.9 465Min 72 31 0.3 331.5 15.5 361

### 47 

### Table 3: Analysis of Wind Direction Data for Look Rock Based on CASTNET Measurements for 2009-2011. Average Hourly Ozone Above 75 ppb

Wind Direction Number of Hours Wind From (hrs) Percent of Time Wind From (%) Average Solar Radiation (Whrs/m 2 

### ) N 135 47.4 385 E 37 13.0 18 S 71 24.9 21 W 42 14.7 251 Average Hourly Ozone 75 ppb or Below

Wind Direction Number of Hours Wind From (hrs) Percent of Time Wind From (%) Average Solar Radiation (Whrs/m 2 

### ) N 7181 30.6 221 E 1015 4.3 54 S 7842 33.3 97 W 747 31.8 196

### 48 Table 4: Detailed Look Rock Back Trajectory Analysis.

Episode Date(s) Times 1-Hr Ozone 75 ppb (24-hr Clock) General Direction of Back Trajectory Did Back Trajectory Cross Any Portion of Knox County? Back Trajectory Reference (Appendix 2) 6/25/2009 1400-2300 Northeast Yes, sparsely populated eastern portion Figure 1 4/2-3/2010 1500-0400 South No Figure 2 4/13-14/10 1600-0300 South to southwest No Figure 3
4/14/2010 1200-2000 South to southwest No Figure 4
4/15/2010 1500-2200 South to southwest No Figure 5
5/5-6/10 1900-0000 South to southwest No Figure 6
5/6-7/10 1200-0200 South to southwest No Figure 7
7/7/2010 1500-1900 North Yes, densely populated central portion Figure 8
7/8/2010 1100-1900 North to northeast Yes, densely populated central portion Figure 9
9/2/2010 1200-1900 North Yes, densely populated central and west portions Figure 10
9/21-22/10 2000-0100 South to southeast No Figure 11
10/11-12-10 1800-0100 South to southwest No Figure 12
6/2-3/11 1500-0600 North to northeast Yes, densely populated central and west portions Figure 13
6/3-4/11 1200-0600 East to northeast Yes, only 500 m over sparsely populated eastern portion Figure 14
6/4/2011 1300-2100 North to northeast Yes, densely populated central and west portions Figure 15
6/6/2011 1600-2200 North to northeast Yes, sparsely populated eastern portion Figure 16
6/30/2011 1500-2300 Northeast Yes, sparsely populated eastern portion Figure 17 7/2/2011 0000-0600 East No Figure 18 7/2/2011 1200-2200 North to northeast Yes, densely populated central portion Figure 19
7/13/2011 1300-1700 North Yes, densely populated central portion Figure 20 8/3/2011 1300-2000 Southwest No Figure 21 8/12/2011 1400-2300 North to northeast Yes, densely populated central portion Figure 22
9/2/2011 1400-2100 South to southwest Yes, sparsely populated southwest portion Figure 23

### 49 

### Table 5: NO X 

### and VOC Emission Levels and Emission Reduction Percentages Used in CSAPR Modeling by Source Type for Tennessee. Source Type 2005 Emissions (TPY) NO X 

### VOC 2005 EGU 102,934 798 2005 Non-EGU Point 54,255 79,846 2005 Nonpoint 18,676 143,122 2005 Non-road 82,331 58,612

2005 On-road 267,818 100,951 Fires 1,012 10,803 2005 Total 527,026 394,132 Source Type 2012 Emissions (TPY)/Reductions (%) 2012 EGU 37,694/63.4 863/-8.1 1 

### 2012 Non-EGU Point 51,355/5.3 66,682/16.5 2012 Nonpoint 18,483/1.0 136,736/4.5 2012 Non-road 65,209/20.8 42,527/27.4

2012 On-road 164,294/38.7 62,182/38.4 2012 Fires 1,012/0.0 10,803/0.0 2012 Total 338,047/35.9 319,793/18.9
Source Type 2014 Emissions (TPY)/Reductions (%) 2014 EGU 29,276/71.6 773/3.1 2014 Non-EGU Point 49,126/9.5 66,476/16.7 2014 Nonpoint 18,184/2.6 133,244/6.9 2014 Non-road 60,111/27.0 37,647/35.8

2014 On-road 144,394/46.1 56,570/44.0 2014 Fires 1,012/0.0 10,803/0.0 2014 Total 302,103/42.7 305,513/22.5

### 50 

### Table 6: Projected 2008-2015 NO X 

### Emission Reductions by County and Source Type for the Knoxville CSA Based on CSPAR Modeling and the 2008 NEI.

State/County/Emission Source Type 2008 NO X 

### Emissions 1 

### (TPY) 2008-2015 Percent

NO X 

### Emission Reduction 2 

### (%) Projected 2015 NO X 

### Emissions 3 

### (TPY) Projected 2008-2015 NO X 

### Emission Reduction 4 

### (TPY) Anderson EGU 8725.87 55.7 3,869.35 4,856.52 Non-EGU Point 1134.78 7.4 1,051.33 83.45 Nonpoint 60.55 2.0 59.30 1.24 Nonroad 831.99 21.0 657.34 174.64

Onroad 2,353.52 35.8 1,509.92 843.59 Fires 57.54 0.0 57.54 0.00 Total 13,164.25 7,204.48 5,959.44 Blount EGU 7.87 55.7 3.49 4.38 Non-EGU Point 881.60 7.4 816.77 64.83 Nonpoint 75.42 2.0 73.88 1.55 Nonroad 888.62 21.0 702.90 186.53

Onroad 2,340.07 35.9 1,501.30 838.78 Fires 36.67 0.0 36.67 0.00 Total 4,230.25 3,135.01 1,096.07 Campbell EGU 0.00 55.7 0.00 0.00 Non-EGU Point 164.55 7.4 152.45 12.10 Nonpoint 32.64 2.0 31.97 0.67 Nonroad 593.12 21.0 468.62 124.50

Onroad 3,182.45 35.9 2,041.73 1,140.72 Fires 53.82 0.0 53.82 0.00 Total 4,026.58 2,748.59 1,277.99 Cocke EGU 0.00 55.7 0.00 0.00 Non-EGU Point 145.04 7.4 134.37 10.67 Nonpoint 18.31 2.0 17.93 0.38 Nonroad 263.01 21.0 207.80 55.21

Onroad 1,898.44 35.8 1,217.97 680.48 Fires 75.64 0.0 75.64 0.00 Total 2,400.44 1,653.71 746.74

### 51 

### Table 6: Projected 2008-2015 NO X 

### Emission Reductions by County and Source Type for the Knoxville CSA Based on CSPAR Modeling and the 2008 NEI.

State/County/Emission Source Type 2008 NO X 

### Emissions 1 

### (TPY) 2008-2015 Percent

NO X 

### Emission Reduction 2 

### (%) Projected 2015 NO X 

### Emissions 3 

### (TPY) Projected 2008-2015 NO X 

### Emission Reduction 4 

### (TPY) Grainger EGU 0.00 55.7 0.00 0.00 Non-EGU Point 82.47 7.4 76.40 6.06 Nonpoint 6.64 2.0 6.50 0.14 Nonroad 155.33 21.0 122.73 32.61

Onroad 645.61 35.9 414.20 231.41 Fires 39.49 0.0 39.49 0.00 Total 929.54 659.32 270.22 Hamblen EGU 0.00 55.7 0.00 0.00 Non-EGU Point 4,470.59 7.4 4,141.83 328.75 Nonpoint 24.68 2.0 24.17 0.51 Nonroad 673.54 21.0 532.16 141.38

Onroad 2,128.19 35.9 1,365.36 762.83 Fires 2.54 0.0 2.54 0.00 Total 7,299.54 6,066.06 1,233.47 Jefferson EGU 0.00 55.7 0.00 0.00 Non-EGU Point 252.20 7.4 233.65 18.55 Nonpoint 21.75 2.0 21.30 0.45 Nonroad 539.67 21.0 426.38 113.28

Onroad 3,255.31 35.9 2,088.48 1,166.83 Fires 24.65 0.0 24.65 0.00 Total 4,093.58 2,794.46 1,299.11 Knox EGU 0.00 55.7 0.00 0.00 Non-EGU Point 1,745.91 7.4 1,617.52 128.39 Nonpoint 254.48 2.0 249.36 5.22 Nonroad 3,271.83 21.0 2,585.04 686.79

Onroad 13,976.54 35.9 8,966.79 5,009.75 Fires 27.36 0.0 27.36 0.00 Total 19,276.12 13,446.07 5,830.15

### 52 

### Table 6: Projected 2008-2015 NO X 

### Emission Reductions by County and Source Type for the Knoxville CSA Based on CSPAR Modeling and the 2008 NEI.

State/County/Emission Source Type 2008 NO X 

### Emissions 1 

### (TPY) 2008-2015 Percent

NO X 

### Emission Reduction 2 

### (%) Projected 2015 NO X 

### Emissions 3 

### (TPY) Projected 2008-2015 NO X 

### Emission Reduction 4 

### (TPY) Loudon EGU 3.64 55.7 1.61 2.03 Non-EGU Point 1,070.50 7.4 991.78 78.72 Non p oint 40.41 2.0 39.58 0.83 Nonroa d 503.65 21.0 397.93 105.72

