The new 2001 meteorological data used for PM2.5 modeling were derived from an updated version of the MM5 model used for the 1996 meteorology used for proposal. The version of MM5 used for the 2001 simulation contains more sophisticated physics options with respect to features like cloud microphysics and land surface interactions, and more refined vertical resolution of the atmosphere compared to the version used for modeling 1996 meteorology. While there are currently no universally accepted criteria for judging the adequacy of meteorological model performance, EPA compared the 2001 MM5 model performance against the benchmark goals99 recommended by some commenters. The benchmark goals suggest that temperature bias should be 391 within the range of approximately + 0.5 degrees C and errors less than or equal to 2.0 degrees C are typical.

In general, the model performance statistics for our 2001 meteorological modeling are in line with the above benchmark goals. Specfically, the mean temperature bias of our 2001 meteorological modeling was approximately 0.6 degrees C and the mean error was approximately 2.0 degrees C. The evaluation of the 2001 MM5 for humidity ( water vapor mixing ratio) shows biases of less than 0.5 g/ kg and errors of approximately 1 g/ kg, which compare favorably to the goals of + 1 g/ kg for bias and 2 g/ kg or less error. Model performance for winds in our 2001 simulation was also improved compared to what has historically been found in MM5 modeling studies. The index of agreement for surface winds in the 2001 case equaled 0.86, which is far better than the benchmark goal of 0.60. The precipitation evaluation results show that the model generally replicates the observed data, but is overestimating precipitation in the summer months. More information about the model performance evaluation and the MM5 configuration is provided in the NFR AQMTSD.

Comment: Several groups criticized the lack of quantitative meteorological model evaluation data for the 1995 RAMS meteorological modeling used for episodic ozone modeling. 392 100 Hogrefe, C. et. al. " Evaluating the performance of regional scale photochemical modeling systems: Part 1 meteorological predictions." Atmospherics Environment, vol. 35 ( 2001), pp. 4159 4174. Response: A peer reviewed, quantitative evaluation of the RAMS model performance for this meteorological period is provided by Hogrefe, et. al. 100 This analysis was performed using RAMS predictions for June through August of 1995. The results show that the RAMS biases and errors are generally in line with past meteorological model simulations by other groups outside EPA. The EPA remains satisfied that the 1995 RAMS meteorological inputs for the three CAMx ozone modeling episodes are of sufficient quality and we have continued to use these inputs for the ozone analyses for the final rule.

Comment: The EPA received several comments on the episodes selected for ozone modeling. There was general criticism that the ozone modeling did not follow EPA's own guidance for the selection of episodes. Additionally, there was specific criticism that the episodes did not provide for a reasonable test of the 8 hour ozone NAAQS in some areas.

Response: The draft 8 hour ozone guidance recommends, at a minimum, that four criteria be used to select episodes which are appropriate to model. This guidance is generally intended for local attainment demonstrations, as opposed to regional transport analyses, but it does recommend that in 393 applying a regional model one should choose episodes meeting as many of the criteria as possible, though it acknowledges there may be tradeoffs. Given the large number of nonattainment areas within the ozone domain, it would be extremely difficult to assess the criteria on a area by area basis. However, from a general perspective, the 1995 episodes address all of the primary criteria, which include:

1) a variety of meteorological conditions; 2) measured ozone values that are close to current air quality; 3) extensive meteorological and air quality data; and 4) a sufficient number of days. More detail is provided in the NFR AQMTSD,

but here is a brief description of how each of the four primary criteria are met by the 1995 cases.

With regard to the criteria of meteorological variations, we have completed inert tracer simulations for each of the three 1995 episodes that show different transport patterns in all three cases. For example the June case involves east to west transport; the July case involves west to east transport; and the August case involves southto north transport. In a separate analysis to determine whether the 1995 modeling days correspond to commonly occurring and ozone conducive meteorology, EPA has applied a multi variate statistical approach for characterizing daily meteorological patterns and investigating their relationship to 8 hour ozone concentrations in the eastern U. S. Across 394 the 16 sites for which the analysis was completed, there were five to six distinct sets of meteorological conditions,

called regimes, that occurred during the ozone seasons studied. An analysis of the 8 hour daily maximum ozone concentrations for each of the meteorological regimes was undertaken to determine the distribution of ozone concentrations and the frequency of occurrence of each regimes. The EPA determined that between 60 and 70 percent of the episode days we modeled are associated with the most frequently occurring, high ozone potential, meteorological regimes. These results also provide support that the episodes being modeled are representative of conditions present when high ozone concentrations are measured throughout the modeling domain. For the second criteria,

EPA has completed an analysis which shows that the 1995 episodes contain observed 8 hour daily maximum ozone values that approximate recent ambient concentrations over the eastern U. S. Additional analyses performed by EPA and others have concluded that each of the three episodes involves widespread areas of elevated ozone concentrations.

The synoptic meteorological pattern of the July 1995 episode has been identified by one of the commenters as representing a classic set of conditions necessary for high ozone over the eastern U. S. While the ozone was not quite as widespread in the June and August 1995 episodes, these 395 periods also contained exceedances of the 8 hour ozone NAAQS in most portions of the region.

We believe that there is ample meteorological and air quality data available to support an evaluation of the modeling for these episodes. Specifically, there were over 700 ozone monitors reporting across the domain for use in model evaluation. As noted above, the model performance for these episodes compares favorably to the recommendations in EPA's urban modeling guidance. In addition, the modeling period is comprised of 30 days, not including model ramp up periods which is considerably more than is typically used in an attainment demonstration modeling submitted to EPA by a State. Finally, EPA's draft ozone guidance also indicates as one of four secondary criteria that extra weight can be assigned to modeling episodes for which there is prior experience in modeling. The 1995 CAIR ozone episodes have been successfully used to drive the air quality modeling completed for several recent notice and comment rulemakings ( Tier 2, Heavy Duty Engine, and NonRoad). Based on the analyses discussed above and the adherence to the modeling guidance, EPA is satisfied that the 1995 CAMx episodes are appropriate for continued use.

B. How did EPA Project Future Nonattainment for PM2.5 and 8 Hour Ozone? 396 1. Projection of Future PM2.5 Nonattainment a. Methodology for Projecting Future PM2.5 Nonattainment In the NPR, we assessed the prospects for future attainment and nonattainment in 2010 and 2015 of the PM2.5 annual NAAQS. The approach for identifying areas expected to be nonattainment for PM2.5 in the future involved using the model predictions in a relative way to forecast current PM2.5 design values to 2010 and 2015. The modeling portion of this approach included annual simulations for 2001 proxy emissions and for 2010 and 2015 Base Case emissions scenarios. As described below, the predictions from these runs were used to calculate relative reduction factors ( RRFs) which were then applied to current PM2.5 design values from FRM sites in the East. This approach is consistent with the procedures in the draft of EPA's PM2.5 modeling guidance.

To determine the current PM2.5 air quality for use in projecting design values to the future, we selected the higher of the 1999 2001 or 2000 2002 design value ( the most recent ambient data at the time of the proposal) for each monitor that measured nonattainment in 2000 2002. For those sites that were attaining the PM2.5 standard based on their 2000 2002 design value, we used the value from this period 397 as the starting point for projecting 2010 and 2015 air quality at these sites.

The procedure for calculating future year PM2.5 design values is called the Speciated Modeled Attainment Test ( SMAT). The test uses model predictions in a relative sense to estimate changes expected to occur in each major PM2.5 species. These species are sulfate, nitrate, organic carbon, elemental carbon, crustal, and un attributed mass.

The relative change in model predicted species concentrations were applied to ambient species measurements in order to project each species for the future year scenarios. We applied a spatial interpolation to the IMPROVE and STN speciation data as a means for estimating species composition fractions for the FRM monitoring sites.

Future year PM2.5 was calculated by summing the projected concentrations of each species. The SMAT technical procedures, as applied for the NPR, are contained in the NPR and NPR AQMTSD.

As noted above, the procedures for determining future year PM2.5 concentrations were applied for each FRM site.

For counties with only one FRM site, the forecast design value for that site was used to determine whether or not the county was predicted to be nonattainment in the future. For counties with multiple monitoring sites, the site with the highest future concentration was selected for that county. 398 Those counties with future year concentrations of 15.1

g/ m3 ( as rounded up from 15.05

g/ m3) or more were predicted to be nonattainment. Based on the modeling performed for the NPR,

61 counties in the East were forecast to be nonattainment for the 2010 Base Case. Of these, 41 were forecast to remain nonattainment for the 2015 Base Case.

Comment: Some commenters said that EPA has not established the credibility of using models in a relative sense to estimate future PM2.5 concentrations and that poor performance of REMSAD for 1996 calls into question the use of models to adequately determine the effects of changes in emissions. One commenter said that a mechanistic model evaluation, in which model predictions of PM2.5 precursor photochemical oxidants are compared to corresponding measurements, is an approach for gaining confidence in the ability of a model to provide a credible response to emission changes.

Response: The EPA believes the future year nonattainment projections should be based on using model predictions in a relative sense. By applying the model in a relative way,

each measured component of PM2.5 is adjusted upward or downward based on the percent change in that component, as determined by the ratio of future year to base year model predictions. The EPA feels that by using this approach, we 399 are able to reduce the risk that overprediction or underprediction of PM2.5 component species may unduly affect our projection of future year nonattainment.

The EPA agrees with commenters that one way to establish confidence in the credibility of this approach is to determine whether model predictions of PM2.5 precursors are generally comparable to corresponding measured data. In this regard, we compared the CMAQ predictions to observations for several precursor gases for which measurements were available in 2001. These gases include sulfur dioxide, nitric acid, and ozone.

The results for the East are summarized in Table VI 2.

Additional details on this analysis can be found in the CMAQ evaluation report. The results indicate that for both summer and winter ozone, the fractional bias and error is within the recommended range for urban scale ozone modeling included in EPA's draft guidance for 8 hour ozone modeling.

For the other species examined, there are limited ambient data and few other studies against which to compare our findings. Still, our performance results for these species are within the range suggested as acceptable by commenters for sulfate ( i. e., ± 30 percent to ± 60 percent for fractional bias and 50 percent to 75 percent for fractional error).

Thus, CMAQ is considered appropriate and credible for use in projecting changes in future year PM2.5 concentrations and 400 the resultant health/ economic benefits due to the emissions reductions.

Table VI 2. CMAQ Model Performance Statistics for Ozone, Total Nitrate, and Nitric Acid in the East.

Eastern U. S. CMAQ 2001 FB (%) FE (%)

Ozone AIRS ( Summer) 13 21 AIRS ( Winter)  9 31 Sulfur Dioxide CASTNet ( Summer) 31 48 CASTNet ( Winter) 39 43 Nitric Acid CASTNet ( Summer) 29 39 CASTNet ( Winter)  21 55 Comment: Several commenters said that EPA's SMAT approach is flawed and suggested alternative methods for attributing individual species mass to the FRM measured PM2.5 mass. One commenter detailed several different methods to apportion the FRM mass to individual PM2.5 species. They refer to two different estimation methods as the " FRM equivalent"

approach and the " best estimate" approach.

Response: The EPA agrees that alternative methodologies can be used to apportion PM2.5 species fractions to the FRM data. We believe that revising SMAT to use a methodology similar to an " FRM equivalent" methodology, as described in the Notice of Data Availability ( 69 FR 47828; August 6,

2004), is warranted. Since nonattainment designation 401 101 Procedures for Estimating Future PM2.5 Values for the CAIR Final Rule by Application of the ( Revised) Speciated Modeled Attainment Test ( SMAT), docket number OAR 2003 0053 1907. determinations and future year nonattainment projections are based on measured FRM data, we believe that the PM2.5 species data should be adjusted to best conform to what is measured on the FRM filters. Based on comments, EPA has revised our technique for projecting current PM2.5 data to incorporate some aspects of the commenter's " FRM equivalent"

methodology. As described in more detail in the NFR AQMTSD,

we believe our revised methodology to be the most technically appropriate way of estimating what is measured on the FRM filters.

Full documentation of the revised EPA SMAT methodology is contained in the updated SMAT report101. In brief, we revised the SMAT methodology to take into account several known differences between what is measured by speciation monitors and what is measured on FRM filters. Among the revisions were calculations to account for nitrate,

ammonium, and organic carbon volatilization, blank PM2.5 mass, particle bound water, the degree of neutralization of sulfate, and the uncertainty in estimating organic carbon mass.

Comment: Several commenters noted that the future year design values were based on projections of the 1999   2001 402 and/ or 2000 2002 FRM monitoring data and that there are more recent design value data available for the 2001 2003 design value period. Commenters also noted that the 2001 2003 data shows lower PM2.5 concentrations at the majority of sites and therefore, by projecting the highest design value, we are overestimating the future year PM2.5 values.

Response: As stated above, the PM2.5 projection methodology in the NPR used the higher of the 1999 2001 or 2000 2002 PM2.5 design value data. The draft modeling guidance for PM2.5 specifies the use of the higher of the three design value periods which straddle the emissions year. The emissions year is 2001 and therefore the three periods would be 1999 2001, 2000 2002, and 2001 2003. Since the 2001 2003 data is now available, we are using it as part of the current year PM2.5 calculations for the final rule.

The observation by a commenter that the 2001 2003 data are generally lower than in the previous two design value periods ( i. e., 1999 2001 and 2000 2002) leads to the issue of how to reduce the influence of year to year variability in meteorology and emissions on our estimate of current air quality. As a consequence of this year to year variability in concentrations, relying on design values from any single period, as in the approach used for proposal, may not provide a robust representation of current air quality for 403 use in forecasting the future. Specifically, the lower PM2.5 values in 2001 2003 may not be representative of the current modeling period. To address the issue of year

toyear variability in the ambient data we have modified our methodology to use an average of the three design value periods that straddle the base year emissions year ( i. e.,

2001). In this case it is the average of the 1999 2001,

2000 2002, and 2001 2003 design values. The average of the three design values is not a straight 5 year average.

Rather, it is a weighted average of the 1999 2003 period.