Onroa d 2,979.14 35.8 1,911.30 1,067.84 Fires 6.94 0.0 6.94 0.00 Total 4,604.28 3,349.14 1,255.14 Roane EGU 7,927.21 55.7 3,515.20 4,412.01 Non-EGU Point 176.60 7.4 163.61 12.99 Nonpoint 40.41 2.0 39.58 0.83 Nonroa d 693.65 21.0 548.05 145.61

Onroa d 2,866.05 35.8 1,838.74 1,027.31 Fires 16.42 0.0 16.42 0.00 Total 11,720.34 6,121.6 5,598.75 Sevier EGU 0.00 55.7 0.00 0.0 Non-EGU Point 212.16 7.4 195.56 15.60 Nonpoint 31.38 2.0 30.74 0.64 Nonroa d 357.87 21.0 282.75 75.12

Onroa d 2,653.30 35.8 1,702.25 951.05 Fires 38.76 0.0 38.76 0.00 Total 3,293.47 2,250.06 1,042.41 Union EGU 0.00 55.7 0.00 0.00 Non-EGU Point 57.89 7.4 53.63 4.26 Non p oint 5.74 2.0 5.62 0.12 Nonroa d 150.92 21.0 119.24 31.68

Onroa d 283.08 35.8 181.62 101.47 Fires 22.02 0.0 22.02 0.00 Total 519.65 382.13 137.53 1. 2008 emissions are from the 2008 NEI, v2 found at http://www.epa.gov/ttn/chie f/net/2008inventory.html. 2. Based on the emission reductions for 2005- 2014 from the CSAPR modeling. 2005-2014 percent reductions were divided by nine and multiplied by seven. 3. Based on 2008 emissions minus the percent reduction from column 3 times the 2008 emissions. 4. The difference between 2008 emissions and the projected 2015 emissions.

### 53 

### Table 7: Projected 2008-2015 VOC Emissi on Reductions by County and Source Type for the Knoxville CSA Based on CSPAR Modeling and the 2008 NEI.

State/County/Emission Source Type 2008 VOC Emissions 1 

### (TPY) 2008-2015 Percent

VOC Emission Reduction 2 

### (%) Projected 2015 VOC Emissions 3 

### (TPY) Projected 2008-2015 VOC Emission Reduction 4 

### (TPY) Anderson EGU 47.18 2.5 46.02 1.16 Non-EGU Point 607.66 13.0 528.52 79.14 Nonpoint 884.27 5.4 836.80 47.47 Nonroad 745.04 27.8 537.76 207.28

Onroad 886.75 34.2 583.53 303.21 Fires 903.15 0.0 903.15 0.00 Total 4,074.05 3,435.78 638.26 Blount EGU 0.57 2.5 0.55 0.02 Non-EGU Point 2,422.09 13.0 2,106.65 315.45 Nonpoint 1,306.76 5.4 1,236.61 70.15 Nonroad 1,106.39 27.8 798.58 307.81

Onroad 1,255.48 34.2 826.19 429.30 Fires 369.56 0.0 369.56 0.00 Total 6,460.85 5,338.14 1,122.73 Campbell EGU 0.00 -- 0.00 0.00 Non-EGU Point 175.92 13.0 153.00 22.91 Nonpoint 394.91 5.4 373.71 21.20 Nonroad 459.64 27.8 331.76 127.88

Onroad 649.82 34.2 427.62 222.20 Fires 915.97 0.0 915.97 0.00 Total 2,596.26 2,202.06 394.19 Cocke EGU 0.00 -- 0.00 0.00 Non-EGU Point 235.72 13.0 205.02 30.70 Nonpoint 475.34 5.4 449.83 25.52 Nonroad 891.16 27.8 643.23 247.93

Onroad 594.11 34.2 390.96 203.15 Fires 1,078.79 0.0 1,078.79 0.00 Total 3,275.12 2,767.83 507.30

### 54 

### Table 7: Projected 2008-2015 VOC Emissi on Reductions by County and Source Type for the Knoxville CSA Based on CSPAR Modeling and the 2008 NEI.

State/County/Emission Source Type 2008 VOC Emissions 1 

### (TPY) 2008-2015 Percent

VOC Emission Reduction 2 

### (%) Projected 2015 VOC Emissions 3 

### (TPY) Projected 2008-2015 VOC Emission Reduction 4 

### (TPY) Grainger EGU 0.00 -- 0.00 0.00 Non-EGU Point 55.03 13.0 47.86 7.17 Nonpoint 231.28 5.4 218.87 12.42 Nonroad 580.22 27.8 418.80 161.42

Onroad 303.22 34.2 199.54 103.68 Fires 830.06 0.0 830.06 0.00 Total 1,999.81 1,715.13 284.69 Hamblen EGU 0.00 -- 0.00 0.00 Non-EGU Point 1,187.29 13.0 1,032.66 154.63 Nonpoint 1,679.47 5.4 1,589.31 90.15 Nonroad 642.49 27.8 463.74 178.75

Onroad 974.10 34.2 641.02 333.08 Fires 24.14 0.0 24.14 0.00 Total 4,507.49 3,750.87 756.61 Jefferson EGU 0.00 -- 0.00 0.00 Non-EGU Point 336.16 13.0 292.38 43.78 Nonpoint 799.60 5.4 756.68 42.92 Nonroad 1,131.49 27.8 816.70 314.79

Onroad 823.62 34.2 541.99 281.63 Fires 332.90 0.0 332.90 0.00 Total 3,423.77 2,740.65 638.12 Knox EGU 0.00 -- 0.00 0.00 Non-EGU Point 751.13 13.0 653.30 97.83 Nonpoint 4,273.79 5.4 4,044.37 229.42 Nonroad 2,507.66 27.8 1,810.00 697.66

Onroad 5,922.24 34.2 3,897.20 2,025.04 Fires 470.01 0.0 470.01 0.00 Total 13,924.83 10,874.88 3,049.95

### 55 

### Table 7: Projected 2008-2015 VOC Emissi on Reductions by County and Source Type for the Knoxville CSA Based on CSPAR Modeling and the 2008 NEI.

State/County/Emission Source Type 2008 VOC Emissions 1 

### (TPY) 2008-2015 Percent

VOC Emission Reduction 2 

### (%) Projected 2015 VOC Emissions 3 

### (TPY) Projected 2008-2015 VOC Emission Reduction 4 

### (TPY) Loudon EGU 2.90 2.5 2.83 0.07 Non-EGU Point 1,020.28 13.0 887.40 132.88 Non p oint 528.01 5.4 499.66 28.34 Nonroa d 758.42 27.8 547.42 211.00

Onroa d 783.95 34.2 515.89 268.06 Fires 96.96 0.0 96.96 0.00 Total 3,190.52 2,550.16 640.35 Roane EGU 152.07 2.5 148.34 3.74 Non-EGU Point 226.76 13.0 197.23 29.53 Non p oint 532.44 5.4 503.86 28.58 Nonroa d 907.01 27.8 654.67 252.34

Onroa d 1,013.70 34.2 667.07 346.62 Fires 189.31 0.0 189.31 0.00 Total 3,021.29 2,360.48 660.81 Sevier EGU 0.00

-- 0.00 0.00 Non-EGU Point 192.24 13.0 167.21 25.04 Non p oint 954.67 5.4 903.42 51.25 Nonroa d 2,388.01 27.8 1,723.64 664.37

Onroa d 1,267.42 34.2 834.04 433.38 Fires 556.71 0.0 556.71 0.00 Total 5,359.05 4,185.02 1,174.04 Union EGU 0.00

-- 0.00 0.00 Non-EGU Point 64.18 13.0 55.82 8.36 Non p oint 214.44 5.4 202.93 11.51 Nonroa d 480.14 27.8 346.56 133.58

Onroa d 133.86 34.2 88.09 45.77 Fires 398.96 0.0 398.96 0.00 Total 1,291.58 1,092.36 199.22 1. 2008 emissions are from the 2008 NEI, v2 found at http://www.epa.gov/ttn/chief/ net/2008inventory.html . 2. Based on the emission reductions for 2005- 2014 from the CSAPR modeling. 2005-2014 percent reductions were divided by 9 and multiplied by 7. 3. Based on 2008 emissions minus the percent reduction from column 3 times the 2008 emissions. 4. The difference between 2008 emissions and the projected 2015 emissions.

### 56 

### Table 8: 2008-2011 NO X 

### Emissions and Emission Rates for TVA’s Bull Run Power Plant. 1



### Year Annual Emissions (TPY) Annual Emission Rate (lbs/mmBTU) 2005 11,487.6 0.358 2006 8,352.0 0.370 2007 11,929.8 0.362 2008 8,622.3 0.387 2009 1,270.7 0.086 2010 1,221.0 0.068 2011 911.9 0.069 1. Source: EPA Air Markets Program Data.

### 57 

### Table 9: 2008-2011 NO X 

### Emissions and Emission Rates for TVA’s Kingston Power Plant. 1



### Year Annual Emissions (TPY) Annual Emission Rate (lbs/mmBTU) 2005 14,318.4 0.284 2006 13,953.2 0.260 2007 12,541.5 0.235 2008 7,927.8 0.148 2009 549.3 0.053 2010 1,602.8 0.091 2011 1,532.5 0.058 1. Source: EPA Air Markets Program Data.

### 58 

### Table 10: Summary of the CSAPR Mo deling and EPA’s Extrapolations for the 2008 Ozone NAAQS for the Knoxville CSA.

County Monitor Location 2003- 2007 DV

(ppb) CSAPR Projected 2014 DV

(ppb) 2008- 2010 DV

(ppb) 2015 Extrapolated DV (ppb) Anderson Freels Bend 77.3 63.4 70 63.0

Blount Cades Cove 68.5 57.5 69 62.9 Blount Look Rock 85.3 71.3 77 70.0 Jefferson Lost Creek 82.3 68.3 74 67.1

Knox Mildred Drive 85.0 71.5 76 69.3 Knox Rutledge Pike 78.7 66.1 71 64.7 Loudon Roberts Road 85.0 68.9 73 65.3 Sevier Clingmans Dome 80.7 67.6 76 69.2 Sevier Cove Mountain 79.0 65.6 76 68.9 1. From Spreadsheet projecting the hypothetical 8-hour ozone nonattainment areas for the 75 ppb NAAQS to 2015 to estimate the number of marginal nonattainment areas that are expected to attain the NAAQS by their attainment date of 2015 , (EPA-HQ-OAR-2010- 0885-0064).9125915.11 

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP 0 25 50 12.5 Miles FIGURE 1 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 30 60 15 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP 0 75 150 37.5 Miles FIGURE 2 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

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### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP 0 50 100 25 Miles FIGURE 3 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 60 120 30 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP 0 40 80 20 Miles FIGURE 4 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 40 80 20 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP 0 30 60 15 Miles FIGURE 5 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 40 80 20 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

### Statistical Boundary 10.0 m AGL Trajectory Ending at 2200 UTC 14 April 2010 (1800 EDT 14 April 2010)I85 I381

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP 0 50 100 25 Miles FIGURE 6 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 50 100 25 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP 0 50 100 25 Miles FIGURE 7 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 60 120 30 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP 0 25 50 12.5 Miles FIGURE 8 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 30 60 15 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

### Statistical Boundary 10.0 m AGL Trajectory Ending at 2200 UTC 7 July 2010 (1800 EDT 7 July 2010)I85 I381

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP 0 30 60 15 Miles FIGURE 9 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 40 80 20 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

### Statistical Boundary 10.0 m AGL Trajectory Ending at 2000 UTC 8 July 2010 (1600 EDT 8 July 2010)I385 I381

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP

0 25 50 12.5 Miles FIGURE 10 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 30 60 15 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP 0 50 100 25 Miles FIGURE 11 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 50 100 25 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP 0 30 60 15 Miles FIGURE 12 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 40 80 20 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP 0 30 60 15 Miles FIGURE 13 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 40 80 20 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP 0 25 50 12.5 Miles FIGURE 14 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 30 60 15 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP 0 25 50 12.5 Miles FIGURE 15 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 30 60 15 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP 0 30 60 15 Miles FIGURE 16 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 40 80 20 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP 0 30 60 15 Miles FIGURE 17 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 40 80 20 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

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1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 30 60 15 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

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Basemap Source: ESRI, i-cubed, USDA FSA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGP 0 25 50 12.5 Miles FIGURE 19 NOAA HYSPLIT Backward Trajectory

1-800-588-7962 WWW.ENSAFE.COM DATE: 10/10/2012 DRAWN BY: J. Shipp/B. Bolton

0888812099 PROJECT NO: N. Rinehart REQUESTED BY:

0 30 60 15 Kilometers 

### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

### Statistical Boundary 10.0 m AGL Trajectory Ending at 2100 UTC 2 July 2011 (1700 EDT 2 July 2011)I385 I381

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### 500.0 m AGL Trajectory 100.0 m AGL Trajectory Highways Great Smoky Mountains National Park Boundary 

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### Appendix 3 TVA’s “Cluster Analysis of Lo ok Rock High Ozone Events and Related Air Parcel Trajectories for 2009-2011.”

### 1 Cluster Analysis of Look Ro ck High Ozone Events and Related Air Parcel Trajectories for 2009-2011 Prepared by Stephen F. Mueller, CCM Tennessee Valley Authority September 2012
Cluster analysis is a statistical procedure designed to explore relationships within groups of data. As such its primary use is to identify commonalities across different sets of variables with no assumed prior knowledge of how su ch variables might be related (Wilks, 2006). Cluster analysis has been applied in studies of atmospheric and climate data. The SAS® statistical software package provides tools for performing cluster analysis. An analysis of Look Rock ozone and trajectory data during 2009-2011 high ozone even ts was performed using the SAS ACECLUS and CLUSTER procedures 1 

### (SAS version 9.2). The ACECLUS procedure analyzes raw data to convert it into variables be tter suited for cluster analysis. This analysis convert s data that are elliptical in n -dimensional space (i.e., exhibit more variation in one direction than the other) into sp herical data that are then re-configured into n canonical (transformed) variables re presenting different combinations of the original data. In this way, ACECLUS performs a procedure simila r to what is done in computing principal components for principal component analysis. The resulting canonical vari ables are then made available for analysis using CLUSTER. CLUSTER performs a hierarchical analysis starting with all data points in their own separate cluster. In a continuous sequenc e, the data points are combined (“agglomerated”) into fewer clusters by associating data pair s having the most similarities based on the relative separation between the cluster-mean values of the canonical variables. The relative degree of reduction in total parametric variance across the remaining clus ters provides a measure of how the clustering process reduces variations from more to fewe r data clusters. SAS CLUSTER documentation provides guidance, based on several statistical metrics, on how to identify significant numbers of clusters. This guidance was used in devel oping the clustering re sults described here.
Data Simulated air parcel coordinates (latitude and l ongitude) for trajectories arriving at Look Rock during high ozone episodes form the basis of th is cluster analysis along with ozone levels measured at Look Rock. HYSPLIT model trajectories arriving at 10, 10 0 and 500 m above Look Rock were provided for differe nt hours during 23 high 8-hr ozone periods of 2009-2011. Data for 63 sets of trajectories were combined w ith the maximum hourly and 8-hr average ozone (centered on the maximum hourly ozone level) mi xing ratios measured on a given day. A subset of 9 high ozone events--represented by 40 sets of trajectories--were accompanied by other air

1 

### Documentation found at http://support.sas.com/documentati on/cdl/en/statug/63033/HTML/defaul t/ viewer.htm#aceclus_toc.htm (ACECLUS) and http://support.sas.com/documentation/cdl/en/statug/63033/H TML/default/viewer.htm#cluster_toc.htm (CLUSTER).

### 2 quality data to provide a more detailed picture of the conditions associated with the high ozone events. Thus, 14 events were characterized only by ozone and 23 sets of trajectory data. For the 9 “detailed” events, data provided 8-hr averages and hourly maximum mixing ratios of CO, NO, NO 2 

### , NO y 

### and photochemical age ( τ=NO z 

### /NO y 

### ), along with 8-hr average solar radiation flux and ridge top wind direction and sp eed. These 8-hr averages coincided with the 8- hr ozone averages previously mentioned. Analysis Trajectory coordinates and oz one mixing ratio (hourly maxima or 8-hr averages) provide excellent variables for cluster analysis because th ey are linear variables with little covariance between data pairs. The canonical variable eq uivalents input into CLUSTER were selected for their expected ability to characterize Look Rock high ozone events. Although any and all trajectory coordinates could have be en used, it is best to minimize the number of parameters in a cluster analysis for ease of interpretation. To this end, CLUSTER wa s run with trajectory coordinates for 10 and 100 m trajectories ( lat 10 

### , lon 10 

### , lat 100 

### and lon 100 

### ) at 12 hr upwind of Look Rock in combination with either the 8-hr average ( C 8h 

### ) or maximum hourly ( C max 

### ) ozone mixing ratio for each event. Both 3 and 5 variable clustering were examined (3 parameter clustering used one ozone metric and one se t of trajectory coordinates; 5 parameter clustering used one ozone metric and both sets of trajectory coordinates). Additional paramete rs add more canonical variance to each analysis (and more potential clus ters) and there can be a trade-off between the useful information derived from the clusters and quantity of results to be interpreted. Although both C 8h 

### and C max 

### were tested, neither was clearly superior in providing more definitive clusters. A bit more variance was contained in the fewest significant clusters using C

max 

### in combination with both trajectory points. Al so, more clusters were needed to identify a major portion of the overall parametric variances when data from both trajectories were used rather than only one of the two trajectories. However, given the complexity of boundary layer airflow and the potential for emissions from differ ent locations to contribute to ozone formation in an environment characterized by complex topogr aphy, it was decided that more useful results could be obtained by jointly analyzing the 10- and 100-m trajectory coordinate fields. After reviewing results based on C max 

### , lat 10 

### , lon 10 

### , lat 100 

### and lon 100 

### (a 5-parameter model) it was evident that the 9 event days accompanied by detailed Look Rock data could be grouped into only 5 clusters representi ng 79 percent of the total parametric variance in the data. However, to achieve a similar degree of parametric variance ( 80 percent) required 11 clusters for the larger 23 event/63 trajectory data set. Clusters are labeled using C 1 