That is, by averaging 1999 2001, 2000 2002, and 2001 2003,

the value from 2001 is weighted three times; 2000 and 2002 are each weighted twice and 1999 and 2003 are each weighted once. This approach has the desired benefits of: ( 1)

weighting the PM2.5 values towards the middle year of the 5

year period, which is the 2001 base year for our emissions projections; and ( 2) smoothing out the effects of year

toyear variability in emissions and meteorology that occurs over the full 5 year period. We have adopted this method for use in projecting future PM2.5 nonattainment for the final rule analysis. We plan to incorporate this new methodology into the next draft version of our PM2.5 modeling guidance. 404 b. Projected 2010 and 2015 Base Case PM2.5 Nonattainment Counties For the final rule, we have revised the projected PM2.5 nonattainment counties for 2010 and 2015 by applying CMAQ for the entire year ( i. e., January through December) of 2001 using 2001 Base Year and 2010 and 2015 future Base Case emissions from the new modeling platform, as described in section VI. A. 2. The 2010 and 2015 Base Case PM2.5 nonattainment counties were determined applying the updated SMAT method using current 1999 2003 PM2.5 air quality coupled with the PM2.5 species from the 2001 Base Year and 2010 and 2015 Base Case CMAQ model runs. For counties with multiple monitoring sites, the site with the highest future concentration was selected for that county. Those counties with future year design values of 15.05

g/ m3 or higher were predicted to be nonattainment. The result is that, without controls beyond those included in the Base Case, 79 counties in the East are projected to be nonattainment for the 2010 Base Case. For the 2015 Base Case, 74 counties in the East are projected to be nonattainment for PM2.5.

In light of the uncertainties inherent in regionwide modeling many years into the future, of the 79 nonattainment counties projected for the 2010 Base Case, we have the most confidence in our projection of nonattainment for those 405 counties that are not only forecast to be nonattainment in 2010, based on the SMAT method, but that also measure nonattainment for the most recent period of available ambient data ( i. e., 2001 2003). In our analysis for the 2010 Base Case, there are 62 such counties in the East that are both " modeled" nonattainment and currently have " monitored" nonattainment. We refer to these counties as having " modeled plus monitored" nonattainment. Out of an abundance of caution, we are using only these 62 " modeled plus monitored" counties as the downwind receptors in determining which upwind States make a significant contribution to PM2.5 in downwind States.

The 79 counties in the East that we project will be nonattainment for PM2.5 in 2010 and the subset of 62 counties that are also " monitored" nonattainment in 2001

2003, are identified in Table VI 3. The 2015 Base Case PM2.5 nonattainment counties are provided in Table VI 4.

Table VI 3. Projected PM2.5 Concentrations (

g/ m3) for Nonattainment Counties in the 2010 Base Case.

State County 2010 Base " Modeled + Monitored"

Alabama DeKalb Co 15.23 No Alabama Jefferson Co 18.57 Yes Alabama Montgomery Co 15.12 No Alabama Morgan Co 15.29 No Alabama Russell Co 16.17 Yes Alabama Talladega Co 15.34 No Delaware New Castle Co 16.56 Yes District of Columbia 15.84 Yes 406 State County 2010 Base " Modeled + Monitored"

Georgia Bibb Co 16.27 Yes Georgia Clarke Co 16.39 Yes Georgia Clayton Co 17.39 Yes Georgia Cobb Co 16.57 Yes Georgia DeKalb Co 16.75 Yes Georgia Floyd Co 16.87 Yes Georgia Fulton Co 18.02 Yes Georgia Hall Co 15.60 No Georgia Muscogee Co 15.65 No Georgia Richmond Co 15.68 No Georgia Walker Co 15.43 Yes Georgia Washington Co 15.31 No Georgia Wilkinson Co 16.27 No Illinois Cook Co 17.52 Yes Illinois Madison Co 16.66 Yes Illinois St. Clair Co 16.24 Yes Indiana Clark Co 16.51 Yes Indiana Dubois Co 15.73 Yes Indiana Lake Co 17.26 Yes Indiana Marion Co 16.83 Yes Indiana Vanderburgh Co 15.54 Yes Kentucky Boyd Co 15.23 No Kentucky Bullitt Co 15.10 No Kentucky Fayette Co 15.95 Yes Kentucky Jefferson Co 16.71 Yes Kentucky Kenton Co 15.30 No Maryland Anne Arundel Co 15.26 Yes Maryland Baltimore City 16.96 Yes Michigan Wayne Co 19.41 Yes Missouri St. Louis City 15.10 No New Jersey Union Co 15.05 Yes New York New York Co 16.19 Yes North Carolina Catawba Co 15.48 Yes North Carolina Davidson Co 15.76 Yes North Carolina Mecklenburg Co 15.22 No Ohio Butler Co 16.45 Yes Ohio Cuyahoga Co 18.84 Yes Ohio Franklin Co 16.98 Yes Ohio Hamilton Co 18.23 Yes Ohio Jefferson Co 17.94 Yes Ohio Lawrence Co 16.10 Yes Ohio Mahoning Co 15.39 Yes Ohio Montgomery Co 15.41 Yes Ohio Scioto Co 18.13 Yes 407 State County 2010 Base " Modeled + Monitored"

Ohio Stark Co 17.14 Yes Ohio Summit Co 16.47 Yes Ohio Trumbull Co 15.28 No Pennsylvania Allegheny Co 20.55 Yes Pennsylvania Beaver Co 15.78 Yes Pennsylvania Berks Co 15.89 Yes Pennsylvania Cambria Co 15.14 Yes Pennsylvania Dauphin Co 15.17 Yes Pennsylvania Delaware Co 15.61 Yes Pennsylvania Lancaster Co 16.55 Yes Pennsylvania Philadelphia Co 16.65 Yes Pennsylvania Washington Co 15.23 Yes Pennsylvania Westmoreland Co 15.16 Yes Pennsylvania York Co 16.49 Yes Tennessee Davidson Co 15.36 No Tennessee Hamilton Co 16.89 Yes Tennessee Knox Co 17.44 Yes Tennessee Sullivan Co 15.32 No West Virginia Berkeley Co 15.69 Yes West Virginia Brooke Co 16.63 Yes West Virginia Cabell Co 17.03 Yes West Virginia Hancock Co 17.06 Yes West Virginia Kanawha Co 17.56 Yes West Virginia Marion Co 15.32 Yes West Virginia Marshall Co 15.81 Yes West Virginia Ohio Co 15.14 Yes West Virginia Wood Co 16.66 Yes Table VI 4. Projected PM2.5 Concentrations (

g/ m3) for Nonattainment Counties in the 2015 Base Case.

State County 2015 Base Alabama DeKalb Co 15.24 Alabama Jefferson Co 18.85 Alabama Montgomery Co 15.24 Alabama Morgan Co 15.26 Alabama Russell Co 16.10 Alabama Talladega Co 15.22 Delaware New Castle Co 16.47 District of Columbia 15.57 Georgia Bibb Co 16.41 408 State County 2015 Base Georgia Chatham Co 15.06 Georgia Clarke Co 16.15 Georgia Clayton Co 17.46 Georgia Cobb Co 16.51 Georgia DeKalb Co 16.82 Georgia Floyd Co 17.33 Georgia Fulton Co 18.00 Georgia Hall Co 15.36 Georgia Muscogee Co 15.58 Georgia Richmond Co 15.76 Georgia Walker Co 15.37 Georgia Washington Co 15.34 Georgia Wilkinson Co 16.54 Illinois Cook Co 17.71 Illinois Madison Co 16.90 Illinois St. Clair Co 16.49 Illinois Will Co 15.12 Indiana Clark Co 16.37 Indiana Dubois Co 15.66 Indiana Lake Co 17.27 Indiana Marion Co 16.77 Indiana Vanderburgh Co 15.56 Kentucky Boyd Co 15.06 Kentucky Fayette Co 15.62 Kentucky Jefferson Co 16.61 Kentucky Kenton Co 15.09 Maryland Baltimore City 17.04 Maryland Baltimore Co 15.08 Michigan Wayne Co 19.28 Mississippi Jones Co 15.18 Missouri St. Louis City 15.34 New York New York Co 15.76 North Carolina Catawba Co 15.19 North Carolina Davidson Co 15.34 Ohio Butler Co 16.32 Ohio Cuyahoga Co 18.60 Ohio Franklin Co 16.64 Ohio Hamilton Co 18.03 Ohio Jefferson Co 17.83 Ohio Lawrence Co 15.92 Ohio Mahoning Co 15.13 Ohio Montgomery Co 15.16 Ohio Scioto Co 17.92 Ohio Stark Co 16.86 409 State County 2015 Base Ohio Summit Co 16.14 Ohio Trumbull Co 15.05 Pennsylvania Allegheny Co 20.33 Pennsylvania Beaver Co 15.54 Pennsylvania Berks Co 15.66 Pennsylvania Delaware Co 15.52 Pennsylvania Lancaster Co 16.28 Pennsylvania Philadelphia Co 16.53 Pennsylvania York Co 16.22 Tennessee Davidson Co 15.36 Tennessee Hamilton Co 16.82 Tennessee Knox Co 17.34 Tennessee Shelby Co 15.17 Tennessee Sullivan Co 15.37 West Virginia Berkeley Co 15.32 West Virginia Brooke Co 16.51 West Virginia Cabell Co 16.86 West Virginia Hancock Co 16.97 West Virginia Kanawha Co 17.17 West Virginia Marshall Co 15.52 West Virginia Wood Co 16.69 2. Projection of Future 8 Hour Ozone Nonattainment a. Methodology for Projecting Future 8 Hour Ozone Nonattainment The approach for projecting future 8 hour ozone concentrations used by EPA in the NPR was based on applying the model in a relative sense to estimate the change in ozone between the base year ( 2001) and each future scenario.

Projected 8 hour ozone design values in 2010 and 2015 were estimated by combining the relative change in model predicted ozone from 2001 to the future scenario with an estimate of the base year ambient 8 hour ozone design value. 410 These procedures for calculating future case ozone design values are consistent with EPA's draft modeling guidance for 8 hour ozone attainment demonstrations. The draft guidance specifies the use of the higher of the design values from ( a) the period that straddles the emissions inventory base year or ( b) the design value period which was used to designate the area under the ozone NAAQS. At the time of the proposal, 2000 2002 was the design value period which both straddled the 2001 base year inventory and was also the latest period available.

Comment: Commenters noted that the procedures used by EPA for projecting future 8 hour ozone concentrations differ from the procedures used for projecting PM2.5. These commenters said that EPA should harmonize the two approaches.

Response: In response to comments, we have made several changes in the approach to projecting future 8 hour ozone nonattainment in order to follow an approach that is consistent with the manner in which PM2.5 projections are determined. The approach we are using to project PM2.5 for the final rule analysis is described in section VI. B. 1,

above. In order to harmonize the ozone approach with the approach used for PM2.5, we are using the weighted average of the design values for the periods that straddle the 411 emission base year ( i. e., 2001). These periods are 1999

2001, 2000 2002, and 2001 2003. In this approach, the fourth high ozone value from 2001 is weighted 3 times, 2000 and 2002 are weighted twice, and 1999 and 2003 are weighted once. This has the desired effect of weighting the projected ozone values towards the middle year of the 5 year period,

which is the emissions year ( 2001), while accounting for the emissions and meteorological variability that occurs over the full 5 year period. The average weighted concentration is expected to be more representative as a starting point for future year projections than choosing ( a) the single design value period that straddles the base year or ( b) the design value used for designations. We plan to incorporate this new methodology into the next draft version of our ozone modeling guidance.

Comment: One commenter claimed that the 2010 and 2015 ozone projections in the proposal base cases were too optimistic,

that is, that the modeling was underestimating the number of areas that may be in nonattainment in the future. The commenter urged a more conservative approach to assessing the future attainment status of areas.

Response: The technical basis for the comment stemmed from the assertion that the regional ozone modeling that EPA performed for the proposal was not of " SIP quality." The 412 EPA response to the specific technical issues with regard to episode selection and grid resolution can be found in section VI. A as well as in the response to comments document. The EPA remains confident that the CAIR 8 hour ozone modeling platform is appropriate for assessing potential levels of future nonattainment.

b. Projected 2010 and 2015 Base Case 8 Hour Ozone Nonattainment Counties For the final rule, we have revised our projections of ozone nonattainment for the 2010 and 2015 Base Cases by applying CAMx for the three 1995 ozone episodes using 2001 Base Year and 2010 and 2015 future Base Case emissions from the new modeling platform, as described in section VI. A. 2.

The revised 2010 and 2015 Base Case 8 hour ozone nonattainment counties were determined by applying the relative change in 8 hour ozone predicted by these CAMx model runs to the weighted average 1999 2003 8 hour ozone concentrations as described above and, in more detail, in the NFR AQMTSD. For counties with multiple monitoring sites, the site with the highest future concentration was selected for that county. Those counties with future year design values of 85 parts per billion ( ppb) or higher were predicted to be nonattainment. 413 As a result of our updated modeling we project that,

without controls beyond those in the Base Case, there will be 40 8 hour ozone nonattainnment counties in 2010 and 22 nonattainment counties in 2015. All of the 40 counties that we are projecting to be nonattainment for the 2010 Base Case are also measuring nonattainment based on the most recent design value period ( i. e., 2001 2003). We refer to these counties as " modeled plus monitored" nonattainment, as described above in section IV. B. 1 for PM2.5. We are using these 40 counties as the downwind receptors to determine which States make a significant contribution to 8 hour ozone nonattainment in downwind States.

The counties we are projecting to be nonattainment for 8 hour ozone in the 2010 Base Case and 2015 Base Case are listed in Table VI 5 and Table VI 6, respectively.

Table VI 5. Projected 2010 Base Case 8 hour Ozone Nonattainment Counties and Concentrations ( ppb).

State County 2010 Base Connecticut Fairfield Co 92.6 Connecticut Middlesex Co 90.9 Connecticut New Haven Co 91.6 Delaware New Castle Co 85.0 District of Columbia 85.2 Georgia Fulton Co 86.5 Maryland Anne Arundel Co 88.8 Maryland Cecil Co 89.7 Maryland Harford Co 93.0 Maryland Kent Co 86.2 Michigan Macomb Co 85.5 New Jersey Bergen Co 86.9 414 State County 2010 Base New Jersey Camden Co 91.9 New Jersey Gloucester Co 91.8 New Jersey Hunterdon Co 89.0 New Jersey Mercer Co 95.6 New Jersey Middlesex Co 92.4 New Jersey Monmouth Co 86.6 New Jersey Morris Co 86.5 New Jersey Ocean Co 100.5 New York Erie Co 87.3 New York Richmond Co 87.3 New York Suffolk Co 91.1 New York Westchester Co 85.3 Ohio Geauga Co 87.1 Pennsylvania Bucks Co 94.7 Pennsylvania Chester Co 85.7 Pennsylvania Montgomery Co 88.0 Pennsylvania Philadelphia Co 90.3 Rhode Island Kent Co 86.4 Texas Denton Co 87.4 Texas Galveston Co 85.1 Texas Harris Co 97.9 Texas Jefferson Co 85.6 Texas Tarrant Co 87.8 Virginia Arlington Co 86.2 Virginia Fairfax Co 85.7 Wisconsin Kenosha Co 91.3 Wisconsin Ozaukee Co 86.2 Wisconsin Sheboygan Co 88.3 Table VI 6. Projected 2015 Base Case 8 hour Ozone Nonattainment Counties and Concentrations ( ppb).