### , C 2 

### , ...C n 

### for an n -cluster result. The first cluster represents the larg est set of agglomerated variance with each subsequent cluster representing decreasing amounts of variance. Comparing trajecto ries common to both sets of results (i.e., for the 9 event subset and the 23 ev ents) it is possible to identify how well the 9- event subset represents the larg er 3-year data base. Table 1 summarizes the commonalities and differences between the two clustering analyses. There is no perfect one- to-one match between the two sets of clusters. The larger number of clusters needed to characterize the 23-event data set introduces more cl usters than could be

### 3 identified using the smaller event subset. This causes some trajectories clustered together in the smaller subset analysis to split across multiple clusters in the larger set. However, some clusters remained intact between the two analyses. The most important (largest contribution to total variance) cluster for the 9-event subset, C 1 

### , was contained entirely in the second cluster of the full data set (denoted FC 2 

### ). The second subset cluster (C 2 

### ) was mostly included in FC 3 

### although small portions were also found in FC 7 

### and FC 10 

### . All of C 3 

### mapped to FC 4 

### , all of C 4 

### mapped to FC 7 

### and all of C 5 

### mapped to FC 8 

### . C 6 

### and FC 11 

### also had a large degree of overlap and both included the largest number of individual data points with the smallest relative contributions to total variance within their data sets. Other subset clusters were spl it across the clusters of the full data set in varying amounts. The complete data set identified 3 clusters--FC 1 

### , FC 5 

### and FC 6 

### --that had no cross-mapping with the subset. These 3 unmapped clusters represent 37 percent of the total variance in the larger set of data. To better understand how well the subset represents the full set it is imperative to examine the relative spatial representations of the different cl usters regarding air pollu tant transport and the comparative ozone values between the two sets of clusters. Plots of 12-hr upwind 10- and 100-m trajectory locations averaged by cluster are illustrated in Figure 1. Except for FC 8 

### , the clusteraverage 10- and 100-m trajectory locations at 12 hr upwind from Look Rock fall within 40 km and one direction sector of each ot her. Therefore, the trajectories at the two levels are mutually consistent and do not indicate airflo w from vastly different origins. Figures 2 and 3 compare average C 8h 

### and C max 

### for the data that fall into the clusters of the full data set. Subset clusters that mapped to the larger cluster set do a good job of representing the average cluster C 8h 

### (Figure 2) even though th is parameter was not in cluded in the clustering procedure. For C max 

### , the match between the two data sets (Figure 3) was excellent as would be expected because C max 

### was used to define the clusters. Other parameters that match well between the two data sets are the upwind distances (relative to Look Rock) of the 10- and 100-m trajectories (Figures 4 and 5). Interpretation With 8 of 11 clusters containing detailed data fro m the 9-event subset it is possible to determine how most subsets differ from the others. Figure s 6-8 illustrate cluste r averages of 8-hr NO y 

### , CO Table 1. Relative mapping between clusters derived from the full 3-year 23-event data set and the 9-event subset. Clusters a 

### 23-Event Set 9-Event Subset Mapping b 

### FC 1 

### FC 2 

### C 1 

### (100%) FC 3 

### C 2 

### (67%) FC 4 

### C 3 

### (100%) FC 5 

### FC 6 

### FC 7 

### C 2 

### (17%) & C 4 

### (100%) FC 8 

### C 5 

### (100%) & C 6 

### (5%) FC 9 

### C 6 

### (14%) FC 10 

### C 2 

### (17%) & C 6 

### (9%) FC 11 

### C 6 

### (73%)
a 

### The cluster designations in each column refer to the designations used for the individual cluster an alyses and are not equivalent across columns. b 

### Values in () denote the fraction of observations in the subset cluster that contributed to the clusters from the larger data set.

### 4 and photochemical age ( τ ). Of those clusters containing data, FC 8 

### had the highest NO y 

### levels while FC 9 

### had the lowest. The airmasses in FC 9 

### had the highest mean τ while the lowest was found for FC 8 

### . In general, τ was inversely associated with NO y 

### . FC 9 

### had the highest average CO levels and FC 2 

### had the lowest. From these data the cl usters can be characterized as summarized in Table 2. Clusters 1, 2 and 6 The highest ozone was asso ciated with clusters FC 1 

### and FC 2 

### and the transport directions were very similar with 12-hr orig ins being farther upwind for FC 2 

### (i.e., winds were stronger for FC 2 

### ).

Table 2. Summary of event cluster characteristics.
Cluster % ofTrajectories O 3 a 

### NO y 

### /Age CO Transport b


### 1 10 Highest N/A N/A From NNE within 40-45 km (i.e., 10 km ENE of downtown Knoxville) 

### 2 14 High Moderate/ high Low From NNE/NE within 75-80 km 

### 3 6 Moderately high Moderate/ high Moderate From S/SSW within 150-200 km (passing east of Atlanta) 

### 4 3 Moderately high Moderate/ high Moderate From S within 185-200 km



### 5 3 Moderate N/A N/A From NE within 100-150 km 

### 6 11 Moderately low N/A N/A From NNE/NE within 70-80 km 

### 7 5 Moderately low Moderately high/ high Moderate From SE within 145-160 km 

### 8 8 Moderate High/low Moderate From ESE through SSW sectors within 15-35 km 

### 9 5 Moderately low Low/high High From WSW within 135-140 km (Chattanooga) 

### 10 5 Moderately low Moderate/ moderate Moderate From SW within 80-100 km 

### 11 30 Moderately low Moderate/ moderate Moderate From WSW within 75-80 km

a 

### Ratings are relative acro ss the population of all event clusters. All 8-hr average ozone levels exceed 75 ppb except for cluster 6 (74 ppb). b 

### Distances refer to transport during the 12 hours preceding arrival at Look Rock and include information from both the 10- and 100-m trajectories.

### 5 Detailed air quality data other th an ozone were not available for FC 1 

### , but given the similarities in transport directions and ozone levels (with lowe r ozone levels associated with higher transport speeds as expected) it is likely th at the air quality signatures of th ese two clusters are similar. FC 2 

### had moderate NO y 

### levels, high τ and low CO. Thus, the airmasses associated with FC 2 

### do not have a strong urban signature despite passi ng only 10 km or so east of downtown Knoxville. Instead, they appear more strongl y associated with transport from more distant sources despite the fact that 12-hr transport distances were not that high. FC 6 

### transport overlapped completely with that of FC 1 

### and FC 2 

### with speeds intermediate between FC 1 

### and FC 2 

### . FC 6 

### ozone levels were lower than either FC 1 

### or FC 2 

### and, like FC 1 

### , FC 6 

### did not have detailed ai r quality data. Thus, all that can be deduced is that c onditions (either meteorology or ozone precursors) were not as amenable to ozone formation in cluster 6. Cluster 5 Cluster 5 is set apart from the ot her clusters by the st rength of its transport and the direction (NE) of its origins. With air or iginating in northeast Tennessee du ring the 12 hours preceding arrival at Look Rock, it is most likely that FC 5 

### ozone levels were influen ced by sources near Kingsport, TN. No detailed air quality data were available. Clusters 3 and 4 Clusters 3 and 4 are unique in that they have the highest transport speeds during the 12 hours preceding arrival at Look Rock and originate fr om well south of Look Rock over north central Georgia. Ozone levels are relatively high, NO y 

### and CO levels are moderate, and τ is high. These clusters could be associated with emissions east of Atlanta and are definitely not due to emissions anywhere near Look Rock. Clusters 7 and 8
Clusters FC 7 

### and FC 8 

### share several features--both origin ate southeast of Look Rock, both have moderately high ozone and CO leve ls and both have relatively high NO y 

### levels. The primary differences are in transport speeds/distances and τ . FC 7 

### is associated with very aged air (high τ ) and high transport speeds; 12-hr airmass origin s are over extreme northeast Georgia and extreme western South Caroli na. However, FC 8 

### is associated with the lowe st transport speeds of any cluster and the largest direc tional divergence between 10- a nd 100-m trajectories. Airmass origins are within 30 km of Look Rock, esse ntially over the Great Smoky Mountains National Park (GSMNP) and nearby national forests and wild erness areas. There are no significant source regions in this area. Despite this, τ was lower for FC 8 

### than any other cluster and this implies a nearby source of NO. Given the transport directi ons and low winds it is likely that Look Rock air quality in cluster 8 was influenced by emissions from the small Happy Valley community east of the Look Rock/Foothills Parkway (Chi lhowee Mountain) and west of GSMNP and, perhaps to some extent, by the Look Rock ca mpground east of the air monitoring station. Emissions from fireplaces, wood stoves and campf ires could contribute the relatively fresh NO emissions and moderate CO levels that were measured.