State County 2015 Base Connecticut Fairfield Co 91.4 Connecticut Middlesex Co 89.1 Connecticut New Haven Co 89.8 Maryland Anne Arundel Co 86.0 Maryland Cecil Co 86.9 Maryland Harford Co 90.6 Michigan Macomb Co 85.1 New Jersey Bergen Co 85.7 415 State County 2015 Base New Jersey Camden Co 89.5 New Jersey Gloucester Co 89.6 New Jersey Hunterdon Co 86.5 New Jersey Mercer Co 93.5 New Jersey Middlesex Co 89.8 New Jersey Ocean Co 98.0 New York Erie Co 85.2 New York Suffolk Co 89.9 Pennsylvania Bucks Co 93.0 Pennsylvania Montgomery Co 86.5 Pennsylvania Philadelphia Co 88.9 Texas Harris Co 97.3 Texas Jefferson Co 85.0 Wisconsin Kenosha Co 89.4 C. How did EPA Assess Interstate Contributions to Nonattainment?

1. PM2.5 Contribution Modeling Approach For the proposed rule, EPA performed State by State zero out modeling to quantify the contribution from emissions in each State to future PM2.5 nonattainment in other States and to determine whether that contribution meets the air quality prong ( i. e., before considering cost)

of the " contribute significantly" test. The zero out modeling technique provides an estimate of downwind impacts by comparing the model predictions from the 2010 Base Case to the predictions from a run in which all anthropogenic SO2 and NOx emissions are removed from specific States.

Counties forecast to be nonattainment for PM2.5 in the proposal 2010 Base Case were used as receptors for 416 quantifying interstate contributions of PM2.5. For each State by State zero out run we projected the annual average PM2.5 concentration at each receptor using the proposed SMAT technique, as described in the NPR AQMTSD. The contribution from an upwind State to nonattainment at a given downwind receptor was determined by calculating the difference in PM2.5 concentration between the 2010 Base Case and the zeroout run at that receptor. We followed this process for each State by State zero out run and each receptor. For each upwind State, we identified the largest contribution from that State to a downwind nonattainment receptor in order to determine the magnitude of the maximum downwind contribution from each State. The maximum downwind contribution was proposed as the metric for determining whether or not the contribution was significant. As described in section III,

EPA proposed, in the alternative, a criterion of 0.10

g/ m3 and 0.15

g/ m3 for determining whether emissions in a State make a significant contribution ( before considering cost) to PM2.5 nonattainment in another State. Details on these procedures can be found in the NPR AQMTSD.

Comments: Commenters questioned the use of zero out modeling and said that EPA should support the development of a source apportionment model for PM2.5 contributions. The commenter recommended that EPA delay the final rule until 417 such a technique can be used. Another commenter provided results of a sulfate source apportionment technique currently under development along with modeling results which showed that the zero out technique and source apportionment for sulfate provide similar results in terms of the magnitude and extent of downwind impacts. The commenter noted that the results suggest that zero out modeling may somewhat underestimate the transport of sulfate.

Response: The EPA continues to believe that the zero out technique is a credible method for quantifying interstate PM2.5 contributions. This is supported by a commenter's results showing that the zero out technique and source apportionment appear to give similar results. We accept the commenter's modeling for sulfate source apportionment results which indicate that the zero out technique does not overestimate interstate transport. Moreover, EPA rejects the notion that we should delay needed reductions while we await alternative assessment techniques.

2. 8 Hour Ozone Contribution Modeling Approach In the proposal, EPA quantified the impact of emissions from specific upwind States on 8 hour ozone concentrations in projected downwind nonattainment areas. The procedures we followed to assess interstate ozone contribution for the 418 proposal analysis are summarized below. We are using these same procedures along with the updated CAMx modeling platform, as described in section VI. A., to assess ozone contributions for today's rule. Details on these procedures can be found in the NFR AQMTSD.

We applied two different modeling techniques, zero out and source apportionment, to assess the contributions of emissions in upwind States on 8 hour ozone nonattainment in downwind States. The outputs of the two modeling techniques were evaluated in terms of three key contribution factors to determine which States make a significant contribution to downwind ozone nonattainment as described in section VI. B. 2.

The zero out and source apportionment modeling techniques provide different, but equally valid, technical approaches to quantifying the downwind impact of emissions from upwind States. The zero out modeling analysis provides an estimate of downwind impacts by comparing the model predictions from the 2010 Base Case and the predictions from a model run in which all anthropogenic NOx and VOC emissions are removed from specific States. The source apportionment modeling quantifies downwind impacts by tracking and allocating the amounts of ozone formed from man made NOx and VOC emissions in upwind States. Because large portions of the six States 419 102 The six States are Kansas, Nebraska, North Dakota, Oklahoma, South Dakota, and Texas. along the western border of the modeling domain102 are outside the area covered by our modeling, EPA did not analyze the contributions to downwind ozone nonattainment for these States.

In the analysis done at proposal, EPA considered three fundamental factors for evaluating whether emissions in an upwind State make large and/ or frequent contributions to downwind nonattainment: ( 1) the magnitude of the contribution; ( 2) the frequency of the contribution; and ( 3)

the relative amount of the contribution when compared against contributions from other areas. The factors are the basis for several metrics that can be used to assess a particular impact. The metrics used in this analysis were the same as those used in the NOx SIP Call.

Within these three factors, eight specific metrics were calculated to assess the contribution of each of the 31 States to the residual nonattainment counties. For the zero out modeling, EPA considered: ( 1) the maximum contribution ( magnitude); ( 2) the number and percentage of exceedances with contributions in certain concentration ranges ( frequency); ( 3) the total contribution relative to the total exceedance level ozone in the receptor area ( relative amount); and ( 4) the population weighted total 420 contribution relative to the total population weighted exceedance level ozone in the receptor area ( relative amount). For the source apportionment modeling EPA considered: ( 5) the maximum contribution ( magnitude); ( 6)

the highest daily average contribution ( magnitude); ( 7) the number and percentages of exceedances with contributions in certain concentration ranges ( frequency); and ( 8) the total average contribution to exceedance ozone in the downwind area ( relative amount). The values for these metrics were calculated using only those periods during which the model predicted 8 hour average ozone concentrations greater than or equal to 85 ppb in at least one of the model grid cells associated with the receptor county in the 2010 base case.

Grid cells were linked to a specific nonattainment county if any part of the grid cell covered any portion of the projected 2010 nonattainment county.

The first step in evaluating the contribution factors was to screen out linkages for which the contributions were clearly small. This initial screening was based on two criteria: ( 1) the maximum contribution had to be greater than or equal to 2 ppb from either of the two modeling techniques; and ( 2) the total average contribution to exceedance of ozone in the downwind area had to be greater than 1 percent. If either screening test was not met, then the linkage was not considered significant. Those linkages 421 that had contributions which exceeded the screening criteria were evaluated further in steps 2 through 4.

In step 2, we evaluated the contributions in each linkage based on the zero out modeling and in step 3 we evaluated the contributions in each linkage based on the source apportionment modeling. In step 4, we considered the results of both step 2 and step 3 to determine which of the linkages were significant. For both techniques, EPA determined whether the linkage is significant by evaluating the magnitude, frequency, and relative amount of the contributions. Each upwind State that made relatively large and/ or frequent contributions to nonattainment in the downwind area, based on these factors, was considered to contribute significantly to nonattainment in the downwind area.

The EPA believes that each of the factors provides an independent measure of contribution, however, there had to be at least two different factors that indicated large and/ or frequent contributions in order for the linkage to be found significant. In this regard, the finding of a significant contribution for an individual linkage was not based on any single factor. Further, each of the modeling approaches had to show at least one indicator of a large and/ or frequent contribution in order for the linkage to be found significant. The EPA received several general 422 comments on the procedures for assessing interstate contributions of ozone to projected residual nonattainment areas, as discussed below.

Comment: A commenter opposed the use of population weighted metrics to determine whether an upwind State's impact on a location in another State is significant.

Response: The commenter's concern was that transport contributions to rural areas with low populations were not being weighted appropriately. This is not a valid concern because the relative contribution factor from the zero out modeling is presumed to be met if either of the two criteria ( population weighted, or non population weighted) show large contributions.

Comment: Also, EPA received a specific comment on a certain linkage that was deemed to be significant in the analysis done to support the NPR. The commenter objected to the conclusion that Mississippi significantly contributes to residual ozone exceedances near Memphis. The objection resulted from issues with grid resolution, episode selection, and the fact that the zero out and source apportionment modeling for Mississippi included some emissions from Tennessee and Arkansas due to the irregular State boundaries. 423 Response: As noted in section VI. B. 2, Crittenden County, AR is no longer projected to be a nonattainment area in the 2010 Base Case. As a result, the issue of Mississippi's contribution to ozone in the Memphis area is moot.

D. What Are the Estimated Interstate Contributions to PM2.5 and 8 Hour Ozone Nonattainment?

1. Results of PM2.5 Contribution Modeling In this section, we present the interstate contributions from emissions in upwind States to PM2.5 nonattainment in downwind nonattainment counties. States which contribute 0.2

g/ m3 or more to PM2.5 nonattainment in another State are determined to contribute significantly ( before considering cost). We calculated the interstate PM2.5 contributions using the State by State zero out modeling technique, as indicated above in section VI. C. 1.

This technique is described in the NFR AQMTSD. We performed zero out modeling using CMAQ for each of 37 States individually ( i. e., Alabama, Arkansas, Connecticut,

Delaware, Florida, Georgia, Illinois, Indiana, Iowa, Kansas,

Kentucky, Louisiana, Maine, Maryland combined with the District of Columbia, Massachusetts, Michigan, Minnesota,

Mississippi, Missouri, Nebraska, New Hampshire, New Jersey,

New York, North Carolina, North Dakota, Ohio, Oklahoma,

Pennsylvania, Rhode Island, South Carolina, South Dakota, 424 103 As noted above, we combined Maryland and the District of Columbia as a single entity in our contribution modeling. This is a logical approach because of the small size of the District of Columbia and, hence, its emissions and its close proximity to Maryland. Under our analysis, Maryland and the District of Columbia are linked as significant contributors to the same downwind nonattainment counties. EPA received no adverse comment on this approach. We also considered these entities separately, and in view of the close proximity of these two areas we believe that Maryland is linked as a significant contributor to nonattainment in the District of Columbia and that the District of Columbia is linked as a significant contributor to nonattainment in Maryland. Tennessee, Texas, Vermont, Virginia, West Virginia, and Wisconsin).

We calculated each State's contribution to PM2.5 in each of the 62 counties that are projected to be nonattainment in the 2010 Base Case ( i. e., " modeled"

nonattainment) and are also " monitored" nonattainment in 2001 2003, as described in section VI. B. 1. b. The maximum contribution from each upwind State to downwind PM2.5 nonattainment is provided in Table VI 7. The contributions from each State to nonattainment in each nonattainment county are provided in the NFR AQMTSD. Based on the Stateby State modeling, there are 23 States and the District of Columbia103 which contribute 0.2

g/ m3 or more to downwind PM2.5 nonattainment ( Alabama, the District of Columbia,

Florida, Georgia, Illinois, Indiana, Iowa, Kentucky,

Louisiana, Maryland, Michigan, Minnesota, Mississippi,

Missouri, New York, North Carolina, Ohio, Pennsylvania, 425 South Carolina, Tennessee, Texas, Virginia, West Virginia,

and Wisconsin). In Table VI 8, we provide a list of the downwind nonattainment counties to which each upwind State contributes 0.2

g/ m3 or more ( i. e., the upwind State

todownwind nonattainment " linkages").

Table VI 7. Maximum Downwind PM2.5 Contribution (

g/ m3) for each of 37 States.

Upwind State Maximum Downwind Contribution Upwind State Maximum Downwind Contribution Alabama 0.98 Nebraska 0.07 Arkansas 0.19 New Hampshire < 0.05 Connecticut < 0.05 New Jersey 0.13 Delaware 0.14 New York 0.34 Florida 0.45 North Carolina 0.31 Georgia 1.27 North Dakota 0.11 Illinois 1.02 Ohio 1.67 Indiana 0.91 Oklahoma 0.12 Iowa 0.28 Pennsylvania 0.89 Kansas 0.11 Rhode Island < 0.05 Kentucky 0.90 South Carolina 0.40 Louisiana 0.25 South Dakota < 0.05 Maine < 0.05 Tennessee 0.65 Maryland/ DC 0.69 Texas 0.29 Massachusetts 0.07 Vermont < 0.05 Michigan 0.62 Virginia 0.44 Minnesota 0.21 West Virginia 0.84 Mississippi 0.23 Wisconsin 0.56 Missouri 1.07 426 Table VI 8. Upwind State to Downwind Nonattainment County Significant " Linkages" for PM2.5.