### 6 Clusters 9 and 11
Clusters FC 9 

### and FC 11 

### share a common transport directio n (WSW) and moderately low high ozone levels. However, they differ considerably in their transport speeds and other air quality characteristics. FC 9 

### has low NO y 

### but high τ and CO. Given the 12-hr transport distances and directions it is likely that FC 9 

### events were influenced by Chattanooga emissions. The relatively high CO levels may reflect the fact that FC 9 

### trajectories follow the Chattanooga-Knoxville transportation and industria l corridor for much of the 12-hr peri od prior to arriva l at Look Rock. FC 11 

### events follow similar paths but tran sport speeds are lower and both CO and τ are lower than for FC 9 

### . The lower FC 11 

### speeds put the Chattanooga source region further upwind in time than for FC 9 

### . The lower τ for these events implies that more nearby sources are important than for FC 9 

### events and the lower CO suggests that they are not mobile sources. FC 11 

### comprises the largest single cluster with 30 percent of all computed trajectories. Cluster 10 Trajectories for cluster 10 originate in north west Georgia 12 hours upwind of Look Rock. This region does not have large urban areas but it does include a variety of industrial facilities and electric generating stations. Air quality data suggest that these moderately low high ozone events are associated with m oderate levels of emissions. Summary A cluster analysis of high ozone events at Lo ok Rock provides insight into the sources and conditions associated with various categories or clusters of events. The data suggest that, out of 11 distinct clusters, only 4 (FC 1 

### , FC 2 

### , FC 5 

### and FC 6 

### ) are likely to have any contributions from the Knoxville urban area. Of these 4, one (FC 5 

### ) has such strong transpor t from the northeast that airmasses spend very little time over Knoxville-area emissions sources. Of the remaining 3 clusters, FC 1 

### has the highest ozone levels and th e greatest potential for Knoxville-area contributions because of the relatively long time spent by sampled air par cels traveling across the urban source region. Clusters 1, 2 and 6 with the highest potential impacts from the Knoxville area comprise 35 percent of the co mputed air parcel trajectories associated with Look Rock high ozone events. In other words, 65 percent of th e Look Rock high ozone even ts are not associated with or significantly impact ed by Knoxville-area emissions.
Reference Wilks, D.S. Statistical Methods in the Atmospheric Sciences , Academic Press, New York, 2006, 549-559.

### 7 Figure 1. Cluster-averaged 10- and 100-m trajector y locations at 12 ho urs upwind of Look Rock during high ozone events. Locations are labeled by clus ter number. Pink ovals denote ozone precursor source regions at 12 hours prior to arrival at Look Rock.

### 8 Figure 2. Comparison of cluster averaged 8-hr oz one mixing ratios for periods centered on the maximum observed one hour ozone value on L ook Rock high ozone event days. Note that this is not the same as the daily maximum 8-hr average ozone value. 

# 70 75 80 85

1 2 3 4 5 6 7 8 9 10 11 ppb

Cluster All Events 9 Event Subset

### 9 Figure 3. Comparison of cluster averaged maximu m hourly ozone mixing ratios observed at Look Rock on high ozone event days. 

# 75 80 85 90 95

1 2 3 4 5 6 7 8 9 10 11 ppb

Cluster All Events 9 Event Subset

### 10 Figure 4. Cluster average computed trajectory di stances upwind of Look Rock at 12 hr preceding arrival at Look Rock during high ozone ev ents for trajectories arriving at a height 10-m above the destination. 

# 0 50 100 150 200

1 2 3 4 5 6 7 8 9 10 11 km

Cluster All Events 9 Event Subset

### 11 Figure 5. Cluster average computed trajectory distances upwind of Look Rock at 12 hr preceding arrival at Look Rock during high ozone ev ents for trajectories arriving at a height 100-m above the destination. 

# 0 50 100 150 200 250

1 2 3 4 5 6 7 8 9 10 11 km

Cluster All Events 9 Event Subset

### 12 Figure 6. Cluster average NO y 

### mixing ratios for 8-hr period s centered on the daily maximum hourly ozone mixing ratio measured dur ing high ozone events at Look Rock. 

# 0 2 4 6 8

1 2 3 4 5 6 7 8 9 10 11 ppb

Cluster

### 13 Figure 7. Cluster average CO mixing ratios for 8- hr periods centered on the daily maximum hourly ozone mixing ratio measured dur ing high ozone events at Look Rock. 

# 0 100 200 300 400 500

1 2 3 4 5 6 7 8 9 10 11 ppb

Cluster

### 14 Figure 8. Cluster average photochemical age ( τ ) for 8-hr periods centered on the daily maximum hourly ozone mixing ratio measured during high ozone events at Look Rock. 

# 0.6 0.7 0.8 0.9

1 2 3 4 5 6 7 8 9 10 11NOz/NOy



# Cluster9125915.11 

### Appendix 4 TVA’s “2008 Environmental Policy.”tennessee valley authority 

# 2008 E nvironmental PolicyMessage from the CEO 1

Chapt e r 1 – Environmental P olicy 2 Background 2 Environmental P olicy 2 Guiding P rinciples 3 P olicy Development 3 Stakeholder Involvement 3

Chapt e r 2 – Environmental Objectives and Critical Success Factors 4 Chapt e r 3 – Environmental A reas 6 Climate Change Mitigation 6 A ir quality Improvement 8 Water R esource P rotection and Improvement 9 Waste Minimization 10 Sustainable Land Use 10 Natural R esource Management 11

Chapt e r 4 – Commitments 12 Commitments to Our Customers 12 P erformance Indicators 12

Online R esources 12

C HA I R M A N WILLI A M S A NSOM of Knoxville, Tennessee, is chairman and chief executive officer of The H.T. Hackney Co., and has held that position since 1983. Hackney is a diversified company involved in wholesale grocery, gas and oil, and furniture manufacturing.

DENNIS BO TT O R FF of Nashville, Tennessee, serves as chairman and partner of Council Ventures, a venture capital firm. He was chairman of AmSouth Bancorporation until his retirement in 2001 and previously was chief executive officer of First American Bank.

DON DE PR IES T of Columbus, Mississippi, is chairman of a venture capital firm headquartered in Alexandria, Virginia, that has founded or invested in such companies as American Telecasting, now merged with Sprint. His Charisma Communications Corp. was a pioneer in the cellular phone business. He previously chaired the Columbus, Mississippi, Utilities Commission.

MIKE DUNC A N of Inez, Kentucky, is chairman, chief executive officer, and director of Community Holding Co.; chairman, CEO, and director of Inez Deposit Bank; and chairman of the Republican National Committee. He is a director of the Regional Center for Rural Development.

TH OM A S GILLIL A ND of Blairsville, Georgia, recently retired as executive vice president, general counsel, and secretary of United Community Banks Inc. He is a former chief of staff to Georgia Lt. Gov. Pierre Howard, and he served as chairman of the Stone Mountain Authority under Georgia governors Roy Barnes and Sonny Perdue.

SKIL A HARR IS of Washington, D.C., is a native of Bowling Green, Kentucky, and served as a full-time TVA director from November 1999 through March 2006. She previously held positions in the U.S. Department of Energy, the White House, and energy-management and engineering-consulting firms.

H OW AR D THRA ILKILL of Huntsville, Alabama, recently retired as president and chief operating officer of Adtran, Inc., in Huntsville, which supplies equipment for telecommunications service providers and corporate end-users. Previously, he was president and chief executive officer of Floating Point Systems. 

# The TVA Board Table of Contents

# Message from the CEO
Stewardship of the T ennessee Valley 

### We are very much aware of the impact that the T ennessee V alley A uthority’s operations have on the environment, and we are working in partnership with others to further the region’s environmental quality. I n fulfilling its historic mission, TVA has contributed to the region’s economic progress by meeting an ever-increasing demand for electricity while significantly reducing its impact on the environment. Y et, we recognize that greater challenges lie ahead to meet higher environmental standards and ensure the finite water and land resources under our stewardship are available for future generations.

T he annual demand for electricity in the TVA service region is forecast to grow more than the national average. T o offset the impact of meeting this demand, we are increasing our efforts in energy efficiency to reduce demand growth, investing in lower-carbon generating sources for meeting any additional growth, and lowering emissions from our current generating plants. T his approach will help us improve performance and be proactive in our environmental stewardship responsibilities, while meeting the demand for more power at an affordable cost. H owever, future decisions to take further actions in these areas could put an upward pressure on power rates.

T his policy sets out environmental objectives that will help us make decisions about our business and identifies areas that will allow TVA to produce cleaner and still-affordable electricity and provide environmental leadership in partnership with our stakeholders. We are establishing this policy because I , and all the people at TVA , appreciate the opportunity to provide cleaner power to you and your family now and in the generations to come.

T om Kilgore President and Chief E xecutive O fficer

TVA Environmental Policy 1Chapter 1 

# Environmental Policy

BACKGROUND As stated in the 2007 TVA Strategic Plan, “TVA will be proactive in addressing environmental concerns, including those related to global climate change.” This Environmental Policy provides board-level guiding principles to successfully lead TVA to reduce its environmental impact while continuing to provide reliable and competitively priced power to the Valley. There is a growing recognition of the environmental and economic need for an increased emphasis on actions that support sustainable initiatives to most effectively meet the three dimensions of the TVA mission. In the Strategic Plan, about half of the identified strategic objectives and critical success factors relate directly to TVA’s environmental-related activities and policy-making. Following the release of the Strategic Plan, the board asked for the development of an integrated environmental policy to outline objectives and critical success factors across the multiple areas of TVA’s activities. The policy also addresses TVA’s response to the uncertain future of legislation on greenhouse gases (GHGs), including carbon, and the scarcity of available mitigating technologies in a carbon-constrained future.

E NVI R ONM E N TA L P OLICY T V A ’s overarching Environmental P olicy objective is to provide cleaner, reliable, and still-affordable energy, support sustainable economic growth in the T ennessee Valley, and engage in proactive environmental stewardship in a balanced and ecologically sound manner. 

### I n this context, the E nvironmental Policy directly aligns with the threefold TVA mission of E nergy, E conomic Development, and E nvironment, and as shown in the center of E xhibit 1, accents and integrates environmental leadership into all aspects of the TVA mission.