Upwind States Total Linkage s Downwind Counties AL 21 Bibb GA Cabell WV Catawba NC Clark IN Clarke GA Clayton GA Cobb GA Davidson NC DeKalb GA Dubois IN Fayette KY Floyd GA Fulton GA Hamilton OH Hamilton TN Jefferson KY Knox TN Lawrence OH Scioto OH Vanderburgh IN Walker GA FL 7 Bibb GA Clarke GA Clayton GA Cobb GA DeKalb GA Jefferson AL Russell AL GA 17 Butler OH Cabell WV Catawba NC Clark IN Davidson NC Fayette KY Hamilton OH Hamilton TN Jefferson AL Jefferson KY Kanawha WV Knox TN Lawrence OH Montgomery OH Russell AL Scioto OH Vanderburgh IN IL 23 Allegheny PA Butler OH Cabell WV Clark IN Cuyahoga OH Dubois IN Fayette KY Franklin OH Hamilton OH Hamilton TN Jefferson AL Jefferson KY Kanawha WV Lake IN Lawrence OH Mahoning OH Marion IN Montgomery OH Scioto OH Stark OH Summit OH Vanderburgh IN Wayne MI IN 46 Allegheny PA Beaver PA Berkeley WV Bibb GA Brooke WV Butler OH Cabell WV Cambria PA Catawba NC Clarke GA Clayton GA Cobb GA Cook IL Cuyahoga OH Davidson NC DeKalb GA Fayette KY Floyd GA Franklin OH Fulton GA Hamilton OH Hamilton TN Hancock WV Jefferson AL Jefferson KY Jefferson OH Kanawha WV Knox TN Lancaster PA Lawrence OH Madison IL Mahoning OH Marion WV Marshall WV Montgomery OH Ohio WV Russell AL St. Clair IL Scioto OH Stark OH Summit OH Walker GA Wayne MI Washington PA Westmoreland PA Wood WV IA 5 Cook IL Lake IN Madison IL Marion IN St. Clair IL KY 35 Allegheny PA Butler OH Cabell WV Catawba NC Clark IN Clarke GA Cobb GA Cuyahoga OH Davidson NC Dubois IN Floyd GA Franklin OH Hamilton OH Hamilton TN Jefferson AL Jefferson OH 427 Kanawha WV Knox TN Lawrence OH Madison IL Mahoning OH Marion IN Marion WV Marshall WV Montgomery OH Ohio WV St. Clair IL Scioto OH Stark OH Summit OH Vanderburgh IN Walker GA Washington PA Westmoreland PA Wood WV LA 2 Jefferson AL Russell AL MD/ DC 13 Berkeley WV Berks PA Cambria PA Dauphin PA Delaware PA District of Columbia Lancaster PA New Castle DE New York NY Philadelphia PA Union NJ Westmoreland PA York PA MI 36 Allegheny PA Beaver PA Berks PA Brooke WV Butler OH Cabell WV Cambria PA Clark IN Cook IL Cuyahoga OH Dauphin PA Delaware PA Fayette KY Franklin OH Hamilton OH Hancock WV Jefferson OH Lake IN Lancaster PA Lawrence OH Mahoning OH Marion IN Marion WV Marshall WV Montgomery OH New Castle DE Ohio WV Philadelphia PA Scioto OH Stark OH Summit OH Union NJ Washington PA Westmoreland PA Wood WV York PA MN 2 Cook IL Lake IN MO 9 Clark IN Cook IL Dubois IN Jefferson KY Lake IN Madison IL Marion IN St. Clair IL Vanderburgh IN MS 1 Jefferson AL NY 5 Berks PA Lancaster PA New Castle DE New Haven CT Union NJ NC 7 Anne Arundel MD Baltimore City Bibb GA Clarke GA District of Columbia Kanawha WV Knox TN OH 51 Anne Arundel MD Allegheny PA Baltimore City Beaver PA Berkeley WV Berks PA Bibb GA Brooke WV Cabell WV Cambria PA Catawba NC Clark IN Clarke GA Clayton GA Cobb GA Cook IL Dauphin PA Davidson NC DeKalb GA Delaware PA District of Columbia Dubois IN Fayette KY Floyd GA Fulton GA Hamilton TN Hancock WV Jefferson AL Jefferson KY Kanawha WV Knox TN Lake IN Lancaster PA Madison IL Marion IN Marion WV Marshall WV New Castle DE New York NY Ohio WV Philadelphia PA Russell AL St. Clair IL Union NJ Vanderburgh IN Walker GA Washington PA Wayne MI 428 Westmoreland PA Wood WV York PA PA 25 Anne Arundel MD Baltimore City Berkeley WV Brooke WV Cabell WV Catawba NC Clarke GA Cuyahoga OH Davidson NC District of Columbia Hancock WV Jefferson OH Kanawha WV Lawrence OH Mahoning OH Marion WV Marshall WV New Castle DE New York NY Ohio WV Stark OH Summit OH Union NJ Wayne MI Wood WV SC 9 Bibb GA Catawba NC Clarke GA Clayton GA Cobb GA Davidson NC DeKalb GA Fulton GA Russell AL TN 23 Bibb GA Butler OH Cabell WV Catawba NC Clark IN Clarke GA Clayton GA Cobb GA Davidson NC DeKalb GA Dubois IN Fayette KY Floyd GA Fulton GA Hamilton OH Jefferson AL Jefferson KY Kanawha WV Lawrence OH Russell AL Scioto OH Vanderburgh TN Walker GA TX 2 Madison IL St Clair IL VA 13 Anne Arundel MD Baltimore City Berkeley WV Berks PA Catawba NC Dauphin PA Davidson NC Delaware PA District of Lancaster PA New Castle DE Philadelphia PA York PA WV 33 Anne Arundel MD Allegheny PA Baltimore City Beaver PA Berks PA Butler OH Cambria PA Catawba NC Clarke GA Cuyahoga OH Dauphin PA Davidson NC Delaware PA District of Columbia Fayette KY Franklin OH Hamilton OH Jefferson OH Knox TN Lancaster PA Lawrence OH Mahoning OH Montgomery OH New Castle DE New York NY Philadelphia PA Scioto OH Stark OH Summit OH Union NJ Washington PA Westmoreland PA York PA WI 4 Cook IL Lake IN Marion IN Wayne MI 2. Results of 8 Hour Ozone Contribution Modeling In this section, we present the results of air quality modeling to determine which upwind States contribute significantly ( before considering cost) to 8 hour ozone 429 104 As noted above, we combined Maryland and the District of Columbia as a single entity in our contribution modeling. nonattainment in downwind States. The analytical procedures to determine which States make a significant contribution are based on the zero out and source apportionment modeling techniques using CAMx, as described in section VI. C. 2 and in the NFR AQMTSD.

We performed ozone contribution modeling using both of these techniques for 31 States in the East and the District of Columbia ( i. e., Alabama, Arkansas, Connecticut, Delaware, Georgia,

Florida, Iowa, Illinois, Indiana, Kentucky, Louisiana,

Massachusetts, Maine, Maryland combined with the District of Columbia, Michigan, Minnesota, Mississippi, Missouri, New Hampshire, New Jersey, New York, North Carolina, Ohio,

Pennsylvania, Rhode Island, South Carolina, Tennessee, Vermont,

Virginia, West Virginia, and Wisconsin).

We evaluated the interstate ozone contributions from each of the 31 upwind States and the District of Columbia to each of the 40 counties that are projected to be nonattainment in the 2010 Base Case ( i. e., " modeled" nonattainment) and are also " monitored" nonattainment in 2001 2003, as described in section VI. B. 2. b. We analyzed the contributions from upwind States to these counties in terms of various metrics, described above and in more detail in the NFR AQMTSD.

Based on the State by State modeling, there are 25 States and the District of Columbia104 which make a significant 430 This is a logical approach because of the small size of the District of Columbia and, hence, its emissions and its close proximity to Maryland. Under our analysis, Maryland and the District of Columbia are linked as significant contributors to the same downwind nonattainment counties. EPA received no adverse comment on this approach. We also considered these entities separately, and in view of the close proximity of these two areas we believe that Maryland is linked as a significant contributor to nonattainment in the District of Columbia and that the District of Columbia is linked as a significant contributor to nonattainment in Maryland. contribution ( before considering cost) to 8 hour ozone nonattainment in downwind States ( i. e., Alabama, Arkansas,

Connecticut, Delaware, the District of Columbia, Florida, Iowa,

Illinois, Indiana, Kentucky, Louisiana, Massachusetts, Maryland,

Michigan, Mississippi, Missouri, New Jersey, New York, North Carolina, Ohio, Pennsylvania, South Carolina, Tennessee,

Virginia, West Virginia, and Wisconsin). In Table VI 9, we provide a list of the downwind nonattainment counties to which each upwind State makes a significant contribution ( i. e., the upwind State to downwind nonattainment " linkages"). 431 Table VI 9. Upwind State to Downwind Nonattainment County Significant " Linkages" for 8 hour Ozone.

Upwind States Total Linkages Downwind Counties AL 3 Fulton GA Harris TX Jefferson TX AR 3 Galveston TX Harris TX Jefferson TX CT 2 Kent RI Suffolk NY DE 13 Bucks PA Camden NJ Chester PA Gloucester NJ Hunterdon NJ Mercer NJ Middlesex NJ Monmouth NJ Montgomery PA Morris NJ Ocean NJ Philadelphia PA Suffolk NY FL 1 Fulton GA IA 3 Kenosha WI Macomb MI Sheboygan WI IL 5 Geauga OH Kenosha WI Macomb MI Ozaukee WI Sheboygan WI IN 5 Geauga OH Kenosha WI Macomb MI Ozaukee WI Sheboygan WI KY 3 Fulton GA Geauga OH Macomb MI LA 3 Galveston TX Harris TX Jefferson TX MA 2 Kent RI Middlesex NJ MD/ DC 23 Arlington VA Bergen NJ Bucks PA Camden NJ Chester PA District of Columbia Erie NY Fairfax VA Fairfield CT Gloucester NJ Hunterton NJ Mercer NJ Middlesex NJ Monmouth NJ Montgomery PA Morris NJ New Castle DE New Haven CT Ocean NJ Philadelphia PA Richmond NY Suffolk NY Westchester NY MI 19 Anne Arundel MD Bergen NJ Bucks PA Camden NJ Cecil MD Chester PA Erie NY Geauga OH Gloucester NJ Kent MD Mercer NJ Middlesex NJ Monmouth NJ Morris NJ New Castle DE Ocean NJ Philadelphia PA Richmond NY Suffolk NY MO 4 Geauga OH Kenosha WI Ozaukee WI Sheboygan WI MS 2 Harris TX Jefferson TX NC 8 Anne Arundel MD Fulton GA Harford MD Kent MD Newcastle DE Suffolk NY Bucks PA Chester PA NJ 10 Erie NY Fairfield CT Kent RI Middlesex CT Montgomery PA New Haven CT Philadelphia Richmond NY Suffolk NY Westchester NY NY 9 Fairfield CT Kent RI Mercer NJ Middlesex CT Middlesex NJ Monmouth NJ Morris NJ New Haven CT Ocean NJ 432 OH 28 Anne Arundel MD Arlington VA Bergen NJ Bucks PA Camden NJ Cecil MD Chester PA District of Columbia Fairfax VA Fairfield CT Gloucester NJ Harford MD Hunterton NJ Kent MD Kent RI Macomb MI Mercer NJ Middlesex CT Middlesex NJ Monmouth NJ Montgomery PA Morris NJ New Castle DE New Haven CT Ocean NJ Philadelphia Suffolk NY Westchester NY PA 25 Anne Arundel MD Arlington VA Bergen NJ Camden NJ Cecil MD District of Columbia Erie NY Fairfax VA Fairfield CT Gloucester NJ Harford MD Hunterton NJ Kent MD Kent RI Mercer NJ Middlesex CT Middlesex NJ Monmouth NJ Morris NJ New Castle DE New Haven CT Ocean NJ Richmond NY Suffolk NY Westchester NY SC 1 Fulton GA TN 1 Fulton GA VA 26 Anne Arundel MD Bergen NJ Bucks PA Camden NJ Cecil MD Chester PA District of Columbia Erie NY Fairfield CT Gloucester NJ Harford MD Hunterton NJ Kent MD Kent RI Mercer NJ Middlesex CT Middlesex NJ Monmouth NJ Morris NJ New Castle DE New Haven CT Ocean NJ Philadelphia Richmond NY Suffolk NY Westchester NY WI 2 Erie NY Macomb MI WV 25 Anne Arundel MD Bergen NJ Bucks PA Camden NJ Cecil MD Chester PA Fairfax VA Fairfield CT Fulton GA Gloucester NJ Harford MD Hunterton NJ Kent MD Mercer NJ Middlesex NJ Monmouth NJ Montgomery PA Morris NJ New Castle DE New Haven CT Ocean NJ Philadelphia Richmond NY Suffolk NY Westchester NY E. What are the Estimated Air Quality Impacts of the Final Rule?

In this section, we describe the air quality modeling performed to determine the projected impacts on PM2.5 and 8 hour ozone of the SO2 and NOx emissions reductions in the control region modeled. The modeling used to estimate the air quality 433 105 In addition to the SO2 and NOx reductions in these States, we also modeled summer season only EGU NOx controls for Connecticut and Massachusetts, which significantly contribute to ozone, but not to PM2.5 nonattainment in downwind areas. impact of these reductions assumes annual SO2 and NOx controls for Arkansas, Delaware, and New Jersey in addition to the 23

States plus the District of Columbia. Since Arkansas, Delaware,

and New Jersey are not included in the final CAIR region for PM2.5, the modeled estimated impacts on PM2.5 are overstated for today's final rule. However, EPA plans to propose to include these three States in the CAIR region for PM2.5 through a separate regulatory process. Thus, the estimates are reflective of the total impacts expected for CAIR assuming Arkansas,

Delaware, and New Jersey will become part of the annual SO2 and NOx trading program.

As discussed in section IV, EPA analyzed the impacts of the regional emissions reductions in both 2010 and 2015. These impacts are quantified by comparing air quality modeling results for the regional control scenario to the modeling results for the corresponding 2010 and 2015 Base Case scenarios. The 2010 and 2015 emissions reductions from the power generation sector include a two phase cap and trade program covering the control region modeled ( i. e., the 23 States plus the District of Columbia included in today's rule and Arkansas, Delaware, and New Jersey). 105 Phase 1 of the regional strategy ( the 2010 434 106 For the purposes of this discussion, we have calculated the percent reduction in total EGU emissions which includes units greater than and less than 25 MW. reductions) is forecast to reduce total EGU SO2 emissions106 in the control region modeled by 40 percent in 2010. Phase 2 ( the 2015 reductions) is forecast to provide a 48 percent reduction in EGU SO2 emissions compared to the Base Case in 2015. When fully implemented post 2015, we expect this rule to result in more than a 70 percent reduction in EGU SO2 emissions compared to current emissions levels. The reductions at full implementation occur post 2015 due to the existing title IV bank of SO2 allowances,

which can be used under the CAIR program. The net effect of the strategy on total SO2 emissions in the control region modeled considering all sources of emissions, is a 28 percent reduction in 2010 and a 32 percent reduction in 2015.

For NOx, Phase 1 of the strategy is forecast to reduce total EGU emissions by 44 percent in 2009. Total NOx emissions across the control region ( i. e., includes all sources) are 11 percent lower in the 2010 CAIR scenario compared to the emissions in the 2010 Base Case. In Phase 2, EGU NOx emissions are projected to decline by 54 percent in 2015 in this region. Total NOx emissions from all anthropogenic sources are projected to be reduced by 14 percent in 2015. The percent change in emissions by State for SO2 and NOx in 2010 and 2015 for the regional control strategy modeled are provided in the NFR EITSD. 435 1. Estimated Impacts on PM2.5 Concentrations and Attainment We determined the impacts on PM2.5 of the CAIR regional strategy by running the CMAQ model for this strategy and comparing the results to the PM2.5 concentrations predicted for the 2010 and 2015 Base Cases. In brief, we ran the CMAQ model for the regional strategy in both 2010 and 2015. The model predictions were used to project future PM2.5 concentrations for CAIR in 2010 and 2015 using the SMAT technique, as described in section VI. B. 1. We compared the results of the 2010 and 2015 regional strategy modeling to the corresponding results from the 2010 and 2015 Base Cases to quantify the expected impacts of CAIR.

The impacts of the SO2 and NOx emissions reductions expected from CAIR on PM2.5 in 2010 and 2015 are provided in Table VI 10 and Table VI 11, respectively. In these tables, counties shown in bold/ italics are projected to come into attainment with CAIR.