T he E nvironmental Policy itself is not intended to serve
as TVA ’s response to future environmental regulations, nor is it intended to outline a specific regulatory forecast for planning purposes. R ather, the policy establishes an overarching framework to guide decision-making and future strategic development. T he board of directors will review the E nvironmental Policy every two years. More frequent reviews may be needed to respond to significant market and regulatory changes and ensure alignment with TVA ’s strategic priorities.
Cleaner, reliable, and still-affordable energy 

### TVA has an enduring responsibility to deliver reliable and affordable power to the residents and businesses in the T ennessee V alley. We have made investments to comply with environmental regulations in an efficient and affordable manner. We recognize the challenge ahead to achieve continuous improvements to make our generation portfolio cleaner while still meeting our commitment to a reliable and affordable energy supply.
Sustainable economic development 

### Growth is an important component of maintaining the economic vitality of the T ennessee V alley, and TVA is committed to continued leadership in economic E xh i b i t 1 Overall Environmental P olicy A lignment With T V

A

’s Mission

2 TVA Environmental Policy

### development. We recognize unplanned growth can place great demands on all of our resources and lead to outcomes that can erode the quality of life within the T ennessee V alley. We believe the solution lies in achieving sustainable community and economic growth while considering environmental impacts.

P roactive environmental stewardship 

### L ooking forward, we see the magnitude of the environmental challenges growing larger and requiring increasing innovation and leadership to find practical, effective, and affordable answers to our stewardship challenges. T o meet the environmental challenges of the 21st century and beyond, we must be proactive in our commitment toprovide both affordable energy and environmental stewardship. We must work together to reduce the “footprint” we all impose upon the environment.

GUIDING PR INCI P L E S 

### TVA will continue to integrate responsible environmental practices into its business operations by establishing goals, measuring progress, and reporting performance through a comprehensive environmental management system. E mployees are trained on their environmental responsibilities and factor environmental considerations into business decisions. TVA remains committed to complying with environmental laws and regulations, with a goal of continuous improvement.
Climate Change Mitigation 

### TVA plans to actively reduce its carbon emissions through cleaner energy options and energy efficiency initiatives.

A ir Quality Improvement 

### TVA improves regional air quality by installing emission control equipment on existing generation and planning for cleaner future energy options.

Water R esource P rotection and Improvement 

### TVA manages an integrated river system for multiple uses while striving to provide clean and sufficient water for the V alley’s needs.

Waste Minimization 

### TVA surveys all aspects of its operational and business functions to implement ways to reduce waste and increase recycling. Sustainable Land Use 

### TVA manages public lands for multiple benefits, striving to keep them in good environmental health while balancing the need for sustainable development.

Natural R esource Management 

### TVA protects natural resources while providing recreational opportunities across the V alley.

P OLICY D E V E LO P M E N T 

### T he development of the E nvironmental Policy followed four phases. T he first phase identified the key environmental focus areas and established an overarching framework for the policy. T he evaluations performed in the second phase analyzed market forces and established a range of possible regulatory outcomes, highlighting the potential impacts of both on TVA

. T he third phase defined a series of environmental objectives and identified the critical success factors necessary to meet those objectives. T he fourth phase asked for public comments and incorporated those comments into the final document, subject to approval of the policy by the TVA Board of Directors.

S TA K EH OLD ER INVOLV E M E N T 

### TVA ’s evaluation of stakeholders’ suggestions and feedback revealed four emerging themes they believe TVA should emphasize:
Leadership 

### TVA must take a leadership position in areas of its core competency such as nuclear power and hydroelectric power.

P artnerships 

### TVA should expand partnership opportunities with stakeholders, such as local, federal, and state institutions, in specific focus areas.

Coordination 

### TVA should leverage its credibility and position as a federal agency to foster coordination among multiple parties to achieve common goals.

Commitment 

### TVA should clearly articulate its environmental commitment, preferred strategies for least-cost solutions, and associated performance metrics.

TVA Environmental Policy 3C lim ate c ha ng e mi t ig at ion Environmental Objective TVA will stop the growth in volume of emissions and reduce the rate of carbon emissions by 2020 by supporting a full slate of reliable, affordable, lower-carbon-dioxide (CO 2 ) energy-supply opportunities and energy efficiency.
Critical Success Factors •	 Reduce load growth by at least one-fourth over five years, through energy efficiency and demand-side management initiatives. •	 Meet the remaining load growth through lower-carbon-emitting energy sources such as affordable renewables, nuclear, and combined heat and power. •	 Improve the efficiency of the transmission network, including the use of technologies such as Smart Grid, which helps achieve environmental benefits through improved communication and remote control, making the system more responsive in real time. •	 Strive to reduce the rate of carbon and other GHG emissions from the existing generation fleet. •	 Use affordable regional resources to comply with renewable and clean-energy standards and mandates, limiting the use of purchased compliance credits. •	 Invest in a technology portfolio that supports low- or zero-carbon emitting generation options and electricity grid infrastructure to support a lower-carbon economy. •	 Promote public education and outreach to encourage energy effi

ciency, clean end-user energy generation, premium green-energy offerings, and regional climate change mitigation opportunities. Ai r q u a li t y im pr ov e m e n t Environmental Objective TVA will continue efforts to reduce sulfur-dioxide, nitrogen-oxide, mercury, and particulate emissions and engage regional and national stakeholders to develop better ways to understand, monitor, and improve regional air quality, including all regulated air emissions.

Critical Success Factors •	 Reduce emissions across the system by continuing to install emission reduction equipment and new technology to control over 80 percent of fossil generation in the next 10 years. •	 Allow for earlier retirement of coal-fired plants if energy efficiency, renewables, and clean-energy gains exceed targets. •	 Elevate air quality improvement as a critical component in evaluating future capacity-planning decisions. •	 Promote open exchange and collaboration with others to improve the industry’s air quality control technology and modeling. Chapter 2 

# Environmental Objectives and Critical Success Factors
The Environmental Policy is organized into six environmental areas that encompass the variety of issues faced by TVA. These areas are climate change mitigation, air quality improvement, water resource protection and improvement, waste minimization, sustainable land use, and natural resource management.

4 TVA Environmental PolicyWater re sou r c e pr o te c t ion a nd im pr ov e m e n t Environmental Objective TVA will improve reservoir and stream-water quality, reduce the impact of its operations, and leverage alliances with local and regional stakeholders to promote water conservation.
Critical Success Factors •	 Mitigate TVA’s impact on aquatic systems while balancing thermal cooling needs with consumptive use. •	 Demonstrate a sustainable reduction of consumptive use of water at TVA’s metered facilities. •	 Integrate the impacts of water quality and quantity into the long-range planning and decision-making process. •	 Maintain river system infrastructure for safe operation while operating in compliance with the operating policy from TVA’s Reservoir Operations Study (ROS). •	 Promote the integration of energy efficiency and water con
servation into community planning and building construction. •	 Collaborate in community outreach and partnerships through voluntary demonstrations of the efficient use of water resources and protection of water quality.

Wa s te minimi zat ion Environmental ObjectiveTVA will drive increased sustainability in existing compliance programs and waste management practices by focusing on wasteavoidance, minimizing waste generation, and increasing recycling to reduce environmental impacts.
Critical Success Factors •	 Reduce the waste footprint of all TVA facilities by pursuing operational and business practices to decrease waste generation and improve recycling. •	 Increase the percentage of recycled coal-combustion waste. •	 Minimize low-level nuclear waste and contribute to efforts by industry groups and agencies to formulate innovative and sustain

able solutions for the management of spent nuclear fuel waste. •	 Further reduce the risk of polychlorinated biphenyl (PCB) releases to the environment over time by eliminating use of PCBs in large electrical equipment. S us ta in ab l e l a nd us e
Environmental Objective TVA will strive to maintain the lands under its management in good environmental health, balancing their multiple uses, and will improve its land transaction processes to support sustainable development.
Critical Success Factors •	 Actively manage TVA lands to meet the desired conditions for their purpose as defined in the Reservoir Land Management Plans. •	 Develop a policy for managing TVA’s mineral rights that considers the potential environmental impacts. •	 Improve reservoir shoreline conditions through collaborative partnership initiatives and balance the multiple uses of the reservoirs in accordance with TVA’s Land Policy and Shoreline Management Policy. •	 Manage TVA lands, mineral rights, and shoreline access to better achieve environmental commitments while meeting the needs for recreation, residential access, and economic development.

Nat u ra l re sou r c e m a n a g e m e n t
Environmental Objective TVA will be a leader in natural resource management through the implementation of sustainable practices in dispersed recreation while balancing the protection of cultural, heritage, and ecological resources.
Critical Success Factors

• Allow for properly managed, eco-friendly dispersed recre
ation while balancing the protection of biological, cultural, and heritage resources. •	 Promote ecological diversity and wildlife habitats on TVA lands through partnerships and voluntary initiatives. •	 Increase the level of environmental quality and management consistency among TVA-managed and -leased recreation facilities.