Table VI 10. Projected PM2.5 Concentrations (

g/ m3) for the 2010 Base Case and CAIR and the Impact of CAIR Regional Controls in 2010.

State County 2010 Base Case 2010 CAIR Impact of CAIR Alabama DeKalb Co 15.23 13.97  1.26 Alabama Jefferson Co 18.57 17.46  1.11 Alabama Montgomery Co 15.12 14.10  1.02 Alabama Morgan Co 15.29 14.11  1.18 Alabama Russell Co 16.17 15.15  1.02 Alabama Talladega Co 15.34 14.00  1.34 Delaware New Castle Co 16.56 14.84  1.72 District of Columbia 15.84 13.68  2.16 436 State County 2010 Base Case 2010 CAIR Impact of CAIR Georgia Bibb Co 16.27 15.17  1.10 Georgia Clarke Co 16.39 14.96  1.43 Georgia Clayton Co 17.39 16.29  1.10 Georgia Cobb Co 16.57 15.35  1.22 Georgia DeKalb Co 16.75 15.70  1.05 Georgia Floyd Co 16.87 15.87  1.00 Georgia Fulton Co 18.02 16.98  1.04 Georgia Hall Co 15.60 14.28  1.32 Georgia Muscogee Co 15.65 14.57  1.08 Georgia Richmond Co 15.68 14.64  1.04 Georgia Walker Co 15.43 14.22  1.21 Georgia Washington Co 15.31 14.22  1.09 Georgia Wilkinson Co 16.27 15.22  1.05 Illinois Cook Co 17.52 16.88  0.64 Illinois Madison Co 16.66 15.96  0.70 Illinois St. Clair Co 16.24 15.54  0.70 Indiana Clark Co 16.51 15.15  1.36 Indiana Dubois Co 15.73 14.37  1.36 Indiana Lake Co 17.26 16.48  0.78 Indiana Marion Co 16.83 15.54  1.29 Indiana Vanderburgh Co 15.54 14.26  1.28 Kentucky Boyd Co 15.23 13.38  1.85 Kentucky Bullitt Co 15.10 13.67  1.43 Kentucky Fayette Co 15.95 14.17  1.78 Kentucky Jefferson Co 16.71 15.44  1.27 Kentucky Kenton Co 15.30 13.72  1.58 Maryland Anne Arundel Co 15.26 12.98  2.28 Maryland Baltimore city 16.96 14.88  2.08 Michigan Wayne Co 19.41 18.23  1.18 Missouri St. Louis City 15.10 14.40  0.70 New Jersey Union Co 15.05 13.60  1.45 New York New York Co 16.19 14.95  1.24 North Carolina Catawba Co 15.48 14.07  1.41 North Carolina Davidson Co 15.76 14.36  1.40 North Carolina Mecklenburg Co 15.22 13.92  1.30 Ohio Butler Co 16.45 15.03  1.42 Ohio Cuyahoga Co 18.84 17.11  1.73 Ohio Franklin Co 16.98 15.13  1.85 Ohio Hamilton Co 18.23 16.61  1.62 Ohio Jefferson Co 17.94 15.64  2.30 Ohio Lawrence Co 16.10 14.11  1.99 Ohio Mahoning Co 15.39 13.40  1.99 437 State County 2010 Base Case 2010 CAIR Impact of CAIR Ohio Montgomery Co 15.41 13.83  1.58 Ohio Scioto Co 18.13 15.98  2.15 Ohio Stark Co 17.14 15.08  2.06 Ohio Summit Co 16.47 14.69  1.78 Ohio Trumbull Co 15.28 13.50  1.78 Pennsylvania Allegheny Co 20.55 18.01  2.54 Pennsylvania Beaver Co 15.78 13.61  2.17 Pennsylvania Berks Co 15.89 13.56  2.33 Pennsylvania Cambria Co 15.14 12.72  2.42 Pennsylvania Dauphin Co 15.17 12.88  2.29 Pennsylvania Delaware Co 15.61 13.94  1.67 Pennsylvania Lancaster Co 16.55 14.09  2.46 Pennsylvania Philadelphia Co 16.65 14.98  1.67 Pennsylvania Washington Co 15.23 12.99  2.24 Pennsylvania Westmoreland Co 15.16 12.60  2.56 Pennsylvania York Co 16.49 14.20  2.29 Tennessee Davidson Co 15.36 14.26  1.10 Tennessee Hamilton Co 16.89 15.57  1.32 Tennessee Knox Co 17.44 16.16  1.28 Tennessee Sullivan Co 15.32 14.01  1.31 West Virginia Berkeley Co 15.69 13.43  2.26 West Virginia Brooke Co 16.63 14.42  2.21 West Virginia Cabell Co 17.03 15.08  1.95 West Virginia Hancock Co 17.06 14.89  2.17 West Virginia Kanawha Co 17.56 15.27  2.29 West Virginia Marion Co 15.32 12.90  2.42 West Virginia Marshall Co 15.81 13.46  2.35 West Virginia Ohio Co 15.14 12.81  2.33 West Virginia Wood Co 16.66 14.14  2.52 Table VI 11. Projected PM2.5 Concentrations (

g/ m3) for the 2015 Base Case and CAIR and the Impact of CAIR Regional Controls in 2015.

State County 2015 Base Case 2015 CAIR Impact of CAIR Alabama DeKalb Co 15.24 13.46  1.78 Alabama Jefferson Co 18.85 17.36  1.49 Alabama Montgomery Co 15.24 13.87  1.37 Alabama Morgan Co 15.26 13.85  1.41 Alabama Russell Co 16.10 14.66  1.44 438 State County 2015 Base Case 2015 CAIR Impact of CAIR Alabama Talladega Co 15.22 13.35  1.87 Delaware New Castle Co 16.47 14.41  2.06 District of Columbia 15.57 13.11  2.46 Georgia Bibb Co 16.41 14.83  1.58 Georgia Chatham Co 15.06 13.86  1.20 Georgia Clarke Co 16.15 14.10  2.05 Georgia Clayton Co 17.46 15.85  1.61 Georgia Cobb Co 16.51 14.67  1.84 Georgia DeKalb Co 16.82 15.29  1.53 Georgia Floyd Co 17.33 15.79  1.54 Georgia Fulton Co 18.00 16.47  1.53 Georgia Hall Co 15.36 13.48  1.88 Georgia Muscogee Co 15.58 14.06  1.52 Georgia Richmond Co 15.76 14.23  1.53 Georgia Walker Co 15.37 13.65  1.72 Georgia Washington Co 15.34 13.67  1.67 Georgia Wilkinson Co 16.54 15.01  1.53 Illinois Cook Co 17.71 16.95  0.76 Illinois Madison Co 16.90 16.07  0.83 Illinois St. Clair Co 16.49 15.64  0.85 Illinois Will Co 15.12 14.27  0.85 Indiana Clark Co 16.37 14.79  1.58 Indiana Dubois Co 15.66 14.16  1.50 Indiana Lake Co 17.27 16.36  0.91 Indiana Marion Co 16.77 15.38  1.39 Indiana Vanderburgh Co 15.56 14.17  1.39 Kentucky Boyd Co 15.06 12.95  2.11 Kentucky Fayette Co 15.62 13.54  2.08 Kentucky Jefferson Co 16.61 15.13  1.48 Kentucky Kenton Co 15.09 13.26  1.83 Maryland Baltimore city 17.04 14.50  2.54 Maryland Baltimore Co 15.08 12.75  2.33 Michigan Wayne Co 19.28 17.95  1.33 Mississippi Jones Co 15.18 14.06  1.12 Missouri St. Louis city 15.34 14.50  0.84 New York New York Co 15.76 14.33  1.43 North Carolina Catawba Co 15.19 13.45  1.74 North Carolina Davidson Co 15.34 13.61  1.73 Ohio Butler Co 16.32 14.67  1.65 Ohio Cuyahoga Co 18.60 16.67  1.93 Ohio Franklin Co 16.64 14.57  2.07 Ohio Hamilton Co 18.03 16.10  1.93 439 State County 2015 Base Case 2015 CAIR Impact of CAIR Ohio Jefferson Co 17.83 15.26  2.57 Ohio Lawrence Co 15.92 13.71  2.21 Ohio Mahoning Co 15.13 12.94  2.19 Ohio Montgomery Co 15.16 13.33  1.83 Ohio Scioto Co 17.92 15.55  2.37 Ohio Stark Co 16.86 14.58  2.28 Ohio Summit Co 16.14 14.18  1.96 Ohio Trumbull Co 15.05 13.08  1.97 Pennsylvania Allegheny Co 20.33 17.47  2.86 Pennsylvania Beaver Co 15.54 13.09  2.45 Pennsylvania Berks Co 15.66 12.99  2.67 Pennsylvania Delaware Co 15.52 13.52  2.00 Pennsylvania Lancaster Co 16.28 13.33  2.95 Pennsylvania Philadelphia Co 16.53 14.53  2.00 Pennsylvania York Co 16.22 13.46  2.76 Tennessee Davidson Co 15.36 14.02  1.34 Tennessee Hamilton Co 16.82 14.94  1.88 Tennessee Knox Co 17.34 15.61  1.73 Tennessee Shelby Co 15.17 14.19  0.98 Tennessee Sullivan Co 15.37 13.77  1.60 West Virginia Berkeley Co 15.32 12.73  2.59 West Virginia Brooke Co 16.51 14.05  2.46 West Virginia Cabell Co 16.86 14.64  2.22 West Virginia Hancock Co 16.97 14.54  2.43 West Virginia Kanawha Co 17.17 14.66  2.51 West Virginia Marshall Co 15.52 12.87  2.65 West Virginia Wood Co 16.69 13.88  2.81 As described in section VI. B. 1, we project that 79 counties in the East will be nonattainment for PM2.5 in the 2010 Base Case. We estimate that, on average, the regional strategy will reduce PM2.5 in these 79 counties by 1.6

g/ m3. In over 90 percent of the nonattainment counties ( i. e., 74 out of 79 counties), we project that PM2.5 will be reduced by at least 1.0 440

g/ m3. In over 25 percent of the 79 nonattainment counties ( i. e., 23 of the 79 counties), we project PM2.5 concentrations will decline by of more than 2.0

g/ m3. Of the 79 counties that are nonattainment in the 2010 Base, we project that 51 counties will come into attainment as a result of the SO2 and NOx emissions reductions expected from the regional controls. Even those 28 counties that remain nonattainment in 2010 after implementation of the regional strategy will be closer to attainment as a result of these emissions reductions.

Specifically, the average reduction of PM2.5 in the 28 residual nonattainment counties is projected to be 1.3

g/ m3. After implementation of the regional controls, we project that 18 of the 28 residual nonattainment counties in 2010 will be within 1.0

g/ m3 of the NAAQS and 12 counties will be within 0.5

g/ m3 of attainment.

In 2015 we are projecting that PM2.5 in the 74 Base Case nonattainment counties will be reduced by 1.8

g/ m3, on average,

as a result of the SO2 and NOx reductions in the regional strategy. In over 90 percent of the nonattainment counties ( i. e., 67 of the 74 counties) concentrations of PM2.5 are predicted to be reduced by at least 1.0

g/ m3. In over 35 percent of the counties ( i. e., 27 of the 74 counties), we project the regional strategy to reduce PM2.5 by more than 2.0

g/ m3. As a result of the reductions in PM2.5, 56 nonattainment counties are projected to come into attainment in 2015. The remaining 18 441 nonattainment counties are projected to be closer to attainment with the regional strategy. Our modeling results indicate that PM2.5 will be reduced in the range of 0.7

g/ m3 to 2.9

g/ m3 in these 18 counties. The average reduction across these 18 residual nonattainment counties is 1.5

g/ m3.

Thus, the SO2 and NOx emissions reductions which will result from the regional strategy will greatly reduce the extent of PM2.5 nonattainment by 2010 and beyond. These emissions reductions are expected to substantially reduce the number of PM2.5 nonattainment counties in the East and make attainment easier for those counties that remain nonattainment by substantially lowering PM2.5 concentrations in these residual nonattainment counties.

2. Estimated Impacts on 8 Hour Ozone Concentrations and Attainment We determined the impacts on 8 hour ozone of the regional strategy by running the CAMx model for this strategy and comparing the results to the ozone concentrations predicted for the 2010 and 2015 Base Cases. In brief, we ran the CAMx model for the regional strategy in both 2010 and 2015. The model predictions were used to project future 8 hour ozone concentrations for the regional strategy in 2010 and 2015 using the Relative Reduction Factor technique, as described in section VI. B. 1. We compared the results of the 2010 and 2015 regional 442 strategy modeling to the corresponding results from the 2010 and 2015 Base Cases to quantify the expected impacts of the regional controls.

The results of the regional strategy ozone modeling are expressed in terms of the expected reductions in projected 8 hour concentrations and the implications for future nonattainment.

The impacts of the regional NOx emissions reductions on 8 hour ozone in 2010 and 2015 are provided in Table VI 12 and Table VI

13, respectively. In these tables, counties shown in bold/ italics are projected to come into attainment with the regional controls.

Table VI 12. Projected 8 hour Concentrations ( ppb) for the 2010 Base Case and CAIR and the Impact of CAIR Regional Controls in 2010.

State County 2010 Base Case 2010 CAIR Impact of CAIR Connecticut Fairfield Co 92.6 92.2  0.4 Connecticut Middlesex Co 90.9 90.6  0.3 Connecticut New Haven Co 91.6 91.3  0.3 District of Columbia District of Columbia 85.2 85.0  0.2 Delaware New Castle Co 85.0 84.7  0.3 Georgia Fulton Co 86.5 85.1  1.4 Maryland Anne Arundel Co 88.8 88.6  0.2 Maryland Cecil Co 89.7 89.5  0.2 Maryland Harford Co 93.0 92.8  0.2 Maryland Kent Co 86.2 85.8  0.4 Michigan Macomb Co 85.5 85.4  0.1 New Jersey Bergen Co 86.9 86.0  0.9 New Jersey Camden Co 91.9 91.6  0.3 New Jersey Gloucester Co 91.8 91.3  0.5 New Jersey Hunterdon Co 89.0 88.6  0.4 New Jersey Mercer Co 95.6 95.2  0.4 443 State County 2010 Base Case 2010 CAIR Impact of CAIR New Jersey Middlesex Co 92.4 92.1  0.3 New Jersey Monmouth Co 86.6 86.4  0.2 New Jersey Morris Co 86.5 85.5  1.0 New Jersey Ocean Co 100.5 100.3  0.2 New York Erie Co 87.3 86.9  0.4 New York Richmond Co 87.3 87.1  0.2 New York Suffolk Co 91.1 90.8  0.3 New York Westchester Co 85.3 84.7  0.6 Ohio Geauga Co 87.1 86.6  0.5 Pennsylvania Bucks Co 94.7 94.3  0.4 Pennsylvania Chester Co 85.7 85.4  0.3 Pennsylvania Montgomery Co 88.0 87.6  0.4 Pennsylvania Philadelphia Co 90.3 89.9  0.4 Rhode Island Kent Co 86.4 86.2  0.2 Texas Denton Co 87.4 86.8  0.6 Texas Galveston Co 85.1 84.6  0.5 Texas Harris Co 97.9 97.4  0.5 Texas Jefferson Co 85.6 85.0  0.6 Texas Tarrant Co 87.8 87.2  0.6 Virginia Arlington Co 86.2 86.0  0.2 Virginia Fairfax Co 85.7 85.4  0.3 Wisconsin Kenosha Co 91.3 91.0  0.3 Wisconsin Ozaukee Co 86.2 85.8  0.4 Wisconsin Sheboygan Co 88.3 87.7  0.6 Table VI 13. Projected 8 hour Concentrations ( ppb) for the 2015 Base Case and CAIR and the Impact of CAIR Regional Controls in 2015.