TVA Environmental Policy 5

### Greenhouse gases are produced by many natural and industrial processes. I n order of abundance, the top four gases are water vapor, C O 2 

### , methane, and nitrous oxides. G H Gs are important to maintaining the temperature on the earth. O ver the past decade, the impact of man-made G H G emissions has been the focus of much scientific, business, and policy debate in the U nited S tates and abroad. Man-made C O 2 

### originates primarily from fossilfuel combustion for transportation, electricity generation, and industrial processes, accounting for more than 80 percent of the nation’s total G H G emissions. Forty percent of the nation’s C O 2 

### emissions can be directly attributed to electricity generation.

TVA is a large emitter in the power sector due to the size of its fossil generation portfolio. H owever, about 30 percent of TVA ’s current generation comes from non-carbon-emitting sources — nuclear, hydropower, and renewables – and that figure is forecast to be over 50 percent by 2020. TVA ’s generating portfolio emissions “intensity” (tons-ofC O 2 

### -per-megawatt-hour) is near the national average and considerably better than that of most utilities in the S outheast.

L egislation has been introduced in the U nited S tates Congress requiring reductions of G H G emissions, specifically focusing on C O 2


### . I f enacted, such legislation could result in significant additional costs for TVA

. T o prepare to respond to this issue, TVAhas undertaken a study of the opportunities to reduce G H G emissions in the V alley. I n order to understand the cost-effectiveness of TVA ’s available actions relative to others within the V alley economy, TVAhas created a comprehensive catalog of specific opportunities to reduce G H Gs and estimated the corresponding volumes and relative costs associated with each. T hose opportunities for carbon abatement that are within TVA ’s control or influence are shown with dark-green bars. Preliminary output from this analysis is depicted in E xhibit 2 on the next page. Chapter 3 

# Environmental Areas

CLIM ATE C HA NG E MI T IG AT ION

6 TVA Environmental PolicySource: TVA – Team analysis E xh i b i t 2 T

ennessee Valley’s Carbon A batement Opportunities and T V

A

Opportunities ( T

V

A

shown as dark-green bars)

-40 -20

-120 -100

80
60
40
20 0 10 20 30 40 50 60 70 80 90 10 0 1 10 12 0 1 30 14 0 1 50 16 0 1 70 18 0 1 90 200 Abatement cost 2008 $/ton CO 2 equivalent

-80 -60 Buildings – shell retrofit Hybridization – light duty vehicl e

Gas plants dispatch Coal rebuild with carbon capture and storage Dedicated biomass

Agricultural N 2 O

management

Wind Additiona l hydro unit s Nuclear ne w builds – future

Buildings – commercial CHP Large hydro unit s on unpowered dam Industrial CHP

Agricultural – CH4 management Buildings – water heaters

Biomass cofiring Nuclear constructio n completion

H ybridization – medium and heavy trucks Nuclear new builds – planned Waste heat recovery

Natural gas systems – CH4 m anagement Buildings – HVAC equipment efficiency Land fill – CH4 management

Appliances Plug-in hybrids – light duty vehicle

Manufacturing – HFCs management Industrial N 2 O management Soil management

Fuel economy package – medium and heavy trucks Land fill gas Coal mining – CH4 management

Nuclear start-up

Industrial process improvement

Cellulosic biofuels Buildings – refrigeration Heat rate improvement Hydro modernization

Buildings – new shell improvement

Nuclear licens e extension

Buildings – lighting

Industrial steam system improvement Buildings – electronics Fuel economy package – light duty vehicle Buildings – controls systems

Industrial product recycling and recovery Solar PV

Opportunities TV A could exercise or influence Electric moto r systems improvement Afforestation an d forestry management

Abatement volume Million tons CO 2 equivalent/yr



### T he abatement curve visualized in E xhibit 2 illustrates the range of actions the V alley can take to reduce carbon emissions, including non-C O 2 

### gases. E ach bar denotes a single type of opportunity to reduce carbon emissions or increase carbon absorption. T he width of the bar repre

sents the total net annual emissions reduction that would result from pursuing the opportunity. T he height of the bar highlights the cost of pursuing each option relative to the costs that would be incurred if the current practices were maintained. S equencing the options from least cost to highest cost helps provide a sense of the relative prior

ity of the abatement measures and can be used to identify the least-cost approach to achieving any targeted level of emissions reduction.

T he shape of the curve warrants explanation. T he soci

etal costs associated with each measure can be positive or negative in the aggregate. T he benefits received are spread over time to one or more beneficiaries who may be different from those making the initial investments. A “negative cost” implies that pursuing the related option will result in a net savings over the life cycle of the oppor

tunity relative to what would be incurred in the businessas-usual case. T hese savings are frequently the result of reduced energy costs associated with improved energy efficiency. T he positive cost options require an incremen

tal expense to abate emissions above and beyond the business-as-usual case.

TVA Environmental Policy 7

### TVA is a regional leader in the installation and operation of air emission control equipment through an aggressive investment of more than $4.8 billion. T his investment has reduced TVA ’s sulfur-dioxide emissions by about 83 percent since 1977, and lowered nitrogen-oxide emissions during the summer ozone season by 81 percent since 1995. A s an additional benefit of these controls, mercury emissions also have been reduced. TVA ’s efforts have contributed to continued air quality improvement across the region. T hese improvements are important to the quality of life and economic sustainability in the V alley. T he fundamentals of TVA ’s program focus on complying with air pollution control requirements, considering air-quality impacts on urban and environmentally sensitive areas, and supporting stakeholder interests. TVA ’s Clean A ir Program is based on a strategy of self-compliance that involves the installation of controls on fossil plants to achieve tangible air quality and health benefits for V alley citizens with a limited use of the allowance markets. Despite these successes, work remains. E P A ’s Clean A ir I nterstate R ule, more-restrictive N ational A mbient A ir Quality S tandards, and future mercury and regional haze requirements will ensure that regional air quality continues to improve. I n the ongoing effort to contribute to that improvement, TVA will continue to reduce its sulfur-dioxide, nitrogen-oxide, mercury, and particulate emissions. We will pursue this objective by continuing to invest in assets that A I R Q U A LI T Y IM PR OV E M E N T

8 TVA Environmental Policy Five key insights have emerged from this analysis that are of critical relevance to T V A ’s Environmental P olicy: •	 A significant amount of energy-efficiency potential exists within the Valley and requires a corresponding level of investment to realize that potential. •	 Nuclear power options available to TVA can provide significant abatement potential at a modest incremental cost. •	 Compared to other regions, the Valley has a limited supply of renewable energy to support carbon and clean-energy objectives. •	 Coal generation remains an important resource to meet T V A ’s mission to deliver low-cost power. •	 Modern transmission and distribution grid technologies can help support the transition to a lower-carbon energy supply by improved real-time information and controls. 

### Given the potential for legislation that will require TVA to find ways to reduce G H G emissions – particularly carbon emissions – we must position TVA to address the challenge of operating in a carbon-constrained world. S pecifically, TVA will continue to reduce the carbon intensity of its generating system and take advantage of lower-C O 2 

### -emitting energy sources consistent with maintaining a reliable and affordable energy supply. T echnology innovations will be needed to address the intermittency of many renewable generation sources. TVA will target reducing load growth by at least one-fourth in five years through energy efficiency and demand response while meeting the remaining load growth through lower-carbon-emitting options.

### TVA operates the T ennessee R iver S ystem to provide a wide range of public benefits: year-round navigation, flood-damage reduction, affordable electricity, improved water quality, water supply, land use, and recreation.

I n 2004, the TVA Board approved a new operating policy based on the results of the agency’s R eservoir O perations S tudy. T he policy maintains TVA ’s ability to meet its fundamental responsibilities for flood control, commercial navigation, and power production while protecting water quality and accommodating the increased demands created by recreational and residential growth. I t shifts the focus of TVA ’s reservoir operations from achieving specific summer pool elevations on the reservoirs to managing the flow of water throughout the river system in an integrated way to support multiple demands.

TVA pursues its progressive management of water quality and water quantity impacts through the permitting of activities on and around TVA reservoirs; the collection, maintenance, and distribution of water quality information; targeted water quality improvement initiatives; and strategies to manage increased water demand.

T he increasing demand for water due to residential, commercial, and industrial growth requires a focus on resource conservation in the T ennessee V alley region. I n addition, chronic rainfall deficits can result in low water flows, which could lead to future constraints on power operations. R apid growth coupled with the challenge of availability further amplifies the importance of balancing resource management activities for multiple, and often competing, uses across the V alley. Facing these challenges, TVA will lead by example. TVA will demonstrate an efficient use of water in its operations and will collaborate and coordinate with internal and external stakeholders to protect and improve water quality and sufficiency, while maintaining an in-depth knowledge of changing conditions in the river system. TVA ’s goal is to mitigate its impact on aquatic systems while balancing thermal cooling needs with consumptive use. A t the same time, TVA will continue to improve river system operations to balance diverse demands. W ATER RE SOU R C E pr o te c t ion a nd IM PR OV E M E N T

TVA Environmental Policy 9 

### will measurably reduce emissions from fossil-fired plants and thereby improve air quality. T his investment will reduce emissions across the system through the installation of emission reduction equipment and new technology to control over 80 percent of fossil generation in the next 10 years. I t’s possible that, if energy efficiency efforts yield higher load reductionsthan forecast, we will have an opportunity to retire higheremitting fossil plants earlier. I n addition, TVA will continue to engage regional and national stakeholders to develop better ways to understand, monitor, and improve regional air quality.SUS TA IN AB L E L A ND US E



### TVA manages public lands for multiple benefits, including economic development, conservation, and recreation. TVA is the steward of 293,000 acres of public land and 11,000 miles of shoreline in the V alley along the T ennessee R iver. I n addition, TVA maintains 293,000 acres of flowage easement rights, 258,000 acres of transmission rights-of-way, 35,000 acres of facility properties, and 159,000 acres of mineral rights. When deciding the proper uses of TVA -managed lands and shoreline or acquiring properties for its operations, TVA , while ensuring compliance with appropriate laws and regulations, considers the effects of these activities on the environment.

S ection 26a of the TVA A ct gives TVA permitting jurisdiction over proposed construction in and along the T ennessee R iver and its tributaries. U nder this jurisdiction, TVA has the responsibility to address obstructions that might affect navigation, flood control, and public lands.

I ncreasing growth within the region necessitates a balance of resource conservation, sustainable economic development, and eco-friendly recreation. T o demonstrate and promote best practices in sustainable land use, TVA intends to lead by example. I t will maintain the public lands under its management in good environmental health to support multiple uses in meeting diverse stakeholder expectations. I t will also improve its acquisition, development, and disposal of managed lands to support sustainable development in the V alley.

T hese efforts will align with TVA ’s L and Policy, approved by the TVA Board in N ovember 2006, and its S horeline Management Policy, approved by the board in June 1999.

10 TVA Environmental Policy 

### TVA manages an array of different wastes, including municipal solid waste, wastewater, hazardous waste, low- and high-level nuclear waste, other regulated wastes (e.g., asbestos and PCBs), scrap metal, office waste, and coal-combustion waste, which includes fly ash, bottom ash, and gypsum. O ne of TVA ’s strengths is its waste management system and the day-to-day implementation of this system at the various facilities by trained environmental personnel. E mployees help integrate waste-management expertise at every level of TVA to minimize the impact on V alley resources.

TVA has a strong focus on the use of coal-combustion waste, which comprises its single largest waste stream. A pproximately 43 percent of this waste is recycled into by-products. S imilarly, TVA recycles the majority of its electronic waste and scrap metal. While focusing on compliance with waste requirements, TVA uses a teamapproach to seek out and implement further wasteminimization opportunities. I n addition, the agency is collaborating with others to identify sustainable solutions for better management of nuclear waste.

TVA will reduce its waste footprint in regulated materials and increase the percentage of recycled coal-combustion waste. I n this effort, TVA will augment its existing compliance programs and waste management practices by focusing on waste reduction at the source (in part through improved procurement practices), avoiding waste generation, and increasing recycling efforts (especially of municipal waste). W A S TE MINIMI ZAT IONN AT U RA L RE SOU R C E M A N A G E M E N T



### TVA manages natural resources in the V alley while providing for many types of recreational opportunities. T he agency has set aside more than 181,000 acres of public land for natural resource management, which includes the enhancement of wildlife habitat and dispersed informal recreation. TVA also oversees and manages an additional 31,000 acres for sensitive resources. T he guidelines for use of these sensitive land resources include restrictions on activities that might endanger significant cultural or natural features.

TVA has more archaeological sites per acre under its management than any other federal agency—over 10,000 archaeological sites have been identified on TVA -managed lands. S ince 1976, TVA has maintained information on rare plants and animals, caves, and other environmentally sensitive resources in the 80,000-square-mile TVA service area.

I n its approach to natural resource management, TVA will demonstrate leadership through the ecologically sound management of natural resources and the protection of cultural and heritage resources. TVA is committed to increasing the proportion of TVA -managed resources that meet the desired environmental conditions of sustainable recreation, ecological diversity, and cultural resource protection. More and more residents and visitors are enjoying the diverse, unique natural resources of the V alley by engaging in dispersed recreation activities such as hiking, bird watching, and fishing. A n increase in outdoor activity has been shown to result not only in a healthier lifestyle but also a greater awareness of the importance of natural resource conservation. A n increase in conservation practices by the public helps ensure the unique and beautiful V alley resources will be preserved for the continued enjoyment of generations to come.

T o support this objective, TVA will pursue collaboration and partnerships to improve the delivery of its natural resource management activities, while also increasing the effectiveness of dispersed public recreation and reducing the impact of human uses on the environment. TVA will allow for properly managed, eco-friendly dispersed recreation on the lands it manages while balancing that goal with the protection of biological, cultural, and heritage resources.

TVA Environmental Policy 11 

### T hese policies direct TVA to manage and balance the multiple uses of lands under its jurisdiction and use its environmental decision-making process to minimize the environmental liabilities and impacts and ensure compliance. TVA will continue to actively manage its public lands to meet the desired conditions for their defined purpose, and it will also develop a policy for managing mineral rights that considers the potential environmental impacts.Chapter 4 

# Commitments

COMMI T M E N T S T O OU R CUS T OM ER S 

### I n collaboration with our 159 distributors, TVA is committed to providing low-cost, reliable power to more than 8.8 million residents and businesses and 62 directly served large industrial and federal facilities in the seven states of the T ennessee V alley. TVA ’s new E nvironmental Policy, in accordance with the 2007 TVA S trategic Plan, emphasizes three issues that are important from its customers’ perspective: maintaining affordable rates, expanding collaboration, outreach, and education, and furthering the V alley’s quality of life.

A ffordable rates 

### •	 TVA will strive to manage potential future rate increases for new generation and transmission construction by collaborating with distributors and customers to pursue lower-cost energy-efficiency and load-management options that may partially offset the need for capacity additions. •	 For large commercial and industrial customers, TVA will continue to focus on rates as a principal measure of affordability and competitiveness when promoting cost-effective energy-efficiency and load-management programs. •	 For residential and small commercial customers, TVA will emphasize the total bill impact by focusing on the combined effect of rate and consumption.
Collaboration, outreach, and education 

### •	 TVA will increase its focus on education and outreach to inform V alley residents on key issues, including energy efficiency and renewables, water conservation, and natural resource protection. •	 TVA will collaborate with distributors and directly served customers to implement enabling technologies for clean-energy and energy-efficiency solutions.
Quality of life 

### •	 TVA will continue to promote an improved quality of life with an emphasis on the deployment of clean, low-carbon emissions technology in the V alley. •	 TVA will consider the environmental footprint of industries recruited into the V alley. •	 TVA will improve air quality and continue to promote the sustainable management of land, water, and natural
resources. •	 TVA will provide for the expansion of ecologically friendly recreation activities within the V alley.

PER FO R M A NC E INDIC AT O R S 

### TVA has an established set of metrics to monitor how well its performance fulfills the threefold TVA mission highlighted in the 2007 S trategic Plan, which outlines the policy level direction for TVA

. E xamples of these metrics are shown in E xhibit 3 on the next page. T hey include the metrics that are found in TVA ’s S trategic Plan, such as delivered cost of power, economic development index, and environmental performance, and additional ones associated with the E nvironmental Policy. T his combined set of performance metrics establishes the successful translation of the TVA E nvironmental Policy into specific and measurable indicators that can be monitored for implementation of the policy. TVA will implement these metrics in an integrated approach to close the gap between the current level and desired improvement in environmental performance.

12 TVA Environmental PolicyAffo r d ab l e, R e li ab l e En er gy

Sta nd ar d O f L iving

Qu a li t y O f L if e C l ea n er En er gy

Envi r onm e n ta l

Ste w ar ds h i p S us ta in ab l e

Gr ow th Economic De v e lo p m e n t E xh i b i t 3 A ligning T V

A

’s Mission With Environmental Commitments and P erformance Measures

T he large circles represent the threefold T V

A

mission, while the intersections of the circles represent a higher quality of life realized through an integrated approach of pursuing cleaner energy, promoting sustainable growth, and providing proactive stewardship.

TVA Environmental Policy 13 Sta nd ar d of L iving •	 Customer Satisfaction •	 TFO/Asset Value •	 Quality of Jobs •	 Recordable Injury Rate •	 Cultural Health Index Affo r d ab l e, R e li ab l e En er gy •	 Connection Point Interruptions •	 Equivalent Availability Generation Assets •	 Productivity

C l ea n er En er gy •	 Energy Efficiency Targets:

–P articipation in DSM Initiatives

– MW R eduction •	 Renewables Targets •	 Emission Rates (CO 2 , SO X , NO X , H g)

Envi r onm e n ta l Ste w ar ds h i p •	 Environmental Performance •	 Stream Miles Improvement •	 Waste Reduction •	 Recreational Use •	 Land Meeting Desired Uses Economic De v e lo p m e n t •	 Economic Development Index •	 Jobs Created and Retained •	 Environment Footprint of R ecruited Industries S us ta in ab l e Gr ow th •	 Average Retail Price of Power
T V A

Strategic P lan Metrics A dditional Environmental Metrics



# Online Resources
View this policy electronically at www.tva.com/environment/policy.htm View the 2007 TVA strategic plan at www.tva.gov/stratplan View the results of the Reservoir Operations Study at www.tva.gov/environment/reports/ros_eis/index.htm View TVA’s Land Management Policy at www.tva.gov/river/landandshore/land_policy.htm View TVA’s Shoreline Management Policy at www.tva.gov/river/landandshore/landuse_shore.htmT ennessee V alley A uthority | 400 W. S ummit H ill Drive | Knoxville, T ennessee 37902


### www.tva.com

This report is printed on 100% post-consumer recycled paper and uses soy-based inks. 08-157 5/08