State County 2015 Base Case 2015 CAIR Impact of CAIR Connecticut Fairfield Co 91.4 90.6  0.8 Connecticut Middlesex Co 89.1 88.4  0.7 444 State County 2015 Base Case 2015 CAIR Impact of CAIR Connecticut New Haven Co 89.8 89.1  0.7 Maryland Anne Arundel Co 86.0 84.9  1.1 Maryland Cecil Co 86.9 85.4  1.5 Maryland Harford Co 90.6 89.6  1.0 Michigan Macomb Co 85.1 84.2  0.9 New Jersey Bergen Co 85.7 84.5  1.2 New Jersey Camden Co 89.5 88.3  1.2 New Jersey Gloucester Co 89.6 88.2  1.4 New Jersey Hunterdon Co 86.5 85.4  1.1 New Jersey Mercer Co 93.5 92.4  1.1 New Jersey Middlesex Co 89.8 88.8  1.0 New Jersey Ocean Co 98.0 96.9  1.1 New York Erie Co 85.2 84.2  1.0 New York Suffolk Co 89.9 89.0  0.9 Pennsylvania Bucks Co 93.0 91.8  1.2 Pennsylvania Montgomery Co 86.5 84.9  1.6 Pennsylvania Philadelphia Co 88.9 87.5  1.4 Texas Harris Co 97.3 96.4  0.9 Texas Jefferson Co 85.0 84.1  0.9 Wisconsin Kenosha Co 89.4 88.8  0.6 As described in section VI. B. 1, we project that 40 counties in the East would be nonattainment for 8 hour ozone under the assumptions in the 2010 Base Case. Our modeling of the regional controls in 2010 indicates that 3 of these counties will come into attainment of the 8 hour ozone NAAQS and that ozone in 16 of the 40 nonattainment counties will be reduced by 1 ppb or more. In addition, our modeling predicts that 8 hour ozone exceedances ( i. e., 8 hour ozone of 85 ppb or higher) within nonattainment areas are expected to decline by 5 percent in 2010 with CAIR. Of the 37 counties that are projected to remain 445 nonattainment in 2010 after the regional strategy, nearly half ( i. e., 16 of the 37 counties) are within 2 ppb of attainment.

In 2015, we project that 6 of the 22 counties which are nonattainment for 8 hour ozone in the Base Case will come into attainment with the regional strategy. Ozone concentrations in over 70 percent ( i. e., 16 of 22 counties) of the 2015 Base Case nonattainment counties are projected to be reduced by 1 ppb or more as a result of the regional strategy. Exceedances of the 8 hour ozone NAAQS are predicted to decline in nonattainment areas by 14 percent with regional controls in place in 2015.

Thus, the NOx emissions reductions which will result from the regional strategy will help to bring 8 hour ozone nonattainment areas in the East closer to attainment by 2010 and beyond.

F. What are the Estimated Visibility Impacts of the Final Rule?

1. Methods for Calculating Projected Visibility in Class I Areas The NPR contained example future year visibility projections for the 20 percent worst days and 20 percent best days at Class I areas that had complete IMPROVE monitoring data in 1996. Changes in future visibility were predicted by using the REMSAD model to generate relative visibility changes, then applying those changes to measured current visibility data.

Details of the visibility modeling and calculations can be found in the NPR AQMTSD. An example visibility calculation was given in Appendix M of the NPR AQMTSD along with the predicted 446 107 The CAIR scenario modeled for the visibility analysis included controls in Arkansas, Delaware, and New Jersey. improvement in visibility ( in deciviews) on the 20 percent best and worst days at 44 Class I areas. The data contained in Appendix M was for informational purposes only and was not used in the significant contribution determination or control strategy development decisions.

The SNPR contained visibility calculations in support of the " better than BART" analysis. The better than BART analysis employed a two pronged test to determine if the modeled visibility improvements from the CAIR cap and trade program for EGU's were " better" than the visibility improvements from a nationwide BART program. The analysis used the visibility calculation methodology detailed in the NPR TSD. Detailed results of the SNPR better than BART analysis are contained in the SNPR AQMTSD. The better than BART analysis for the final rule is addressed in section IX. C. 2 of the preamble. Additional information on the visibility calculation methodology is contained in the NFR AQMTSD.

2. Visibility Improvements in Class I Areas For the NFR we have modeled several new CAIR107 and CAIR +

BART cases to re examine the better than BART two pronged test.

We have modeled an updated nationwide BART scenario as well as a CAIR in the East/ BART in the West scenario. The results were analyzed at 116 Class I areas that have complete IMPROVE data 447 for 2001 or are represented by IMPROVE monitors with complete data. Twenty nine of the Class I areas are in the East and 87 are in the West. The results of the visibility analysis are summarized in section IX. C. 2. Detailed results for all 116 Class I areas are presented in the NFR AQMTSD.

VII. SIP Criteria and Emissions Reporting Requirements This section describes: ( 1) the criteria we will use in determining approvability of SIPs submitted to meet the requirements of today's rulemaking; ( 2) the dates for submittal of the SIPs that are required under the CAIR; ( 3) the consequences of either failing to submit such a SIP or submitting a SIP which is disapproved; and ( 4) the emissions inventory reporting requirements for States.

A. What Criteria Will EPA Use to Evaluate the Approvability of a Transport SIP?

1. Introduction The approvability criteria for CAIR SIP submissions are finalized today in 40 CFR 51.123 ( NOx emissions reductions) and in 40 CFR 51.124 ( SO2 emissions reductions). Most of the criteria are substantially similar to those that currently apply to SIP submissions under CAA section 110 or part D 448 ( nonattainment). For example, each submission must describe the control measures that the State intends to employ, identify the enforcement methods for monitoring compliance and managing violations, and demonstrate that the State has legal authority to carry out its plan.

This part of the preamble explains additional approvability criteria specific to the CAIR that were proposed and discussed in the CAIR NPR or in the CAIR SNPR, and are being promulgated today. As explained in both the CAIR NPR and the CAIR SNPR, EPA proposed that each affected State must submit SIP revisions containing control measures that assure that a specified amount of NOx and SO2 emissions reductions are achieved by specified dates.

Although EPA determined the amount of emissions reductions required by identifying specific, highly cost effective control levels for EGUs, EPA explained in the CAIR NPR and the CAIR SNPR that States have flexibility in choosing which sources to control to achieve the required emissions reductions. As long as a State's emissions reductions requirements are met, a State may impose controls on EGUs only, on non EGUs only, or on a combination of EGUs and non EGUs. The SIP approvability criteria are intended to provide as much certainty as possible that, whichever sources a State chooses to control, the controls will result in the required amount of emissions reductions. 449 In the CAIR NPR, EPA proposed a " hybrid" approach for the mechanisms used to ensure emissions reductions are achieved.

This approach incorporates elements of an emissions " budget"

approach ( requiring an emissions cap on affected sources) and an " emissions reduction" approach ( not requiring an emissions cap).

In this hybrid approach, if States impose control measures on EGUs, they would be required to impose an emissions cap on all EGUs, which would effectively be an emissions budget. And, as stated in the CAIR NPR, if States impose control measures on non EGUs, they would be encouraged but not required to impose an emissions cap on non EGUs. In the CAIR NPR, we requested comment on the issue of requiring States to impose caps on any source categories that the State chooses to regulate.

In the CAIR SNPR, we proposed to modify the hybrid approach and require States that choose to control large industrial boilers or turbines ( greater than 250 MMBTU/ hr) to impose an emissions cap on all such sources within their State. This is similar to EPA's approach in the NOx SIP Call which required States to include an emissions cap on such sources as well as on EGUs if the SIP submittals included controls on such sources.

( See 40 CFR 51.121( f)( 2)( ii).)

A few commenters supported the use of emissions caps on any source category subject to CAIR controls, including non EGUs,

because it would be the most effective way to demonstrate compliance with the budget. A few other commenters opposed the 450 use of an emissions cap on non EGUs, saying either that States should have the flexibility to determine whether to impose a cap, or that such a requirement would result in increased costs for non EGUs including cogeneration units that are non EGUs. No commenter opposing such a requirement provided any information indicating that such a requirement would be ineffective or impracticable. Today EPA is adopting the modified approach, as described in the CAIR SNPR, that States choosing to control EGUs or large industrial boilers or turbines must do so by imposing an emissions cap on such sources, similar to what was required in the NOx SIP Call.

Extensive comments were received regarding the need for an ozone season NOx cap in States identified to be contributing significantly to the region's ozone nonattainment problems. In proposal, EPA stated that the annual NOx cap under CAIR reduced NOx emissions sufficiently enough to not warrant a regional ozone season NOx cap. Commenters remained very concerned that the annual NOx cap would not aid ozone attainment. While EPA feels that the annual NOx limit will most likely be protective in the ozone season, a seasonal cap will provide certainty,

which EPA agrees is very important in the effort to help areas achieve ozone attainment. Today, EPA is finalizing an ozone season NOx cap for States shown to contribute significantly for ozone. As is further explained in section VIII, EPA is also finalizing an ozone season trading program that States may use 451 to achieve the required emissions reductions. This program will subsume the existing NOx SIP Call trading program. Therefore,

any State that wishes to continue including its sources in an interstate trading program run by EPA to achieve the emissions reductions required by EPA must modify its SIP to conform with this new trading program.

The EPA will automatically find that a State is continuing to meet its NOx SIP Call obligation if it achieves all of its required CAIR emissions reductions by capping EGUs, it modifies its existing NOx SIP Call to require its non EGUs currently participating in the NOx SIP Call budget trading program to conform to the requirements of the CAIR ozone season NOx trading program with a trading budget that is the same or tighter than the budget in the currently approved SIP, and it does not modify any of its other existing NOx SIP Call rules. If a State chooses to achieve the ozone season NOx emissions reduction requirements of CAIR in another way, it will also be required to demonstrate that it continues to meet the requirements of the NOx SIP Call.

Specific criteria for approval of CAIR SIP submissions as promulgated by today's action are described below. The criteria are dependent on the types of sources a State chooses to control.

2. Requirements for States Choosing to Control EGUs 452 a. Emissions Caps and Monitoring As explained in the CAIR NPR ( 69 FR 4626), and in the CAIR SNPR ( 69 FR 32691), EPA proposed requiring States to apply the " budget" approach if they choose to control EGUs; that is, each State must cap total EGU emissions at the level that assures the appropriate amount of reductions for that State. The requirement to cap all EGUs is important because it prevents shifting of utilization ( and resulting emissions) to uncapped EGUs. The EGUs are part of a highly interconnected electricity grid that makes utilization shifting likely and even common.

The units are large and offer the same market product ( i. e.,

electricity), and therefore the units that are least expensive to operate are likely to be operated as much as possible. If capped and uncapped units are interconnected, the uncapped units' costs would tend to decrease relative to the capped units, which must either reduce emissions or use or buy allowances, and the uncapped units' utilization would likely increase. The cap ensures that emissions reductions from these interconnected sources are actually achieved rather than emissions simply shifting among sources. The caps constitute the State EGU Budgets for SO2 and NOx. Additionally, EPA proposed that, if States choose to control EGUs, they must require EGUs to follow part 75 monitoring, recordkeeping, and reporting requirements. Part 75 monitoring and reporting 453 requirements have been used effectively for determining NOx and SO2 emissions from EGUs under the title IV Acid Rain program and the NOx SIP Call program and in combination with emissions caps are an integral part of those programs. ( Additional explanation for the need for Part 75 monitoring is given in the NPR and SNPR and is incorporated here.) Therefore, today, EPA adopts the requirements for emission caps and Part 75 monitoring for EGUs in these States.

b. Using the Model Trading Rules As proposed, if a State chooses to allow its EGUs to participate in EPA administered interstate NOx and SO2 emissions trading programs, the State must adopt EPA's model trading rules, as described elsewhere in today's preamble and in § § 96.101 96.176 ( for NOx) and § § 96.201 96.276 ( for SO2), set forth below. Additionally, EPA proposed that for the States for which EPA made a finding of significant contribution for both ozone and PM2.5, participation in both the NOx and SO2 trading programs would be required in order to be included in the EPAadministered program. States for which the finding was for ozone only could choose to participate in only the EPAadministered NOx trading program through adoption of the NOx model trading rule. The EPA stated that States adopting EPA's model trading rules, modified only as specifically allowed by EPA, will meet the requirement for applying an emissions cap and 454 requirement to use part 75 monitoring, recordkeeping, and reporting for EGUs.

Some commenters opposed EPA's proposal to require participation in both the NOx and SO2 trading programs because some States may want to participate in the EPA administered trading programs for only NOx or only SO2. A few commenters claimed that the requirement to participate in both programs would limit State flexibility or is an " all or nothing"

approach; other commenters objected that there was no environmental basis for such a requirement; and one commenter suggested that States not affected by CAIR but that volunteer to control emissions should be permitted to join the program for one or both pollutants. Additionally, commenters cited a need for an ozone season NOx program.

The EPA has taken the comments into account and in today's action agrees to allow a State identified to contribute significantly for PM2.5 ( and therefore required to make annual SO2 and NOx reductions) to participate in the EPA administered CAIR trading program for either SO2 or NOx, not necessarily both, so long as the State adopts the model rule for the applicable trading program.

In response to extensive comments relating to EPA's proposal to forego a seasonal NOx cap because EPA demonstrated that the annual NOx cap was sufficiently stringent, EPA is finalizing an ozone season NOx trading program for States 455 identified as contributing significantly for ozone. These States will be subject to an ozone season NOx cap and an annual NOx cap if the State is also identified as contributing significantly for PM 2.5. Therefore, today's action includes an additional model rule for an ozone season NOx trading program ( 40 CFR 96, subparts AAAA through IIII). The States that may use the ozone season NOx trading program but not the annual NOx trading program are those States in the CAIR region identified as contributing significantly for ozone only ( Arkansas,

Connecticut, Delaware, Massachusetts, and New Jersey).

As discussed in the proposal, EPA is finalizing the option for New Hampshire and Rhode Island to participate in the regional trading program through use of the CAIR ozone season NOx model rule because sources in these States have made investments in NOx controls in the past based on the existence of a regional ozone season NOx trading program. Additionally,

the States' combined projected 2010 and 2015 NOx emissions are less than one half of one percent of the total CAIR regional NOx cap and therefore would not create a significant increase in the CAIR cap. All comments received were supportive of this approach and EPA is finalizing it today.

None of these States ( Arkansas, Connecticut, Delaware,

Massachusetts, New Hampshire, New Jersey, or Rhode Island) has the option to participate in the EPA administered CAIR SO2 trading program nor the annual CAIR NOx trading program because 456 108Title IV allowances can however be traded freely across the boundary of the CAIR region without any significant, negative environmental consequence. The potential negative consequences have been addressed through other requirements discussed below, like the retirement of excess title IV allowances. there are no PM2.5 related emissions reductions required under today's action in those States. ( Of course, sources in these States will still be subject to the Acid Rain SO2 cap and trade program.) Likewise, Texas, Minnesota and Georgia may not participate in the ozone season NOx program, because they have not been shown to contribute significantly to the regional ozone problem. They are, however, required to make annual NOx and SO2 reductions and may choose to participate in the annual NOx and annual SO2 trading program to meet their CAIR obligations.

Except for the special cases of Rhode Island and New Hampshire, other States outside of the CAIR region may not participate in the CAIR trading programs for either pollutant,

because they were not shown to contribute significantly to PM2.5 or ozone nonattainment in the CAIR region. Allowing States outside of the CAIR region to participate would generally create an opportunity    through net sales of allowances from the non

CAIR States to CAIR States for emission increases in States that have been shown to contribute significantly to nonattainment in the CAIR region. 108 A State may not participate in the EPA administered trading programs if they choose to get a portion of CAIR reductions from 457 non EGUs. ( This is also discussed in Section VIII.) EPA maintains that requiring certain consistencies among States in the regionwide trading programs that EPA has offered to run does not unfairly limit States' flexibility to choose an approach for achieving CAIR mandated reductions that is best suited for a particular State's unique circumstances. States are free to achieve the reductions through whatever alternative mechanisms the States wish to design; for example, a group of States could cooperatively implement their own multi State trading programs that EPA would not administer.

c. Using a Mechanism Other than the Model Trading Rules If States choose to control EGUs through a mechanism other than the EPA administered NOx and SO2 emissions trading programs, then the States ( i) must still impose an emissions cap on total EGU emissions and require part 75 monitoring,

recordkeeping, and reporting requirements on all EGUs, and ( ii)

must use the same definition of EGU as EPA uses in its model trading rules, i. e., the sources described as " CAIR units" in § 96.102, § 96.202, and § 96.302. A few commenters expressed concern that these requirements limit States' discretion in designing control measures to meet the CAIR requirements, but failed to offer any reason why the requirements would be impracticable or ineffective. The EPA believes that the requirements are necessary for a number of reasons. The 458 requirements to cap all EGUs and to use the same definition of EGU are important because they prevent shifting of utilization ( and resulting emissions) from capped to uncapped sources. In this case, not requiring a cap on total EGU emissions in these States is likely to result in increased utilization and consequently increased emissions in these States. The requirement to use part 75 monitoring ensures the accuracy of monitored data and consistency of reporting among sources ( and thus the certainty that emissions reductions actually occurred)

across all States. Furthermore, most EGUs are currently monitoring and reporting using part 75 so it does not impose an additional requirement. Therefore, EPA is finalizing the proposed approach.

If a State chooses to design its own intrastate or interstate NOx or SO2 emissions trading programs, the State must, in addition to meeting the requirements of the rules finalized in today's action, consider EPA's guidance, " Improving Air Quality with Economic Incentive Programs," January, 2001 ( EPA 452/ R 01 001) ( available on EPA's website at:

http:// www. epa. gov/ ttn/ ecas/ incentiv. html). The State's programs are subject to EPA approval. The EPA will not administer a State designed trading program. Additionally, it should be noted that allowances from any alternate trading program may not be used in the EPA administered trading programs. 459 d. Retirement of Excess Title IV Allowances The CAIR NPR proposed requirements on SIPs relating to the effects of title IV SO2 allowance allocations for 2010 and beyond that are in excess of the State's CAIR EGU SO2 emissions budget. The requirements were intended to ensure that the excess is not used in a manner that would lead to a significant increase in supply of title IV allowances, the collapse of the price of title IV allowances, the disruption of operation of the title IV allowance market and the title IV SO2 cap and trade system, and the potential for increased emissions in all States prior to 2010 and in non CAIR States in 2010 and later. These negative impacts on the title IV allowance market and on air quality, which are discussed in detail in section IX. B. below,

would undermine the efficacy of the title IV program and could erode confidence in cap and trade programs in general. To avoid these impacts, EPA proposed to require retirement of the excess title IV allowances through a retirement ratio mechanism.

The EPA proposed, as a mechanism for removing these additional allowances and meeting the 50 percent reduction required under phase I ( 2010 2014), that each affected EGU had to hold, and EPA would retire, two vintage 2010 2014 allowances for every ton of SO2 that the unit emits. Further, EPA proposed that, for phase II ( which begins in 2015) when a 65 percent reduction is required, each affected EGU had to hold, and EPA 460 would retire, three vintage 2015 and beyond allowances for every ton of SO2 that the unit emits. This 3 to 1 ratio would result in slightly more reductions than EPA has determined were necessary to eliminate the significant contribution by an upwind State.

In the CAIR SNPR, EPA proposed two alternatives for addressing the issue of the additional allowances. Under the first alternative, affected EGUs had to hold, and EPA would retire, vintage 2015 and beyond allowances at a rate of 2.86 to

1 rather than 3 to 1, which would result in exactly the amount of reductions EPA has determined are necessary to eliminate a State's significant contribution.

Alternatively, also in the CAIR SNPR, EPA proposed requiring the retirement of 2015 and beyond vintage allowances at a 3 to 1 ratio and permitting States to convert the additional reductions into allowances in their rules. The EPA also suggested that some States may want to use these reserved allowances to create an incentive for additional local emissions reductions that will be needed to bring all areas into attainment with the PM2.5 NAAQS.

As part of today's final CAIR rulemaking, EPA is finalizing a ratio of 2.86 to one. The ratio ultimately represents a reduction of 65 percent from the final title IV cap level, which has been found to be highly cost effective. For a detailed discussion regarding EPA's determination of highly cost 461 effective, please refer to Section IV of the final CAIR preamble. As discussed earlier, EPA must employ a uniform ratio across sources to ensure consistency and the same costeffectiveness level across sources. Therefore, EPA will use a Phase II ratio of 2.86 to 1 for all States affected by CAIR who choose to participate in the trading program.

Today, EPA is finalizing the general requirement that all SIPs must include a mechanism to ensure that excess SO2 allowances are retired. Furthermore, for States that participate in the EPA administered cap and trade program, EPA is finalizing a specific mechanism that States must use.

i. States Participating in the EPA Administered SO2 Trading Program If a State chooses to participate in the EPA administered trading program, the State's excess title IV allowance retirement mechanism must follow the provisions of the SO2 model trading rule that requires that vintage 2010 through 2014 title IV allowances be retired at a ratio of two allowances for every ton of emissions and that vintage 2015 and beyond title IV allowances be retired at a ratio of 2.86 allowances for every ton of emissions. Pre 2010 vintage allowances would be retired at a ratio of one allowance for every ton of emissions. ( See discussion of the model SO2 cap and trade rule in section VIII of today's preamble.) States using the model SO2 cap and trade 462 rule satisfy the requirement for retirement of excess title IV allowances.

ii. States not Participating in the EPA Administered SO2 Trading Program In the CAIR NPR, EPA stated that if a State does not choose to participate in the EPA administered trading programs but controls only EGUs, the State may choose the specific method to retire allowances in excess of its budget. The EPA considered alternative ways for retiring these excess allowances and, as stated in the CAIR SNPR, believed that the use by different States of different means to address this concern could undermine the regionwide emissions reduction goals of the CAIR rulemaking. The EPA further described its concerns in section II of the preamble to the CAIR SNPR. ( See 69 FR 32686 32688.)

Because of these concerns, in the CAIR SNPR, EPA withdrew the CAIR NPR proposal on this point and re proposed that all States use a 2 for 1 retirement ratio for vintage 2010 through 2014 allowances and a 2.86 for 1 or a 3 for 1 retirement ratio for vintage 2015 and beyond allowances to address concerns about title IV allowances that exceed State budgets. The EGUs would have a total emissions cap enforced by the State. The SNPR described that for sources affected by both title IV and CAIR,

allowance deductions and associated compliance determinations would be sequential. That is, title IV compliance would be 463 determined and then CAIR compliance would be determined. So, in 2010 2014, after surrendering one vintage 2010 through 2014 allowance for each ton of emissions for title IV compliance, the source would then surrender one additional allowance ( for a total of two allowances for each ton which meets the CAIR requirement). Similarly, in 2015 and beyond, after surrendering one vintage 2015 and beyond allowance for each ton of emissions for title IV compliance, the source would surrender 1.86 or 2 additional allowances and therefore meet the CAIR requirement.

Commenters argued that in States where EGUs are not trading under CAIR that the excess title IV allowances could be removed in a variety of ways and that EPA did not need to require each State do this the same way, only that each State ensure that they are removed.

Today, EPA adopts the following requirement: if a State does not choose to participate in the EPA administered trading programs but controls only EGUs, the State must include in its SIP a mechanism for retiring the excess title IV allowances ( i. e., the difference between total allowance allocations in the State and the State EGU SO2 budget). To meet this requirement,

the State may use the above described retirement mechanism or may develop a different mechanism that will achieve the required retirement of excess allowances. 464 3. Requirements for States Choosing to Control Sources Other than EGUs a. Overview of Requirements As noted in both the CAIR NPR and the CAIR SNPR, if a State chooses to require emissions reductions from non EGUs, the State must adopt and submit SIP revisions and supporting documentation designed to quantify the amount of reductions from the non EGU sources and to assure that the controls will achieve that amount. Although EPA did not propose in the CAIR NPR that States be required to impose an emissions cap on those sources,

but instead solicited comment on the issue, EPA proposed in the CAIR SNPR that States be required to impose an emissions cap in certain cases on non EGU sources. ( See discussion in VII. A. 1 of today's preamble.)

If a State chooses to obtain some, but not all, of its required reductions for SO2 or NOx emissions from non EGUs, it would still be required to set an EGU budget for SO2 or NOx respectively, but it would set such a budget at some level higher than shown in Tables V 1, V 2, or V 4 in today's preamble, thus allowing more emissions from EGUs. The difference between the amount of a State's SO2 budget in Table V 1 and a State's selected higher EGU SO2 budget would be the amount of SO2 emissions reductions the State demonstrates it will achieve from non EGU sources. By the same token, the 465 109In the CAIR SNPR, EPA mistakenly cited the EGU budget numbers from Tables VI 9 and VI 10 in the CAIR NPR ( 69 FR 4619 20) when it should have cited Tables II 1 and II 2 in the CAIR SNPR. The EPA used the correct numbers, however, in the proposed regulatory text in the CAIR SNPR ( 69 FR 32729 30 and 69 FR 32733 34 ( § § 51.123( e)( 2) and 51.124( e)( 2)). difference between the amount of a State's annual NOx budget in Table V 2 and a State's selected higher annual EGU NOx budget would be the amount of annual NOx emissions reductions the State demonstrates it will achieve from non EGU sources. 109 Further,

the difference between the amount of a State's seasonal NOx budget in Table V 4 and a State's selected higher ozone season EGU NOx budget would be the amount of ozone season NOx emissions reductions the State demonstrates it will achieve from non EGU sources.

Special concerns about SO2 allowances In the case where a State requires a portion of its SO2 emissions reductions from non EGU sources and a portion from EGUs, there remains a concern about the impact of excess title IV allowances above a State's EGU cap, particularly on the operation of the title IV SO2 cap and trade program.

Consequently, today, we are adopting the requirement that these States include a mechanism for retirement of the allowances in excess of the State's SO2 budget.

Like a State choosing to control only EGUs but not to participate in the trading program, a State that chooses to 466 control non EGUs and EGUs must adopt a mechanism for retiring surplus title IV allowances. The number of title IV allowances that must be retired is equal to the difference between the number of title IV allowances allocated to EGUs in that State and the SO2 budget the State sets for EGUs under this rule. If the State uses a retirement mechanism ( as discussed in VII. A. 2. d.) in which a source surrendering allowances under the title IV SO2 cap and trade program surrenders more allowances than otherwise required under title IV, the total number of allowances surrendered per ton of emissions in this case will be less than 2 to 1 in Phase 1 and less than 2.86 to 1 in Phase 2.

This is because the non EGUs will control to achieve a portion of the CAIR SO2 reduction required, and so there will be a smaller surplus of title IV allowances than if all the required reductions were achieved by EGUs. The appropriate retirement factor will equal two times the State's SO2 budget in Phase I or 2.86 times the State's SO2 budget in Phase II as noted in Table V 1 of the budget section, divided by the State's selected higher EGU SO2 budget ( taking into account non EGU reductions).

The factor could then be used as the EGU retirement ratio for compliance purposes in a scenario where a State has decided to control SO2 emissions from EGUs through a mechanism other than the EPA administered trading program.

A simplified example can help illustrate this. Let us assume a State's sources were allocated a total of 200 467 allowances under title IV. Under CAIR, in Phase I, the State's reduction requirement would thus be 100 tons. Suppose this State decided that 25 tons would be reduced by non EGUs and the remaining 75 tons would be reduced by the EGUs. ( The State's budget for EGUS would increase to 125 tons.) The State would also need to retire 75 excess title IV allowances. This could be accomplished by requiring each Acid Rain source to surrender a total of 1.6 vintage 2010 through 2014 allowances ( 200 allowances allocated in the State / 125 tons in State EGU budget) per ton of SO2 emissions. The allowances surrendered would satisfy the Acid Rain Program requirement of surrendering one allowance per ton of emissions, as well as achieving the additional retirement requirement under CAIR since 200 allowances would be used for EGUs to emit the EGU budget of 125 tons of SO2. ( Pre 2010 allowances continue to be available for use on a one allowance per ton of emissions basis here as in other situations.)

This is consistent with EPA's overall approach. If this same State decided to get all reductions ( i. e., 100 tons) from EGUs, the State would require EGUs to retire 100 additional allowances by surrendering a total of 2 vintage 2010 through 2014 allowances ( 200 allowances allocated in the State / 100 tons in State EGU budget) per ton of SO2 emissions.

The demonstration of emissions reductions from non EGUs is a critical requirement of the SIP revision due from a State that 468 chooses to control non EGUs. The State must take into account the amount of emissions attributable to the source category in both ( i) the base case, in the implementation years 2010 and 2015, i. e., without assuming any SIP required reductions under the CAIR from non EGUs; and ( ii) in the control case, in the implementation years 2010 and 2015, i. e., assuming SIP required reductions under the CAIR from non EGUs. We proposed an alternative methodology for calculating the base case for certain large non EGU sources, as described below, but generally the difference between emissions in the base case and emissions in the control case equals the amount of emissions reductions that can be claimed from application of the controls on non

EGUs. ( See discussion later in this section for criteria applicable to development of the baseline and projected control emissions inventories.)

States that meet the lesser of their CAIR ozone season NOx budget or NOx SIP Call EGU trading budget using the CAIR ozone season NOx trading program also satisfy their NOx SIP Call requirements for EGUs. States may also choose to include all of their NOx SIP Call non EGUs in the CAIR ozone season NOx program at their NOx SIP Call levels ( i. e., the non EGU trading budget remains the same).

To the extent EPA allows through the Regional Haze Rule and a State then chooses to use EPA analysis to show that CAIR reductions from EGUs meet BART requirements, States that achieve 469 a portion of their CAIR reductions from sources other than EGUs and wanting to show that even with those reductions the EGUs will meet BART requirements must make a supplemental demonstration that BART requirements are satisfied.

b. Eligibility of Non EGU Reductions In the CAIR SNPR, EPA proposed that, in evaluating whether emissions reductions from non EGUs would count towards the emissions reductions required under the CAIR, States may only include reductions attributable to measures that are not otherwise required under the CAA. Specifically, EPA proposed that States must exclude non EGU reductions attributable to measures otherwise required by the CAA, including: ( 1) measures required by rules already in place at the date of promulgation of today's final rule, such as adopted State rules, SIP revisions approved by EPA, and settlement agreements; ( 2)

measures adopted and implemented by EPA ( or other Federal agencies) such as emissions reductions required pursuant to the Federal Motor Vehicle Control Program for mobile sources ( vehicles or engines) or mobile source fuels, or pursuant to the requirements for National Emissions Standards for Hazardous Air Pollutants; and ( 3) specific measures which are mandated under the CAA ( which may have been further defined by EPA rulemaking)

based on the classification of an area which has been designated 470 nonattainment for a NAAQS, such as vehicle inspection and maintenance programs.

In discussing this proposal, EPA noted that States required to make CAIR SIP submittals may also be required to make separate SIP submittals to meet other requirements applicable to non EGUs, e. g., nonattainment SIPs required for areas designated nonattainment under the PM2.5 or 8 hour ozone NAAQS or regional haze SIPs. The EPA noted it is likely that CAIR SIP submittals will be due before or at the same time as some of these other SIP submittals. We therefore proposed that States relying on reductions from controls on non EGUs must commit in the CAIR SIP revisions to replace the emissions reductions attributable to any CAIR SIP measure if that measure is subsequently determined to be required to meet any other SIP requirement.

Some commenters objected to the proposed exclusion of credit for measures which are mandated under the CAA based on the classification of an area which has been designated nonattainment for a NAAQS, as well as to the proposed requirement that such measures must be replaced if they are later determined to be required in meeting separate SIP requirements. These commenters reasoned that such a requirement would not be applied to EGUs and would impose unnecessary and costly burdens on non EGUs, thus creating an incentive for States to avoid controlling non EGUs and to impose all CAIR reduction requirements on EGUs. One commenter further objected 471 that, as long as a measure was not included in the base case EPA used to determine a State's contribution to other States'

nonattainment under CAA section 110( a)( 2)( D), there is no justification for excluding CAIR credit for such measure, and that EPA's proposed exclusion of credit for any measure " otherwise required by the CAA" is inconsistent with the NOx SIP Call.

In response to these comments, EPA agrees that it is not appropriate to apply this proposed restriction inconsistently to EGUs and non EGUs. Thus, EPA is adopting a modified form of the proposed criteria for the eligibility of non EGU emissions reductions, eliminating the requirement that States must exclude non EGU reductions attributable to measures otherwise required by the CAA based on the classification of an area which has been designated nonattainment for a NAAQS. Consequently, the final rule allows credit for measures that a State later adopts in response to requirements which result from an area's nonattainment classification, such as reasonably available control technology ( RACT). With this change, all emissions reductions are eligible for credit in meeting CAIR except: ( 1)

measures adopted or implemented by the State as of the date of promulgation of today's final rule, such as adopted State rules,

SIP revisions approved by EPA, and settlement agreements; and ( 2) measures adopted or implemented by the Federal government ( e. g., EPA or other Federal agencies) as of the date of 472 submission of the SIP revision by the State to EPA, such as emissions reductions required pursuant to the Federal Motor Vehicle Control Program for mobile sources ( vehicles or engines)

or mobile source fuels, or pursuant to the requirements for National Emissions Standards for Hazardous Air Pollutants.

This exclusion of credit is consistent with EPA's approach in the NOx SIP Call, although a direct comparison of the creditability requirements in the CAIR and in the NOx SIP Call is not possible due to the timing and context in which both rules were developed. The NOx SIP Call used statewide budgets for all sources as an accounting tool to determine the adequacy of a strategy, while the CAIR takes a different approach in which baseline emission inventories for non EGU sectors will, if needed, be developed later. The NOx SIP Call did, as does the CAIR, restrict States from taking credit for any Federal measures adopted after promulgation of the rule ( 63 FR 57427

28). It also did not allow credit for already adopted measures,

but the timing of the NOx SIP Call was such that nonattainment planning measures would have already likely been adopted as the SIP deadlines for adoption of such measures had passed. In today's action, nonattainment planning measures adopted after the promulgation of today's rule will be allowed credit under CAIR.

In order to take credit for CAIR reductions from non EGUs,

the reductions must be beyond what is required under the NOx SIP 473 Call. That is, a reduction must be in the non ozone season or it must be beyond what is expected in the ozone season.

Nonozone season reductions must also be beyond what is in the base case, particularly for units that have low NOx burners and certain SCRs ( e. g., ones required to be run annually). The reductions must be in addition to those already expected. If ozone season reductions are considered, the non EGU NOx SIP Call trading budget must be adjusted by the increment of CAIR reductions beyond the levels in the NOx SIP Call. This removes the corresponding allowances from the market and ensures that the emissions do not shift to other sources.

After evaluating the eligibility of non EGU reductions in accordance with the requirements discussed here, States must exclude credit for ineligible measures by ( i) including such measures in both the baseline and controlled emissions inventory cases, if they have already been adopted; or ( ii) excluding them from both the base and control emissions inventory cases if they have not yet been adopted. ( See discussion later in this section regarding development of emissions inventories and demonstration of non EGU reductions.)

c. Emissions Controls and Monitoring As noted in section VII. A. 1., we modified the " hybrid"

approach described in the CAIR NPR as it applies to certain non

EGUs, and adopt today the approach described in the CAIR SNPR. 474 Specifically, for States that choose to impose controls on large industrial boilers and turbines, i. e., those whose maximum design heat input is greater than 250 mmBtu/ hr, to meet part or all of their emissions reductions requirements under the CAIR,

State rules must include an emissions cap on all such sources in their State. Additionally, in this situation, States must require those large industrial boilers and turbines to meet part 75 requirements for monitoring and reporting emissions as well as recordkeeping. This ensures consistency in measurement and certainty of reductions and has been proven technologically and economically feasible in other programs.

If a State chooses to control non EGUs other than large industrial boilers and turbines to obtain the required emissions reductions, the State must either ( i) impose the same requirements, i. e., an emissions cap on total emissions from non EGUs in the source category in the State and part 75 monitoring, reporting and recordkeeping requirements; or ( ii)

demonstrate why such requirements are not practicable. In the latter case, the State must adopt appropriate alternative requirements to ensure that emissions reductions are being achieved using methods that quantify those emissions reductions,

to the extent practicable, with the same degree of assurance that reductions are being quantified for EGUs and non EGU boilers and turbines using part 75 monitoring. This is to ensure that, regardless of how a State chooses to meet the CAIR 475 110The many EPA guidance documents and tools for preparing emission inventory estimates for SO2 and NOx are available at the following websites: http:// www. epa. gov/ ttn/ chief/ net/ general. html, http:// www. epa. gov/ ttn/ chief/ eiip/ techreport/, http:// www. epa. gov/ ttn/ chief/ publications. html# general, emissions reduction requirements, all reductions made by States to comply with the CAIR have the same, high level of certainty as that achieved through the cap and trade approach. Further,

if a State adopts alternative requirements that do not apply to all non EGUs in a particular source category ( defined to include all sources where any aspect of production of one or more such sources is reasonably interchangeable with that of one or more other such sources), the State must demonstrate that it has analyzed the potential for shifts in production from the regulated sources to unregulated or less stringently regulated sources in the same State as well as in other States and that the State is not including reductions attributable to sources that may shift emissions to such unregulated or less regulated sources.

d. Emissions Inventories and Demonstrating Reductions To quantify emissions reductions attributable to controls on non EGUs, the States must submit both baseline and projected control emissions inventories for the applicable implementation years. We have issued many guidance documents and tools for preparing such emissions inventories, some of which apply to specific sectors States may choose to control. 110 While much of 476 http:// www. epa. gov/ ttn/ chief/ software/ index. html, and http:// www. epa. gov/ ttn/ chief/ efinformation. html.

111The 2010 modeling date is relevant for both SO2 and NOx even though NOx requirements begin in 2009. See Section IV for discussion. that guidance is applicable to today's rulemaking, there are some key differences between quantification of emissions reduction requirements under a SIP designed to help achieve attainment with a NAAQS and emissions reduction requirements under a SIP designed to reduce emissions that contribute significantly to a downwind State's nonattainment problem or interfere with maintenance in a downwind State. Because States are taking actions as a result of their impact on other States,

and because the impacted States have no authority to reduce emissions from other States, the emissions reduction estimates become even more important. ( For a complete discussion, see 69 FR 32693; June 10, 2004.)

Specifically, when we review CAIR SIPs for approvability,

we intend to review closely the emissions inventory projections for non EGUs to evaluate whether emissions reduction estimates are correct. We intend to review the accuracy of baseline historical emissions for the subject sources, assumptions regarding activity and emissions growth between the baseline year and 2010111 and 2015, and assumptions about the effectiveness of control measures. 477 Before describing the specific steps involved in this quantification process, EPA notes that a few commenters objected to the proposed requirements as arbitrary restrictions intended to discourage States' discretion in imposing control measures on non EGUs since these requirements would use what the commenters describe as extremely conservative emissions baseline and emissions reduction estimates. No commenter refuted EPA's explanation, noted above, of the need for stringent requirements to ensure greater accuracy of emission inventories and greater certainty of reduction estimates used in SIPs addressing transported pollutants. The EPA maintains that the need for more accurate inventories and more certain reduction estimates justifies the requirements discussed below. Further, no commenter provided an alternate method of addressing EPA's concerns about the development of such inventories and reduction estimates. Thus, EPA is finalizing its proposed approach.

iii. Historical Baseline To quantify non EGU reductions, as the first step, a historical baseline must be established for emissions of SO2 or NOx from the non EGU source( s) in a recent year. The historical baseline inventory should represent actual emissions from the sources prior to the application of the controls. We expect that States will choose a representative year ( or average of several years) during 2002 2005 for this purpose. 478 The requirements for estimating the historical baseline inventory that follow reflect EPA's view that, when States assign emissions reductions to non EGU sources, achievement of those reductions should carry a high degree of certainty, just as EGU reductions can be quantified with a high degree of certainty in accordance with the applicable part 75 monitoring requirements. Because the non EGU emissions reductions are estimated by subtracting controlled emissions from a projected baseline, if the historical baseline overestimates actual emissions, the estimated reductions could be higher than the actual reductions achieved.

For non EGU sources that are subject to part 75 monitoring requirements, historical baselines must be derived from actual emissions obtained from part 75 monitored data. For non EGU sources that do not have part 75 monitoring data, historical baselines must be established that estimate actual emissions in a way that matches or approaches as closely as possible the certainty provided by the part 75 measured data for EGUs. For these sources, States must estimate historical baseline emissions using source specific or category specific data and assumptions that ensure a source's or source category's actual emissions are not overestimated.

To determine the baseline for sources that do not have part 75 measured data, States must use emission factors that ensure that emissions are not overestimated ( e. g., emission factors at 479 the low end of a range when EPA guidance presents a range) or the State must provide additional information that shows with reasonable confidence that another value is more appropriate for estimating actual emissions. Other monitoring or stack testing data can be considered, but care must be taken not to overestimate baselines. If a production or utilization factor is part of the historical baseline emissions calculation, a factor that ensures that emissions are not overestimated must be used, or additional data must be provided. Similarly, if a control or rule effectiveness factor enters into the estimate of historical baseline emissions, such a factor must be realistic and supported by facts or analysis. For these factors, a high value ( closer to 100 percent control and effectiveness) ensures that emissions are not overestimated.

iv. Projections of 2010 and 2015 Baselines The second step in quantifying SO2 or NOx emissions reductions for non EGUs is to use the historical baseline emissions and project emissions that would be expected in 2010 and 2015 without the CAIR. This step results in the 2010 and 2015 baseline emissions estimates.

The EPA proposed and requested comment on two procedures for estimating the future baselines: one relies on projections based on a number of estimated parameters; the second uses the lower of this projection and actual historical emissions. 480 Today, EPA finalizes the second approach for determining 2010 and 2015 emissions baselines.

To estimate future emissions, States must use state of

theart methods for projecting the source or source category's economic output. Economic and population forecasts must be as specific as possible to the applicable industry, State, and county of the source and must be consistent with both national projections and relevant official planning assumptions,

including estimates of population and vehicle miles traveled developed through consultation between State and local transportation and air quality agencies. However, if these official planning assumptions are themselves inconsistent with official U. S. Census projections of population or with energy consumption projections contained in the most recent Annual Energy Outlook published by the U. S. Department of Energy, then adjustments must be made to correct the inconsistency, or the SIP must demonstrate how the official planning assumptions are more accurate. If the State expects changes in production method, materials, fuels, or efficiency to occur between the baseline year and 2010 or 2015, the State must account for these changes in the projected 2010 and 2015 baseline emissions. For example, if a source has publicly announced a change or applied for a permit for a change, it should be reflected in the projections. The projection must also reflect any adopted 481 regulations that are ineligible control measures and that will affect source emissions.